Дисертації з теми "Wearable robotic"

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2015.
"June 2015." Cataloged from PDF version of thesis.
Includes bibliographical references (pages 135-136).
The work of this thesis aims to enable the fast prototyping of multi-axis wearable robotic systems by developing a new modular electronics system. The flexible, scalable electronics architecture (FlexSEA) developed for this thesis fills the void between embedded systems used in commercial devices and in research prototypes. This system provides the required hardware and software for precise motion control, data acquisition, and networking. Scalability is obtained through the use of fast industrial communication protocols between the modules, and the standardization of the peripheral interfaces. Hardware and software encapsulation is used to provide high-performance, real-time control of the actuators while keeping the high-level control development fast, safe and simple. The FlexSEA kits are composed of two custom circuit boards (advanced brushless motor driver and microcontroller board), one commercial embedded computer, a complete software stack and documentation. During its development it has been integrated into a powered prosthetic knee as well as an autonomous ankle exoskeleton. To assess the usability of the FlexSEA kit, a new user successfully used a kit to read sensors and control an output device in less than three hours. FlexSEA simplifies and accelerates wearable robotics prototyping.
by Jean-François Duval.
S.M.

Stretchable electronic systems are needed in realising a wide range of applications, such as wearable healthcare monitoring where stretching movements are present. Current electronics and sensors are rigid and non-stretchable. However, after integrating with stretchable interconnects, the overall system is able to withstand a certain degree of bending, stretching and twisting. The presence of stretchable interconnects bridges rigid sensors to stretchable sensing networks. In this thesis, stretchable interconnects focusing on the conductive polymer Poly (3,4-ethylenedioxythiophene): poly (4-styrenesulfonate) (PEDOT:PSS) , the composite and the metallic-polyimide (PI) are presented. Three type of stretchable interconnects were developed including gold (Au) -PEDOT:PSS hybrid film interconnects, Graphite-PEDOT:PSS composite interconnects and Au-PI dual-layered interconnects. The Au-PEDOT:PSS hybrid interconnects' stretchability can reach 72%. The composite exhibits a stretchability of 80% but with an extremely high variation in resistance (100000%). The Au-PI interconnects that have a serpentine shape with the arc degree of 260° reveal the highest stretchability, up to 101%, and its resistance variation remains within 0.2%. Further, the encapsulation effect, cyclic stretching, and contact pad's influence, are also investigated. To demonstrate the application of developed stretchable interconnects, this thesis also presents the optimised interconnects integrated with the electrochemical pH sensor and CNT-based strain sensor. The integrated stretchable system with electrochemical pH sensor is able to wirelessly monitor the sweat pH. The whole system can withstand up to 53% strain and more than 500 cycles at 30% strain. For the CNT-based strain sensor, the sensor is integrated on the pneumatically actuated soft robotic finger to monitor the bending radius (23 mm) of the finger. In this way, the movement of the soft robotic finger can be controlled. These two examples of sensor's integration with stretchable interconnects successfully demonstrate the concept of stretchable sensing network. Further work will focus on realising a higher density sensing and higher multifunctional sensing stretchable system seamlessly integrated with cloth fibres.

Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 22).
The Supernumerary Robotic Limbs (SRL) is a wearable robot that augments its user with two robotic limbs, kinematically independent from the user's own limbs. This thesis explores the use of the SRL as a hands-free robotic crutch for assisting injured or elderly people. This paper first details the mechanical and material design choices that drastically reduced the weight of this SRL prototype, including advanced composite materials, efficient joint structure, and high-performance pneumatic actuators. The latter half of this paper characterizes the biomechanics of both traditional crutch-assisted and SRL-assisted ambulation, models this gait pattern with an inverted pendulum system, and derives equations of motion to create a simulation that examines the effect of various initial parameters. Finally, an optimum set of initial parameters is identified to produce a successful SRL-assisted swing.
by Michael Yanshun Cheung.
S.B.

Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 31).
Presented is work on the development of the Supernumerary Robotic Limbs project, headed by Federico Parietti in the d'Arbeloff Labs under Prof. Harry Asada. Specifically, this paper focuses on the integration of lightweight, pneumatic systems for prismatic joint actuation, and the various control schemes studied. This joint serves as the leg of the robot, and extends from the hip of the wearer to contact the ground. The design consists of a two-way pneumatic cylinder inside a load bearing carbon fiber sleeve, actuated with a nominally closed 5-3 way solenoid valve, and weighs in at <1kg per actuator. The positional control scheme is closed via tracking from a linear magnetopotentiometer, while the force control scheme utilizes both the positional tracking as well as a load cell at the foot of the leg. System modeling of the actuator dynamics allowed for development of a model based proportional control method. Optimization of the proportional gain and system delay time produced a rise time of 200ms given a step input command for a 250mm stroke. The developed scheme was implemented in the full wearable system to assist a human support weight in crouched positions and standing up from a sitting position. Initial testing has shown the effectiveness of the power, compactness and compliance of pneumatic systems in a wearable robotic device.
by Roger Lo.
S.B.

This report details the design, development, and testing of a man-wearable operator control station for the use of a low-cost robotic system in Urban Search and Rescue (USAR). The complete system, dubbed the "Scarab", is the 1st generation developed and built in the Robotics and Agents Research Laboratory (RARL) at the University of Cape Town (UCT), and was a joint effort between three MSc students. Robots have found a place in USAR as replaceable units which can be deployed into dangerous and confined voids in the place of humans. As such, they have been utilized in a large variety of disaster environments including ground, aerial, and underwater scenarios, and have been gathering research momentum since their first documented deployment in the rescue operations surrounding the 9/11 terrorist attacks. However one issue is their cost as they are not economical solutions, making them less viable for inclusion into a rescue mission as well as negatively affecting the operator‟s decisions in order to prioritise the safety of the unit. Another concern is their difficulty of transport, which becomes dependent on the size and portability of the robot. As such, the Scarab system was conceived to provide a deployable robotic platform which was lowcost, with a budget goal of US $ 500. To address the transportability concerns, it aimed to be portable and light-weight; being able to be thrown through a window by a single hand and withstanding a drop height of 3 m. It includes an internal sensor payload which incorporates an array of sensors and electronics, including temperature monitors and two cameras to provide both a normal and IR video feed. Two LED spotlights are used for navigation, and a microphone and buzzer is included for interaction with any discovered survivors. The operator station acts as the user interface between the operator and the robotic platform. It aimed to be as intuitive as possible, providing quick deployment and minimalizing the training time required for its operation. To further enhance the Scarab system‟s portability, it was designed to be a manwearable system, allowing the operator to carry the robotic platform on their back. It also acts as a charging station, supplying power to the robotic platform‟s on-board charging circuitry. The control station‟s mechanical chassis serves as the man-wearable component of the system, with the functionality being achieved by integration onto a tactical vest. This allows the operator to take the complete system on and off as a single unit without assistance, and uses two mounting brackets to dock the robotic platform. Key areas focussed upon during design were the weight and accessibility of the system, as well as providing a rugged housing for the internal electronics. All parts were manufactured in the UCT Mechanical Engineering workshop.

付記する学位プログラム名: デザイン学大学院連携プログラム
Kyoto University (京都大学)
0048
新制・課程博士
博士(工学)
甲第21759号
工博第4576号
新制||工||1713(附属図書館)
京都大学大学院工学研究科機械理工学専攻
(主査)教授 松野 文俊, 教授 椹木 哲夫, 教授 小森 雅晴
学位規則第4条第1項該当

In the latest years, robotic technologies have been increasingly introduced in rehabilitation with the main purpose of reducing the costs and speeding up the recovery process of patients. However, most of the commercial devices impose a pre-programmed trajectory to the limbs of the patients, who therefore behave in a passive way. Another current major limitation is the inability to accurately evaluate the dynamics of the interaction between the patient and the robotic device. This interaction plays a central role in the mutual modulation of human and robot system behavior with respect of their standalone behavior. In particular, the prediction of the interaction can provide useful information to better design the exoskeleton as well as the rehabilitation treatment. This thesis presents my proposed solution for the development of a simulator able to dynamically simulate at the same time the actuated robot device, the human body, and their emerging physical interaction during the movement cooperation. The main idea behind this solution is to decompose the main system in different levels. I called the proposed solution Multi-Level modeling approach, which is the main topic of this thesis. I proposed the following decomposition: Human, Robot, and Boundary Level. The levels are integrated into a whole system in which each of them addresses specific challenges. The Human Level represents the subject who is wearing, for example, an exoskeleton for the lower limbs. To reach a symbiotic collaboration between the subject and the exoskeleton, the proposed approach has to include the subject's intentions and efforts. Moreover, user's internal transformations provide important information about the internal dynamic parameters modulation due to the external device. The Robot Level consists of the wearable robot system which supports the movements. Our proposed approach includes models of both device mechanics and control strategies. This allows to test different control strategies and find the one that better fits each specific patient's needs and characteristics. The last level is the Boundary Level, which has the main objective to model the human-robot mechanical power transfer, including also the non-idealities (such as dissipative forces), in order to accurately estimate interactions. Challenges emerged during the development of the simulator system were faced, investigating different solutions, and selecting and validating the most promising one. First, I selected a common software platform, able to simultaneously reproduce the dynamic behavior of the three levels. The common software platform allows to build a quite flexible system where different solution could be evaluated simply modifying model parameters. Among different available software, OpenSim was selected because it is well known and used for the dynamic study of human movement. Although OpenSim was well tested in biomechanics, it required a further evaluation as simulator for Robot and Boudary Levels. Performed tests and their motivations are reported in this work. Human internal dynamics parameters are modulated by the influence of the external device. I proposed to monitor this variation, taking into consideration the neural drive sent to the muscles. This can be done by measuring the muscles' electromyographic (EMG) signals, which are the electrical potential generated by muscle cells when they are activated, prior to muscle contraction. These signals can be used as input for a physiologically accurate human musculoskeletal model, to calculate the subject contribution to the movement. As the relation between EMGs and the generated muscle forces and joint moments is not linear, the neuromusculoskeletal model is indeed needed to replicate step-by-step all the internal transformations which occur from the excitation of the muscle to the joint movement. Estimation of the emerging interaction, during the human-robot cooperation, can be performed through an interaction model which is basically a set of contact models. Due to the specific rehabilitation purpose of our work, this contact model needs special attention. I introduced and validated a procedure to calibrate the contact models to improve the accuracy of the estimated interaction forces. One of the problems of using EMG signals is that, in order to acquire them in a non-invasive way, surface electrodes must be used; however, this means that the collected data quality is quite susceptible to the electrodes placements and decay, and to electric and magnetic interferences. In many contexts, such as home rehabilitation, this could be a limitation. An alternative solution to avoid the direct EMG measurement is presented in this work. The idea is that for some repetitive tasks, which are most interesting for rehabilitation, it is possible to substitute the direct data collection with a subject specific model of EMGs. The objective of this work is to provide an effective approach to estimate the emerging interaction during the human-robot movement cooperation. The Multi-Level Modeling approach, presented in this thesis, decomposes this complex problem allowing to find all the required components to realize a whole system able to reach this objective.
Negli ultimi anni, la riabilitazione sfrutta sempre di più dispositivi robotici al fine di ridurre i costi e velocizzare il processo di recupero dei pazienti. Finora però, la maggior parte dei dispositivi disponibili sul mercato porta il soggetto a comportarsi in modo passivo, imponendo traiettorie preprogrammate ai pazienti. Un'ulteriore limitazione delle attuali tecnologie è l'incapacità di valutare accuratamente la dinamica dell'interazione tra il paziente e il dispositivo robotico. Tale interazione gioca un ruolo centrale nella mutua modulazione del comportamento dell'essere umano e del sistema robotico, che risulerà diverso rispetto a quello indipendente. In particolare, la predizione di questa interazione può fornire informazioni utili per migliorare sia il design dell'esoscheletro che il processo di riabilitazione. Questa tesi presenta la soluzione che propongo per lo sviluppo di un simulatore in grado di simulare dinamicamente il movimento che risulta dalla cooperazione dell'essere umano e del dispositivo robotico. L'idea principale su cui si basa questa soluzione è di decomporre il sistema in diversi livelli. La soluzione proposta è stata chiamata Multi-Level modeling approach ed è l'argomento principale di questa tesi. La decomposizione proposta si articola in tre livelli: Human, Robot, e Boundary. I livelli sono poi integrati in un unico sistema in cui ogni livello si occupa di rispondere a specifici problemi. Il livello Human rappresenta il soggetto che sta indossando il sistema robotico, ad esempio un esoscheletro per gli arti inferiori. Per raggiungere una collaborazione simbiotica tra il soggetto e l'esoscheletro, l'approccio deve includere le intenzioni del soggetto e monitorare i suoi sforzi per raggiungere il movimento desiderato. Conoscere le trasformazioni interne all'utente possono fornire importanti informazioni sulla modulazione dei parametri dinamici interni dovuti al dispositivo esterno. Il livello Robot si concentra sul sistema robotico indossabile che supporta i movimenti. L'approccio si propone di modellare sia i meccanismi del dispositivo che le strategie di controllo. Questo permette di testare diverse strategie di controllo per trovare quella che meglio si adatta agli specifici bisogni del paziente e alle sue caratteristiche. L'ultimo livello è il Boundary, che ha come obiettivo principale quello di modellare il meccanismo di trasferimento di energia meccanica, includendo anche le non idealità (come le forze dissipative), per riuscire a stimare accuratamente l'interazioni risultante. Diverse sfide sono emerse durante lo sviluppo del sistema complessivo, che sono state affrontate investigando diverse soluzioni, selezionando e validando la più promettente. Il primo problema è stato individuare una piattaforma software comune ai tre livelli in grado di riprodurre simultaneamente il loro comportamento dinamico. Tra i diversi software disponibili ho selezionato OpenSim perchè molto conosciuto e già usato per lo studio della dinamica del movimento umano. Anche se OpenSim è già testato nell'ambito biomeccanico, era necessaria un'ulteriore valutazione come simulatore per i livelli Robot e Boundary. In questo lavoro sono stati presentati quali analisi sono state compiute e i risultati ottenuti. I parametri dinamici interni dell'essere umano sono modulati ed influenzati dei dispositivi esterni. Ho quindi proposto di monitorare queste variazioni, prendendo in considerazione il comando neurale che viene inviato ai muscoli. Questo può essere eseguito misurando l'attività elettromiografica dei muscoli, cioè il potenziale elettrico generato dal muscolo quando viene attivato, prima della contrazione muscolare. Questi segnali possono essere usati come ingresso per un modello dell'apparato muscoloscheletrico umano al fine di calcolare il contributo del soggetto al movimento. L'uso di questo modello si rende necessario a causa delle relazioni non lineari tra gli EMG e le forze muscolari generate e quindi i momenti ai giunti. La stima delle forze di interazione che emergono durante la cooperazione uomo-robot può essere effettuata attraverso un modello di interazione che è fondamentalmente un insieme di modelli di contatto. A causa delle specifiche caratteristiche del nostro lavoro dedicato alla riabilitazione, questo modello di contatto richiede maggiori attenzioni. Per questo ho introdotto e validato una procedura per calibrare i modelli di contatto e migliorare l'accuratezza delle forze di interazione stimate. Uno dei problemi nell'usare i segnali EMG è che è necessario utilizzare degli elettrodi di superficie per acquisirli in modo non invasivo; questo però significa che la qualità dei dati raccolti è molto sensibile alla disposizione degli elettrodi e al loro decadimento, oltre che alle interferenze magnetiche e elettriche. In molti contesti, come la riabilitazione a casa, questo può costituire una forte limitazione. Una soluzione alternativa per evitare la misura diretta degli EMG è presentata in questo lavoro. L'idea è che per azioni ripetitive, che sono spesso di grande interesse nella riabilitazione, sia possibile sostituire la raccolta dati diretta con un modello degli EMG calibrato sul soggetto. L'obiettivo di questo lavoro è stato di proporre un approccio efficace per la stima delle iterazioni che emergono durante il movimento cooperativo uomo-robot. L'approccio Multi-Level Modeling, che è stato presentato in questa tesi, decompone questo problema complesso permettendo di sviluppare tutti i componenti necessari alla realizzazione di un sistema completo che sia in grado di raggiungere l'obiettivo finale.

In their daily lives, stroke survivors must often choose between attempting upper-extremity activities using their impaired limb, or compensating with their less impaired limb. Choosing their impaired limb can be difficult and discouraging, but might elicit beneficial neuroplasticity that further reduces motor impairments, a phenomenon referred to as “the virtuous cycle”. In contrast, compensation is often quicker, easier, and more effective, but can reinforce maladaptive changes that limit motor recovery, a phenomenon referred to as “learned non-use”. This dissertation evaluated the role of robotic assistance in, and designed a wearable sensing system for, promoting the virtuous cycle.

In the first half of the dissertation, we use the FINGER robot to test the hypothesis that robotic assistance during clinical movement training triggers the virtual cycle. FINGER consists of two singly-actuated mechanisms that assist individuated movement of the index and middle fingers. 30 chronic stroke participants trained in FINGER using a GuitarHero-like game for nine sessions. Half were guided by an adaptive impedance controller towards a success rate of 85%, while the other half were guided towards 50%. Increasing assistance to enable successful practice decreased effort, but primarily for less-impaired participants. Overall, however, high success practice was as effective (or more) as low success practice and even more effective for highly impaired individuals. Participants who received high assistance training were more motivated and reported using their impaired hand more at home. These results support the hypothesis that high assistance clinical movement training motivates impaired hand use, leading to greater use of the hand in daily life, resulting in a self-training effect that reduces motor impairment.

The second half of the dissertation describes the development of the manumeter - a non-obtrusive wearable device for monitoring and incentivizing impaired hand use. Contrasted against wrist accelerometry (the most comparable technology), the manumeter uses a magnetic ring and a wristband with mangetometers to detect wrist and finger movement rather than gross arm movement. We describe 1) the inference of wrist and finger movement from differential magnetometer readings using a radial basis function network, 2) initial testing in which distance traveled estimates were within 94.7%±19.3 of their goniometricly measured values, 3) experiments with non-impaired participants in which the manumeter detected some functional activities better than wrist accelerometry, and 4) improvements to the hardware and data processing that allow both subject-independent tracking of the position of the finger relative to the wrist (RMS errors < 1cm) and highly reliable detection of whether the hand is open or closed. Its performance and non-obtrusive design make the manumeter well suited for measuring and reinforcing impaired hand use in daily life after stroke.

The contributions of this dissertation are experimental confirmation that high assistance movement training promotes the virtuous cycle, and development of a wearable sensor for monitoring hand movement in daily life. Training with robotic assistance and hand use feedback may ultimately help individuals with stroke recover to their full potential.

The following thesis project aims to study and realize a wearable manipulation system composed by an AR10 robotic hand, controlled via myoelectric signals and tactile sensors for prosthetic studies. The project starts with the kinematic study of the hand via MATLAB and Simulink, in order to obtain a complete insight on the robotic grasping device. Thereafter, a wearable support has been designed and printed to fix the robotic hand around the user forearm. Surface electromyography is acquired using a gForce gesture armband. A Simulink system has been developed to acquire and filter the signals, then the myoelectric data are elaborated to derive the command for the robotic hand. Tactile sensors are added by means of custom 3D-printed support on the fingertips in order to get a force feedback to allow the user to perform the grasp of different objects. Finally, in order to test the whole solution, a subject wearing the whole manipulation system carried out a series of tasks to evaluate the system’s usability during dynamic grasps of different objects. The results of the tests report the accuracy of the manipulation system. The main goal of the project is to test a wearable manipulation system made to be worn by intact subjects, in order to study prosthetic grasping scenarios that can provide results useful for future developments involving amputees.

The Humanoid Walking Robot (HWR) is a research platform for the study of legged and wearable robots actuated with Hydro Muscles. The fluid operated HWR is representative of a class of biologically inspired, and in some aspects highly biomimetic robotic musculoskeletal appendages showing certain advantages in comparison to more conventional artificial limbs and braces for physical therapy/rehabilitation, assistance of daily living, and augmentation. The HWR closely mimics the human body structure and function, including the skeleton, ligaments, tendons, and muscles. The HWR can emulate close to human-like movements even when subjected to simplified control laws. One of the main drawbacks of this approach is the inaccessibility of an appropriate fluid flow management support system, in the form of affordable, lightweight, compact, and good quality valves suitable for robotics applications. To resolve this shortcoming, the Compact Robotic Flow Control Valve (CRFC Valve) is introduced and successfully proof-of-concept tested. The HWR added with the CRFC Valve has potential to be a highly energy efficient, lightweight, controllable, affordable, and customizable solution that can resolve single muscle action.

In the past decade, Human Activity Recognition (HAR) has been an important part of the regular day to day life of many people. Activity recognition has wide applications in the field of health care, remote monitoring of elders, sports, biometric authentication, e-commerce and more. Each HAR application needs a unique approach to provide solutions driven by the context of the problem. In this dissertation, we are primarily discussing two application of HAR in different contexts. First, we design a novel approach for in-home, fine-grained activity recognition using multimodal wearable sensors on multiple body positions, along with very small Bluetooth beacons deployed in the environment. State-of-the-art in-home activity recognition schemes with wearable devices are mostly capable of detecting coarse-grained activities (sitting, standing, walking, or lying down), but cannot distinguish complex activities (sitting on the floor versus on the sofa or bed). Such schemes are not effective for emerging critical healthcare applications – for example, in remote monitoring of patients with Alzheimer's disease, Bulimia, or Anorexia – because they require a more comprehensive, contextual, and fine-grained recognition of complex daily user activities. Second, we introduced Watch-Dog – a self-harm activity recognition engine, which attempts to infer self-harming activities from sensing accelerometer data using wearable sensors worn on a subject's wrist. In the United States, there are more than 35,000 reported suicides with approximately 1,800 of them being psychiatric inpatients every year. Staff perform intermittent or continuous observations in order to prevent such tragedies, but a study of 98 articles over time showed that 20% to 62% of suicides happened while inpatients were on an observation schedule. Reducing the instances of suicides of inpatients is a problem of critical importance to both patients and healthcare providers. Watch-dog uses supervised learning algorithm to model the system which can discriminate the harmful activities from non-harmful activities. The system is not only very accurate but also energy efficient. Apart from these two HAR systems, we also demonstrated the difference in activity pattern between elder and younger age group. For this experiment, we used 5 activities of daily living (ADL). Based on our findings we recommend that a context aware age-specific HAR model would be a better solution than all age-mixed models. Additionally, we find that personalized models for each individual elder person perform better classification than mixed models.

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 65-67).
A new 'axial-transverse flux' motor (ATFM) topology is of interest to autonomous lower-extremity robotics designers for its high torque density and low winding resistance. Unfortunately, deliberate asymmetries in the design make finite-element modeling of this topology largely intractable. An ATFM prototype was characterized experimentally using a custom dynamometer and controller. The prototype was found to have a torque constant Kt of 7.26 Nm/A and a per-phase winding resistance of 0.59 Ohms. It is characterized by high AC and DC zero-current torque, as well as significant torque ripple (M: 12.9%, SD: 0.6%) when driven with balanced three-phase sinusoidal commutation. A set of optimized commutation waveforms are developed based on an independent phase control strategy, and it is shown that this strategy can eliminate ripple in simulation and reduce it in practice (M: 7.8%, SD: 0.5%), without reduction of mean torque or increased conduction losses relative to sinusoidal commutation.
by Madeleine Rose Abromowitz.
S.M.

On-the-go users' interaction with mobile devices often requires high visual attention that can overtax limited human resources. For example, while attending information displayed on a mobile device, on-the-go users who are driving a car or walking in the street can easily fail to see a dangerous situation. This dissertation explores the benefits of wearable tactile displays (WTDs) to support eyes-free interaction for on-the-go users. The design and implementation of the WTDs are motivated by two principles in mobile user interaction that have been proven both commercially and academically: wristwatch interfaces that reduce the time for device acquisition and tactile interfaces that eliminate the need for visual attention. In this dissertation, I present three phases of design iteration on WTDs to provide the design rationale and challenges. The result of the iterative design is evaluated through in-depth formal investigations with novice users in two experiments: user perception of the tactile stimuli and information throughput in association with multiple tactile parameters, and perception of the tactile stimuli and information throughput when the user is visually distracted. The first experiment explores general human capabilities in perceiving tactile stimuli on the wrist. It reveals that subjects could discriminate 24 tactile patterns with 98% accuracy after 40 minutes of training. Of the four parameters (intensity, starting point, rhythm, direction) that were configured to design the 24 patterns, intensity was the most difficult parameter to distinguish, and temporal variation was the easiest. The second experiment explores users' abilities to perceive incoming alerts from two mobile devices (WTD and mobile phone) with and without visual distraction. The second experiment reveals that when the user was distracted visually, reaction time to perceive the incoming alerts became slower with the mobile phone alert but not with the WTD.

This thesis presents the development and implementation of a machine learning prediction model for concurrently aggregating interval linear step distance predictions before future foot placement. Specifically, on-body inertial measurement units consisting of accelerometers, gyroscopes, and magnetometers, through integrated development by Xsens, are used for measuring human walking behavior in real-time. The data collection process involves measuring activity from two subject participants who travel an intended course consisting of flat, stair, and sloped walking elements. This work discusses the formulation of the ensemble machine learning prediction algorithm, real-time application design considerations, feature extraction and selection, and experimental testing under which this system performed several different test case conditions. It was found that the system was able to predict the linear step distances for 47.2% of 1060 steps within 7.6cm accuracy, 67.5% of 1060 steps within 15.2cm accuracy, and 75.8% of 1060 steps within 23cm. For separated flat walking, it was found that 93% of the 1060 steps have less than 25% error, and 75% of the 1060 steps have less than 10% error which is an improvement over the commingled data set. Future applications and work to expand upon from this system are discussed for improving the results discovered from this work.
Master of Science

A wearable robot should know its environment and its location in order to help its operator. Wearable robots are becoming more feasible with the development of more powerful and smaller computing devices and cameras. The main aim of this research is to build a wearable robot with a low cost stereo camera system which explores a room sized unknown environment online and automatically. To achieve 3D localization and map building for the wearable robot, a consistent visual-SLAM algorithm is implemented by using point features in the environment and Extended Kalman Filter for state estimation. The whole system includes camera models and calibration, feature extraction, depth measurement and Extended Kalman Filter algorithm. Moreover, a map management algorithm is developed. This algorithm keeps the number of features spatially uniform in the scene and adds new features when feature number decreases in a frame. Furthermore, a user-interface is presented so that the location of the camera,the features and the constructed map are visualized online. Most importantly, the system is conducted by a low-cost stereo system.

Industrial robots are delivering more and more manipulation services in manufacturing. However, when the task is complex, it is difficult to programme a robot to fulfil all the requirements because even a relatively simple task such as a peg-in-hole insertion contains many uncertainties, e.g. clearance, initial grasping position and insertion path. Humans, on the other hand, can deal with these variations using their vision and haptic feedback. Although humans can adapt to uncertainties easily, most of the time, the skilled based performances that relate to their tacit knowledge cannot be easily articulated. Even though the automation solution may not fully imitate human motion since some of them are not necessary, it would be useful if the skill based performance from a human could be firstly interpreted and modelled, which will then allow it to be transferred to the robot. This thesis aims to reduce robot programming efforts significantly by developing a methodology to capture, model and transfer the manual manufacturing skills from a human demonstrator to the robot. Recently, Learning from Demonstration (LfD) is gaining interest as a framework to transfer skills from human teacher to robot using probability encoding approaches to model observations and state transition uncertainties. In close or actual contact manipulation tasks, it is difficult to reliabley record the state-action examples without interfering with the human senses and activities. Therefore, wearable sensors are investigated as a promising device to record the state-action examples without restricting the human experts during the skilled execution of their tasks. Firstly to track human motions accurately and reliably in a defined 3-dimensional workspace, a hybrid system of Vicon and IMUs is proposed to compensate for the known limitations of the individual system. The data fusion method was able to overcome occlusion and frame flipping problems in the two camera Vicon setup and the drifting problem associated with the IMUs. The results indicated that occlusion and frame flipping problems associated with Vicon can be mitigated by using the IMU measurements. Furthermore, the proposed method improves the Mean Square Error (MSE) tracking accuracy range from 0.8˚ to 6.4˚ compared with the IMU only method. Secondly, to record haptic feedback from a teacher without physically obstructing their interactions with the workpiece, wearable surface electromyography (sEMG) armbands were used as an indirect method to indicate contact feedback during manual manipulations. A muscle-force model using a Time Delayed Neural Network (TDNN) was built to map the sEMG signals to the known contact force. The results indicated that the model was capable of estimating the force from the sEMG armbands in the applications of interest, namely in peg-in-hole and beater winding tasks, with MSE of 2.75N and 0.18N respectively. Finally, given the force estimation and the motion trajectories, a Hidden Markov Model (HMM) based approach was utilised as a state recognition method to encode and generalise the spatial and temporal information of the skilled executions. This method would allow a more representative control policy to be derived. A modified Gaussian Mixture Regression (GMR) method was then applied to enable motions reproduction by using the learned state-action policy. To simplify the validation procedure, instead of using the robot, additional demonstrations from the teacher were used to verify the reproduction performance of the policy, by assuming human teacher and robot learner are physical identical systems. The results confirmed the generalisation capability of the HMM model across a number of demonstrations from different subjects; and the reproduced motions from GMR were acceptable in these additional tests. The proposed methodology provides a framework for producing a state-action model from skilled demonstrations that can be translated into robot kinematics and joint states for the robot to execute. The implication to industry is reduced efforts and time in programming the robots for applications where human skilled performances are required to cope robustly with various uncertainties during tasks execution.

With the advent of ever smaller and more powerful portable computing devices, and ever smaller cameras, wearable computing is becoming more feasible. The ever increasing numbers of augmented reality applications are allowing users to view additional data about their world overlaid on their world using portable computing devices. The main aim of this research is to enable a user of a wearable robot to explore large environments automatically viewing augmented reality at locations and on objects of interest. To implement this research a wearable visual robotic assistant is designed and constructed. Evaluation of the different technologies results in a final design that combines a shoulder mounted self stabilizing active camera, and a hand held magic lens into a single portable system. To enable the wearable assistant to locate known objects, a system is designed that combines an established method for appearance-based recognition with one for simultaneous localization and mapping using a single camera. As well as identifying planar objects, the objects are located relative to the camera in 3D by computing the image-to-database homography. The 3D positions of the objects are then used as additional measurements in the SLAM process, which routinely uses other point features to acquire and maintain a map of the surroundings, irrespective of whether objects are present or not. The monocular SLAM system is then replaced with a new method for building maps and tracking. Instead of tracking and mapping in a linear frame-rate driven manner, this adopted method separates the mapping from the tracking. This allows higher density maps to be constructed, and provides more robust tracking. The flexible framework provided by this method is extended to support multiple independent cameras, and multiple independent maps, allowing the user of the wearable two-camera robot to escape the confines of the desk top and explore arbitrarily sized environments. The final part of the work brings together the parallel tracking and multiple mapping system with the recognition and localization of planar objects from a database. The method is able to build multiple feature rich maps of the world and simultaneously recognize, reconstruct and localize objects within these maps. The object reconstruction process uses the spatially separated keyframes from the tracking and mapping processes to recognize and localize known objects in the world. These are then used for augmented reality overlays related to the objects.

Wearable assistive robotics have the potential to address an unmet medical need of reducing disability in individuals with chronic hand impairments due to neurological trauma. Despite myriad prior works, few patients have seen the benefits of such devices. Following application experience with tendon-actuated soft robotic gloves and a collaborator's orthosis with novel flat-spring actuators, we identified two common assumptions regarding hand orthosis design. The first was reliance on incomplete studies of grasping forces during activities of daily living as a basis for design criteria, leading to poor optimization. The second was a neglect of increases in muscle tone following neurological trauma, rendering most devices non-applicable to a large subset of the population. To address these gaps, we measured joint torques during activities of daily living with able-bodied subjects using dexterity representative of orthosis-aided motion. Next, we measured assistive torques needed to extend the fingers of individuals with increased flexor tone following TBI. Finally, we applied this knowledge to design a cable actuated orthosis for assisting finger extension, providing a basis for future work focused on an under-represented subgroup of patients.

In recent years, soft materials have seen increased prevalence in the design of robotic systems and wearables capable of addressing the needs of individuals living with disabilities. In particular, pneumatic artificial muscles (PAMs) have readily been employed in place of electromagnetic actuators due to their ability to produce large forces and motions, while still remaining lightweight, compact, and flexible. Due to the inherent nonlinearity of PAMs however, additional external or embedded sensors must be utilized in order to effectively control the overall system. In the case of external sensors, the bulkiness of the overall system is increased, which places limits on the system’s design. Meanwhile, the traditional cylindrical form factor of PAMs limits their ability to remain compact and results in overly complex fabrication processes when embedded fibers and/or sensing elements are required to provide efficient actuation and control. In order to overcome these limitations, this thesis proposed the design of flat pneumatic artificial muscles (FPAMs) capable of being fabricated using a simple layered manufacturing process, in which water-soluble masks were utilized to create collapsed air chambers. Furthermore, hyperelastic deformation models were developed to approximate the mechanical performance of the FPAMs and were verified through experimental characterization. The feasibility of these design techniques to meet the requirements of human centered applications, including the suppression of hand tremors and catheter ablation procedures, was explored and the potential for these soft actuation systems to act as solutions in other real world applications was demonstrated. We expect the design, fabrication, and modeling techniques developed in this thesis to aid in the development of future wearable devices and motivate new methods for researchers to employ soft pneumatic systems as solutions in human-centered applications.

The work presented in this paper aims at developing a hydraulic actuation system for an ankle exoskeleton that is able to deliver a peak power of 250 W, with a maximum torque of 90 N.m and maximum speed of 320 deg/s. After justifying the choice of a servo hydraulic actuator (SHA) over an electro hydrostatic actuator (EHA) for the targeted application, some test results of a first functional prototype are presented. The closed-loop unloaded displacement frequency response of the prototype shows a bandwidth ranging from 5 Hz to 8 Hz for displacement amplitudes between +/-5mm and +/- 20mm, thus demonstrating adequate dynamic performance for normal walking speed. Then, a detailed design is proposed as a combination of commercially available components (in particular a miniature servo valve and a membrane accumulator) and a custom aluminium manifold that incorporates the hydraulic cylinder. The actuator design achieves a total weight of 1.0 kg worn at the ankle.

Questo lavoro ha l’obiettivo di analizzare e mettere in evidenza come il progresso tecnologico abbia contribuito ad una efficace risposta allo stato di emergenza che ha colpito il globo a causa del Covid-19. In primo luogo è stata messa in luce l’importanza della Telemedicina, uno strumento che fino all’inizio della pandemia era stato poco considerato, ma che si è rivelato di fondamentale importanza per garantire le cure a distanza, in particolare a pazienti con malattie croniche. Un altro ruolo fondamentale è svolto dall’Intelligenza Artificiale: dalla diagnostica, che ha consentito un’analisi più accurata delle immagini radiografiche dei pazienti, all’impiego dei robot infermieri, fondamentali per salvaguardare la salute degli operatori sanitari. Infine vengono presi in considerazione diversi progetti che vanno dal contact tracing, ai dispositivi indossabili per ricordare agli utenti di mantenere una certa distanza di sicurezza, fino alla creazione di particolari mascherine.

The purpose of this thesis is to explore the subject of industrial exoskeleton in accord-ance to the applicability of the technology preventing musculoskeletal disorders within the automotive industry. The modern technology of exoskeletons has a limited field of research and knowledge and is in need to be studied to provide organisations with proper findings for understanding the applicability of the technology. In the auto-motive industry musculoskeletal disorders (MSDs) is one of the most common disor-ders among employees and industries work constantly to decrease and prevent MSDs within their work environments. By conducting literature reviews, the status of exo-skeleton research and development concluded that academic research mostly focuses on technological development of exoskeletons, and not laboratory and/or field testing of currently available industrial exoskeletons. However, through database and website searches, twenty-four available industrial exoskeletons were identified which could be applicable within the automotive industry. Through literature and a case illustration, a number of potential causes for MSDs within the automotive industry were identified and a framework was developed in order to match appropriate available industrial ex-oskeleton to be used in potentially preventing common MSDs. The discussion of the thesis highlights the benefits and challenges of implementing an industrial exoskele-ton within an industry. Proper research on the currently available industrial exoskele-tons is lacking and creates questions of reliability for the technology. However, devel-opment of industrial exoskeletons have shown to focus on prevention of the most common causes of MSDs within industries in their design and development, making the applicability of industrial exoskeletons highly possible.

Soft matter, here, liquids and polymers, have adaptability to a surrounding geometry. They intrinsically have advantageous characteristics from a mechanical perspective, such as flowing and wetting on surrounding surfaces, giving compliant, conformal and deformable behavior. From the behavior of soft matter for heterogeneous surfaces, compliant structures can be engineered as embedded liquid microstructures or patterned liquid microsystems for emerging compliant microsystems. Recently, skin electronics and soft robotics have been initiated as potential applications that can provide soft interfaces and interactions for a human-machine interface. To meet the design parameters, developing soft material engineering aimed at tuning material properties and smart processing techniques proper to them are to be highly encouraged. As promising candidates, Ga-based liquid alloys and silicone-based elastomers have been widely applied to proof-of-concept compliant structures. In this thesis, the liquid alloy was employed as a soft and stretchable electrical and thermal conductor (resistor), interconnect and filler in an elastomer structure. Printing-based liquid alloy patterning techniques have been developed with a batch-type, parallel processing scheme. As a simple solution, tape transfer masking was combined with a liquid alloy spraying technique, which provides robust processability. Silicone elastomers could be tunable for multi-functional building blocks by liquid or liquid-like soft solid inclusions. The liquid alloy and a polymer additive were introduced to the silicone elastomer by a simple mixing process. Heterogeneous material microstructures in elastomer networks successfully changed mechanical, thermal and surface properties. To realize a compliant microsystem, these ideas have in practice been useful in designing and fabricating soft and stretchable systems. Many different designs of the microsystems have been fabricated with the developed techniques and materials, and successfully evaluated under dynamic conditions. The compliant microsystems work as basic components to build up a whole system with soft materials and a processing technology for our emerging society.

碩士
國立交通大學
電控工程研究所
101
With the increase of stroke patients, the quality of stroke rehabilitation has drawn much attention in recent years. Researchers have been developed various kinds of exoskeleton devices for specific rehabilitation functions. In this thesis, we have developed a 3 Degrees of Freedom (3DOF) wearable robotic fingers for task-oriented training of rehabilitation grasping tasks. We propose a control strategy for the task training considering user comfort based-on his/her intention and the safety in task training procedure. The control strategy is divided into two parts: user compliance control and grasping compliance control. In user compliance control, we employed a mass-spring-damper model for grasping operation when the user exerted an intention force, this strategy can allow the user to feel comfortable guidance of the movement. In grasping compliance control, a similar physical model is used when the finger exoskeleton comes into contact with the object, that the system will percept the situation immediately and assists an appropriate grasping force for stable grasping. Experimental verification shows that the developed wearable rehabilitation robotic fingers can provide a comfortable fit for the users and is capable to assist the users to achieve the grasping task training.

abstract: The term Poly-Limb stems from the rare birth defect syndrome, called Polymelia. Although Poly-Limbs in nature have often been nonfunctional, humans have had the fascination of functional Poly-Limbs. Science fiction has led us to believe that having Poly-Limbs leads to augmented manipulation abilities and higher work efficiency. To bring this to life however, requires a synergistic combination between robot manipulation and wearable robotics. Where traditional robots feature precision and speed in constrained environments, the emerging field of soft robotics feature robots that are inherently compliant, lightweight, and cost effective. These features highlight the applicability of soft robotic systems to design personal, collaborative, and wearable systems such as the Soft Poly-Limb. This dissertation presents the design and development of three actuator classes, made from various soft materials, such as elastomers and fabrics. These materials are initially studied and characterized, leading to actuators capable of various motion capabilities, like bending, twisting, extending, and contracting. These actuators are modeled and optimized, using computational models, in order to achieve the desired articulation and payload capabilities. Using these soft actuators, modular integrated designs are created for functional tasks that require larger degrees of freedom. This work focuses on the development, modeling, and evaluation of these soft robot prototypes. In the first steps to understand whether humans have the capability of collaborating with a wearable Soft Poly-Limb, multiple versions of the Soft Poly-Limb are developed for assisting daily living tasks. The system is evaluated not only for performance, but also for safety, customizability, and modularity. Efforts were also made to monitor the position and orientation of the Soft Poly-Limbs components through embedded soft sensors and first steps were taken in developing self-powered compo-nents to bring the system out into the world. This work has pushed the boundaries of developing high powered-to-weight soft manipulators that can interact side-by-side with a human user and builds the foundation upon which researchers can investigate whether the brain can support additional limbs and whether these systems can truly allow users to augment their manipulation capabilities to improve their daily lives.
Dissertation/Thesis
Doctoral Dissertation Systems Engineering 2020

abstract: Wearable assistive devices have been greatly improved thanks to advancements made in soft robotics, even creation soft extra arms for paralyzed patients. Grasping remains an active area of research of soft extra limbs. Soft robotics allow the creation of grippers that due to their inherit compliance making them lightweight, safer for human interactions, more robust in unknown environments and simpler to control than their rigid counterparts. A current problem in soft robotics is the lack of seamless integration of soft grippers into wearable devices, which is in part due to the use of elastomeric materials used for the creation of most of these grippers. This work introduces fabric-reinforced textile actuators (FRTA). The selection of materials, design logic of the fabric reinforcement layer and fabrication method are discussed. The relationship between the fabric reinforcement characteristics and the actuator deformation is studied and experimentally verified. The FRTA are made of a combination of a hyper-elastic fabric material with a stiffer fabric reinforcement on top. In this thesis, the design, fabrication, and evaluation of FRTAs are explored. It is shown that by varying the geometry of the reinforcement layer, a variety of motion can be achieve such as axial extension, radial expansion, bending, and twisting along its central axis. Multi-segmented actuators can be created by tailoring different sections of fabric-reinforcements together in order to generate a combination of motions to perform specific tasks. The applicability of this actuators for soft grippers is demonstrated by designing and providing preliminary evaluation of an anthropomorphic soft robotic hand capable of grasping daily living objects of various size and shapes.
Dissertation/Thesis
Masters Thesis Biomedical Engineering 2019

碩士
國立清華大學
動力機械工程學系
102
The development of robotics has gradually advanced from industrial and military use to medical nursing and rehabilitation use. Physical rehabilitation robotics has become the main stream in the medical application, including upper and lower limb rehabilitation robotic devices. Investigated researches in the global have shown that the intensity, repeatability, and the amount of rehabilitation in the process are directly related to the results of the rehabilitation process. Also, the preferable time for rehabilitation process for each patient is crucial the rehabilitation results. The patents will have beneficial recovery results if patents are able to undergo proper rehabilitation process on the preferable time set by the doctors. The method of rehabilitation process is decided by the clinical experience of the doctors and therapists; thus, different rehabilitation methods chosen by the doctors and therapist might lower the result of the rehabilitation process and raise the unnecessary medical cost. The purpose of this study is to design and develop a wearable robotic device for human hand, which focuses on patents who lost their range of motion limitation in their hand movement and suffered from nervous system diseases. The aim of this rehabilitation device is to assist patents in performing repeating hand movement rehabilitation. Also, doctors and therapist can control the setting rehabilitation device to fulfill the needs of the patents. Not only did this study focus on the design and development of a wearable robotic device for human hand but also develop the stiffness measurement system for robotic device. The measured data can be used to determine the level of healthiness of patents' hand in order for the doctors and therapist to decide the appropriate rehabilitation therapy for each individual. Through the development of the rehabilitation device and stiffness measurement system, doctors and therapists can be provided with real time result data to assist them in rehabilitation diagnosis and treatment.

The human spine is an integral part of the human body. Its functions include mobilizing the torso, controlling postural stability, and transferring loads from upper body to lower body, all of which are essential for the activities of daily living. However, the many complex tasks of the spine leave it vulnerable to damage from a variety of sources. Prolonged walking with a heavy backpack can cause spinal injuries. Spinal diseases, such as scoliosis, can make the spine abnormally deform. Neurological disorders, such as cerebral palsy, can lead to a loss of torso control. External torso support has been used in these cases to mitigate the risk of spinal injuries, to halt the progression of spinal deformities, and to support the torso. However, current torso support designs are limited by rigid, passive, and non-sensorized structures. These limitations were the motivations for this work in developing the science for design of torso exoskeletons that can improve the effectiveness of current external torso support solutions. Central features to the design of these exoskeletons were the abilities to sense and actively control the motion of or the forces applied to the torso. Two applications of external torso support are the main focus in this study, backpack load carriage and correction of spine deformities. The goal was to develop torso exoskeletons for these two applications, evaluate their effectiveness, and exploit novel assistive and/or treatment paradigms. With regard to backpack load carriage, current torso support solutions are limited and do not provide any means to measure and/or adjust the load distribution between the shoulders and the pelvis, or to reduce dynamic loads induced by walking. Because of these limitations, determining the effects of modulating these loads between the shoulders and the pelvis has not been possible. Hence, the first scientific question that this work aims to address is What are the biomechanical and physiological effects of distributing the load and reducing the dynamic load of a backpack on human body during backpack load carriage? Concerning the correction of spinal deformities, the most common treatment is the use of a spine brace. This method has been shown to effectively slow down the progression of spinal deformity. However , a limitation in the effectiveness of this treatment is the lack of knowledge of the stiffness characteristics of the human torso. Previously, there has been no means to measure the stiffness of human torso. An improved understanding of this subject would directly affect treatment outcomes by better informing the appropriate external forces (or displacements) to apply in order to achieve the desired correction of the spine. Hence, the second scientific question that this work aims to address is How can we characterize three dimensional stiffness of the human torso for quantifiable assessment and targeted treatment of spinal deformities? In this work, a torso exoskeleton called the Wearable upper Body Suit (WEBS) was developed to address the first question. The WEBS distributes the backpack load between the shoulders and the pelvis, senses the vertical motion of the pelvis, and provides gait synchronized compensatory forces to reduce dynamic loads of a backpack during walking. It was hypothesized that during typical backpack load carriage, load distribution and dynamic load compensation reduce gait and postural adaptations, the user’s overall effort and metabolic cost. This hypothesis was supported by biomechanical and physiological measurements taken from twelve healthy male subjects while they walked on a treadmill with a 25 percent body weight backpack. In terms of load distribution and dynamic load compensation, the results showed reductions in gait and postural adaptations, muscle activity, vertical and braking ground reaction forces, and metabolic cost. Based on these results, it was concluded that the wearable upper body suit can potentially reduce the risk of musculoskeletal injuries and muscle fatigue associated with carrying heavy backpack loads, as well as reducing the metabolic cost of loaded walking. To address the second question, the Robotic Spine Exoskeleton (ROSE) was developed. The ROSE consists of two parallel robot platforms connected in series that can adjust to fit snugly at different levels of the human torso and dynamically modulate either the posture of the torso or the forces exerted on the torso. An experimental evaluation of the ROSE was performed with ten healthy male subjects that validated its efficacy in controlling three dimensional corrective forces exerted on the torso while providing flexibility for a wide range of torso motions. The feasibility of characterizing the three dimensional stiffness of the human torso was also validated using the ROSE. Based on these results, it was concluded that the ROSE may alleviate some of the limitations in current brace technology and treatment methods for spine deformities, and offer a means to explore new treatment approaches to potentially improve the therapeutic outcomes of the brace treatment.

Thesis (M.S.)--Florida State University, 2006.
Advisor: Carl A. Moore, Florida State University, College of Engineering, Dept. of Mechanical Engineering. Title and description from dissertation home page (viewed June 8, 2006). Document formatted into pages; contains x, 107 pages. Includes bibliographical references.

abstract: Lower-limb wearable assistive robots could alter the users gait kinematics by inputting external power, which can be interpreted as mechanical perturbation to subject normal gait. The change in kinematics may affect the dynamic stability. This work attempts to understand the effects of different physical assistance from these robots on the gait dynamic stability. A knee exoskeleton and ankle assistive device (Robotic Shoe) are developed and used to provide walking assistance. The knee exoskeleton provides personalized knee joint assistive torque during the stance phase. The robotic shoe is a light-weighted mechanism that can store the potential energy at heel strike and release it by using an active locking mechanism at the terminal stance phase to provide push-up ankle torque and assist the toe-off. Lower-limb Kinematic time series data are collected for subjects wearing these devices in the passive and active mode. The changes of kinematics with and without these devices on lower-limb motion are first studied. Orbital stability, as one of the commonly used measure to quantify gait stability through calculating Floquet Multipliers (FM), is employed to asses the effects of these wearable devices on gait stability. It is shown that wearing the passive knee exoskeleton causes less orbitally stable gait for users, while the knee joint active assistance improves the orbital stability compared to passive mode. The robotic shoe only affects the targeted joint (right ankle) kinematics, and wearing the passive mechanism significantly increases the ankle joint FM values, which indicates less walking orbital stability. More analysis is done on a mechanically perturbed walking public data set, to show that orbital stability can quantify the effects of external mechanical perturbation on gait dynamic stability. This method can further be used as a control design tool to ensure gait stability for users of lower-limb assistive devices.
Dissertation/Thesis
Masters Thesis Mechanical Engineering 2018

abstract: Wearable robotics has gained huge popularity in recent years due to its wide applications in rehabilitation, military, and industrial fields. The weakness of the skeletal muscles in the aging population and neurological injuries such as stroke and spinal cord injuries seriously limit the abilities of these individuals to perform daily activities. Therefore, there is an increasing attention in the development of wearable robots to assist the elderly and patients with disabilities for motion assistance and rehabilitation. In military and industrial sectors, wearable robots can increase the productivity of workers and soldiers. It is important for the wearable robots to maintain smooth interaction with the user while evolving in complex environments with minimum effort from the user. Therefore, the recognition of the user's activities such as walking or jogging in real time becomes essential to provide appropriate assistance based on the activity. This dissertation proposes two real-time human activity recognition algorithms intelligent fuzzy inference (IFI) algorithm and Amplitude omega ($A \omega$) algorithm to identify the human activities, i.e., stationary and locomotion activities. The IFI algorithm uses knee angle and ground contact forces (GCFs) measurements from four inertial measurement units (IMUs) and a pair of smart shoes. Whereas, the $A \omega$ algorithm is based on thigh angle measurements from a single IMU. This dissertation also attempts to address the problem of online tuning of virtual impedance for an assistive robot based on real-time gait and activity measurement data to personalize the assistance for different users. An automatic impedance tuning (AIT) approach is presented for a knee assistive device (KAD) in which the IFI algorithm is used for real-time activity measurements. This dissertation also proposes an adaptive oscillator method known as amplitude omega adaptive oscillator ($A\omega AO$) method for HeSA (hip exoskeleton for superior augmentation) to provide bilateral hip assistance during human locomotion activities. The $A \omega$ algorithm is integrated into the adaptive oscillator method to make the approach robust for different locomotion activities. Experiments are performed on healthy subjects to validate the efficacy of the human activities recognition algorithms and control strategies proposed in this dissertation. Both the activity recognition algorithms exhibited higher classification accuracy with less update time. The results of AIT demonstrated that the KAD assistive torque was smoother and EMG signal of Vastus Medialis is reduced, compared to constant impedance and finite state machine approaches. The $A\omega AO$ method showed real-time learning of the locomotion activities signals for three healthy subjects while wearing HeSA. To understand the influence of the assistive devices on the inherent dynamic gait stability of the human, stability analysis is performed. For this, the stability metrics derived from dynamical systems theory are used to evaluate unilateral knee assistance applied to the healthy participants.
Dissertation/Thesis
Doctoral Dissertation Aerospace Engineering 2018

Although in many of the tasks in robotics, what is sought mainly includes accuracy, precision, flexibility, adaptivity, etc., yet in wearable robotics, there are some other aspects as well that could distinguish a reliable and promising approach. The three key elements that are addressed are as follows: control, actuation, and sensors. Where the goal for each of the previously mentioned objectives is to find a solution/design compatible with humans. A possible way to understand the human motor behaviours is to generate them on human-like robots. Biologically inspired action generation is promising in control of wearable robots as they provide more natural movements. Furthermore, wearable robotics shows exciting progress, also with its design. Soft exosuits use soft materials to build both sensors and actuators. This work investigates an adaptive representation model for actions in robotics. The concrete action model is composed of four modularities: pattern selection, spatial coordination, temporal coordination, and sensory-motor adaptation. Modularity in motor control might provide us with more insights about action learning and generalisation not only for humanoid robots but also for their biological counterparts. Successfully, we tested the model on a humanoid robot by learning to perform a variety of tasks (push recovery, walking, drawing, grasping, etc.). In the next part, we suggest several soft actuation mechanisms that overcome the problem of holding heavy loads and also the issue of on-line programming of the robot motion. The soft actuators use textile materials hosting thermoplastic polyurethane formed as inflatable tubes. Tubes were folded inside housing channels with one strain-limited side to create a flexor actuator. We proposed a new design to control the strained side of the actuator by adding four textile cords along its longitudinal axis. As a result, the actuator behaviour can be on-line programmed to bend and twist in several directions. In the last part of this thesis, we organised piezoresistive elements in a superimposition structure. The sensory structure is used on a sensory gripper to sense and distinguish between pressure and curvature stimuli. Next, we elaborated the sensing gripper by adding proximity sensing through conductive textile parts added to the gripper and work as capacitive sensors. We finally developed a versatile soft strain sensor that uses silicone tubes with an embedded solution that has an electrical resistance proportional to the strain applied on the tubes. Therefore, an entirely soft sensing glove exhibits hand gestures recognition. The proposed combinations of soft actuators, soft sensors, and biologically inspired action representation might open a new perspective to obtain smart wearable robots.
Obwohl bei vielen Aufgaben in der Robotik vor allem Genauigkeit, Präzision, Flexibilität, Anpassungsfähigkeit usw. gefragt sind, gibt es in der Wearable-Robotik auch einige andere Aspekte, die einen zuverlässigen und vielversprechenden Ansatz kennzeichnen. Die drei Schlüsselelemente, sind die folgenden: Steuerung, Aktuatoren und Sensoren. Dabei ist das Ziel für jedes der genannten Elemente, eine menschengerechte Lösung und ein menschengerechtes Design zu finden. Eine Möglichkeit, die menschliche Motorik zu verstehen, besteht darin, sie auf menschenähnlichen Robotern zu erzeugen. Biologisch inspirierte Bewegungsabläufe sind vielversprechend bei der Steuerung von tragbaren Robotern, da sie natürlichere Bewegungen ermöglichen. Darüber hinaus zeigt die tragbare Robotik spannende Fortschritte bei ihrem Design. Zum Beispiel verwenden softe Exoskelette weiche Materialien, um sowohl Sensoren als auch Aktuatoren zu erschaffen. Diese Arbeit erforscht ein adaptives Repräsentationsmodell für Bewegungen in der Robotik. Das konkrete Bewegungsmodell besteht aus vier Modularitäten: Musterauswahl, räumliche Koordination, zeitliche Koordination und sensorisch-motorische Anpassung. Diese Modularität in der Motorsteuerung könnte uns mehr Erkenntnisse über das Erlernen und Verallgemeinern von Handlungen nicht nur für humanoide Roboter, sondern auch für ihre biologischen Gegenstücke liefern. Erfolgreich testeten wir das Modell an einem humanoiden Roboter, indem dieser gelernt hat eine Vielzahl von Aufgaben auszuführen (Stoß-Ausgleichsbewegungen, Gehen, Zeichnen, Greifen, etc.). Im Folgenden schlagen wir mehrere weiche Aktuatoren vor, welche das Problem des Haltens schwerer Lasten und auch die Frage der Online- Programmierung der Roboterbewegung lösen. Diese weichen Aktuatoren verwenden textile Materialien mit thermoplastischem Polyurethan, die als aufblasbare Schläuche geformt sind. Die Schläuche wurden in Gehäusekanäle mit einer dehnungsbegrenzten Seite gefaltet, um Flexoren zu schaffen. Wir haben ein neues Design vorgeschlagen, um die angespannte Seite eines Flexors zu kontrollieren, indem wir vier textile Schnüre entlang seiner Längsachse hinzufügen. Dadurch kann das Verhalten des Flexors online programmiert werden, um ihn in mehrere Richtungen zu biegen und zu verdrehen. Im letzten Teil dieser Arbeit haben wir piezoresistive Elemente in einer Überlagerungsstruktur organisiert. Die sensorische Struktur wird auf einem sensorischen Greifer verwendet, um Druck- und Krümmungsreize zu erfassen und zu unterscheiden. Den sensorischen Greifer haben wir weiterentwickelt indem wir kapazitiv arbeitende Näherungssensoren mittels leitfähiger Textilteile hinzufügten. Schließlich entwickelten wir einen vielseitigen weichen Dehnungssensor, der Silikonschläuche mit einer eingebetteten resistiven Lösung verwendet, deren Wiederstand sich proportional zur Belastung der Schläuche verhält. Dies ermöglicht einem völlig weichen Handschuh die Erkennung von Handgesten. Die vorgeschlagenen Kombinationen aus weichen Aktuatoren, weichen Sensoren und biologisch inspirierter Bewegungsrepräsentation kann eine neue Perspektive eröffnen, um intelligente tragbare Roboter zu erschaffen.

碩士
義守大學
電機工程學系
100
cerebral vascular accident is third largest cause of the human toll. It also most of reason to bring adults disability in the world. In America, each year about 75 million stroke patient increase in. And there are rising trend year by year, each year, about 500 million people have Non-fatal stroke of which about one-third people disability The chance of stroke recurrence is very high of which one-fifth of patients have the opportunity to recurrence within five years. It has become one of people the top ten leading cause of death, due to the impact of lifestyle and eating habits, the rapid increase in stroke patients. The event, patients with serious cases will die, the mild will cause physical handicaps can not walk by themselves, they must count on others to take care of. They just can complete their daily life. Although market already has health equipment, but most are large and weight doesn’t light, and also expensive, so this research purpose for design a light volume and can simple and easy of wearing type rehabilitation robotics can let patients wear rehabilitation robotics from hospital or home by themselves, through institutions of improved design, can make patients wearing more easily, and it won’t cause arm heavy and complex and difficult to started or using places has limit. This study focuses on improved design on the machine body, and by LEGO robots to do the experiment to show the overall mode of operation and set the movable limit switch point in the rehabilitation robotics，and according to each patient's situation to make adjustments, It’s excellent versatile.

abstract: Wearable robotics is a growing sector in the robotics industry, they can increase the productivity of workers and soldiers and can restore some of the lost function to people with disabilities. Wearable robots should be comfortable, easy to use, and intuitive. Robust control methods are needed for wearable robots that assist periodic motion. This dissertation studies a phase based oscillator constructed with a second order dynamic system and a forcing function based on the phase angle of the system. This produces a bounded control signal that can alter the damping and stiffens properties of the dynamic system. It is shown analytically and experimentally that it is stable and robust. It can handle perturbations remarkably well. The forcing function uses the states of the system to produces stable oscillations. Also, this work shows the use of the phase based oscillator in wearable robots to assist periodic human motion focusing on assisting the hip motion. One of the main problems to assist periodic motion properly is to determine the frequency of the signal. The phase oscillator eliminates this problem because the signal always has the correct frequency. The input requires the position and velocity of the system. Additionally, the simplicity of the controller allows for simple implementation.
Dissertation/Thesis
Doctoral Dissertation Mechanical Engineering 2016

abstract: The world population is aging. Age-related disorders such as stroke and spinal cord injury are increasing rapidly, and such patients often suffer from mobility impairment. Wearable robotic exoskeletons are developed that serve as rehabilitation devices for these patients. In this thesis, a knee exoskeleton design with higher torque output compared to the first version, is designed and fabricated. A series elastic actuator is one of the many actuation mechanisms employed in exoskeletons. In this mechanism a torsion spring is used between the actuator and human joint. It serves as torque sensor and energy buffer, making it compact and safe. A version of knee exoskeleton was developed using the SEA mechanism. It uses worm gear and spur gear combination to amplify the assistive torque generated from the DC motor. It weighs 1.57 kg and provides a maximum assistive torque of 11.26 N·m. It can be used as a rehabilitation device for patients affected with knee joint impairment. A new version of exoskeleton design is proposed as an improvement over the first version. It consists of components such as brushless DC motor and planetary gear that are selected to meet the design requirements and biomechanical considerations. All the other components such as bevel gear and torsion spring are selected to be compatible with the exoskeleton. The frame of the exoskeleton is modeled in SolidWorks to be modular and easy to assemble. It is fabricated using sheet metal aluminum. It is designed to provide a maximum assistive torque of 23 N·m, two times over the present exoskeleton. A simple brace is 3D printed, making it easy to wear and use. It weighs 2.4 kg. The exoskeleton is equipped with encoders that are used to measure spring deflection and motor angle. They act as sensors for precise control of the exoskeleton. An impedance-based control is implemented using NI MyRIO, a FPGA based controller. The motor is controlled using a motor driver and powered using an external battery source. The bench tests and walking tests are presented. The new version of exoskeleton is compared with first version and state of the art devices.
Dissertation/Thesis
Masters Thesis Mechanical Engineering 2018

Data from the latest World Health Organization estimates paint a picture where one-seventh of the world population needs at least one assistive device. At the same time, clinical facilities are more and more overcrowded. On one side, due to the aging of the population, on the other side, thanks to the advances in medicine for which pathologies once certainly deadly, nowadays present a low mortality rate. However, only a small percentage of those who need an assistive or rehabilitative aid can get it properly because the healthcare system is globally under heavy pressure. The early 2000s are also characterized by a marked technological drive which, starting in the middle of the twentieth century, took the name of the Fourth Industrial Revolution. Increasingly smaller processors deliver ever higher computing power, production processes are optimized, data transmission reaches impressive speeds, and technology becomes more and more accessible. In this terrain, robotics is making its way through more and more aspects of everyday life, and robotics-based assistance or rehabilitation to physically impaired people are considered two of the most promising applications of this widely investigated technology. Providing high-intensity rehabilitative sessions or home assistance through low-cost robotic devices can be an active solution to democratize some services otherwise not accessible. Simultaneously, it will also contribute to lower the burden over the healthcare system. The work presented in this thesis has aimed to tackle the topic mentioned above by developing an innovative control strategy to be implemented on a low-cost hand exoskeleton system to support people suffering from hand disabilities during the activities of daily living. Most of the independence in everyday life is due in fact to the activities carried out using the hands; this is why restoring their dexterity when pathologically lost, is vitally important. This work has been conducted starting from the solutions available within state of the art and following the main trends, heading to the development of an intuitive and easy to manage control strategy based on the intention recognition from surface electromyographic signals. Exploiting epidermal measurements of the myoelectric activity lends itself well to research activities as it is a noninvasive procedure and therefore is widely studied in the literature, including in the eld of control of robotic devices. The application of these techniques to the real control of robotic devices is rarely addressed, however, and only a few cases are reported in the literature. The main contribution of this activity is hence not only to propose a novel control strategy but also to provide a detailed explanation of its implementation into a real device. The performance of the resulting systems has been tested enrolling a patient suffering from spinal muscular atrophy in a pilot study.

Assisting human locomotion with a wearable robotic orthosis is still quite challenging, largely due to the complexity of the neuromusculoskeletal system, the time-varying dynamics that accompany motor adaptation, and the uniqueness of every individual’s response to the assistance given by the robot. To this day, these devices have not met their well-known promise yet, mostly due to the fact that they are not perfectly suitable for the rehabilitation of neuropathologic patients. One of the main challenges hampering this goal still relies on the interface and co-dependency between the human and the machine. Nowadays, most commercial exoskeletons replay pre-defined gait patterns, whereas research exoskeletons are switching to controllers based on optimized torque profiles. In most cases, the dynamics of the human musculoskeletal system are still ignored and do not take into account the optimal conditions for inducing a positive modulation of neuromuscular activity. This is because both rehabilitation strategies are still emphasized on the macro level of the whole joint instead of focusing on the muscles’ dynamics and activity, which are the actual anatomical elements that may need to be rehabilitated. Strategies to keep the human in the loop of the exoskeleton’s control laws in real-time may help to overcome these challenges. The main purpose of the present dissertation is to make a paradigm shift in the approach on how the assistance that is given to a subject by an exoskeleton is modelled and controlled during physical rehabilitation. Therefore, in the scope of the present work, it was intended to design, concede, implement, and validate a real-time muscle-in-the-loop optimization model to find the best assistive support ratio that would induce optimal rehabilitation conditions to a specific group of impaired muscles while having a minimum impact on the other healthy muscles. The developed optimization model was implemented in the form of a plugin and was integrated on a neuromechanical model-based interface for driving a bilateral ankle exoskeleton. Experimental pilot tests evaluated the feasibility and effectiveness of the model. Results of the most significant pilots achieved EMG reductions up to 61 ± 3 % in Soleus and 41 ± 10 % in Gastrocnemius Lateralis. Moreover, results also demonstrated the efficiency of the optimization’s specific reduction on rehabilitation by looking into the muscular fatigue after each experiment. Finally, two parallel preliminary studies emerged from the pilots, which looked at muscle adaptation, after a new assistive condition had been applied, over time and at the effect of the lateral positioning of the exoskeleton’s actuators on the leg muscles.
Auxiliar a locomoção humana com uma ortose robótica ainda é bastante desafiante, em grande parte devido à complexidade do sistema neuromusculoesquelético, à dinâmica variável no tempo que acompanha a adaptação motora e à singularidade da resposta de cada indivíduo à assistência dada pelo robô. Até hoje, está por cumprir a promessa inicial destes dispositivos, principalmente devido ao facto de não serem perfeitamente adequados para a reabilitação de pacientes neuropatológicos. Um dos principais desafios que dificultam esse objetivo foca-se ainda na interface e na co-dependência entre o ser humano e a máquina. Hoje em dia, a maioria dos exoesqueletos comerciais reproduz padrões de marcha predefinidos, enquanto que os exoesqueletos em investigação estão só agora a mudar para controladores com base em perfis de binário otimizados. Na maioria dos casos, a dinâmica do sistema musculoesquelético humano ainda é ignorada e não tem em consideração as condições ideais para induzir uma modulação positiva da atividade neuromuscular. Isso ocorre porque ambas as estratégias de reabilitação ainda são enfatizadas no nível macro de toda a articulação, em vez de se concentrar na dinâmica e atividade dos músculos, que são os elementos anatómicos que realmente precisam de ser reabilitados. Estratégias para manter o ser humano em loop nos comandos que controlam o exoesqueleto em tempo real podem ajudar a superar estes desafios. O principal objetivo desta dissertação é fazer uma mudança de paradigma na abordagem em como a assistência que é dada a um sujeito por um exosqueleto é modelada e controlada durante a reabilitação física. Portanto, no contexto do presente trabalho, pretendeu-se projetar, conceder, implementar e validar um modelo de otimização muscle-in-the-loop em tempo real para encontrar a melhor relação de suporte capaz de induzir as condições ideais de reabilitação para um grupo específico de músculos fragilizados, tendo um impacto mínimo nos outros músculos saudáveis. O modelo de otimização desenvolvido foi implementado na forma de um plugin e foi integrado numa interface baseada num modelo neuromecânico para o controlo de um exoesqueleto bilateral de tornozelo. Testes experimentais piloto avaliaram a viabilidade e a eficácia do modelo. Os resultados dos testes mais significativos demonstraram reduções de EMG de até 61 ± 3 % no Soleus e 41 ± 10 % no Gastrocnemius Lateral. Adicionalmente, os resultados demonstraram também a eficiência em reabilitação da redução específica no EMG devido à otimização tendo em conta a fadiga muscular após cada teste. Finalmente, dois estudos preliminares paralelos emergiram dos testes piloto, que analisaram a adaptação muscular após uma nova condição assistiva ter sido definida ao longo do tempo e o efeito do posicionamento lateral dos atuadores do exoesqueleto nos músculos da perna.
Mestrado em Engenharia Biomédica

abstract: As the world population continues to age, the demand for treatment and rehabilitation of long-term age-related ailments will rise. Healthcare technology must keep up with this demand, and existing solutions must become more readily available to the populace. Conditions such as impairment due to stroke currently take months or years of physical therapy to overcome, but rehabilitative exoskeletons can be used to greatly extend a physical therapist’s capabilities. In this thesis, a rehabilitative knee exoskeleton was designed which is significantly lighter, more portable and less costly to manufacture than existing designs. It accomplishes this performance by making use of high-powered and weight-optimized brushless DC (BLDC) electric motors designed for drones, open-source hardware and software solutions for robotic motion control, and rapid prototyping technologies such as 3D printing and laser cutting. The exoskeleton is made from a series of laser cut aluminum plates spaced apart with off-the-shelf standoffs. A drone motor with a torque of 1.32 Nm powers an 18.5:1 reduction two-stage belt drive, giving a maximum torque of 24.4 Nm at the output. The bearings for the belt drive are installed into 3D printed bearing mounts, which act as a snug intermediary between the bearing and the aluminum plate. The system is powered off a 24 volt, 1,500 MAh lithium battery, which can provide power for around an hour of walking activity. The exoskeleton is controlled with an ODrive motor controller connected to a Raspberry Pi. Hip angle data is provided by an IMU, and the knee angle is provided by an encoder on the output shaft. A compact Rotary Series Elastic Actuator (cRSEA) device is mounted on the output shaft as well, to accurately measure the output torque going to the wearer. A Proportional-Derivative (PD) controller with feedforward relates the input current with the output torque. The device was tested on a treadmill and found to have an average backdrive torque of 0.39 Nm, significantly lower than the current state of the art. A gravity compensation controller and impedance controller were implemented to assist during swing and stance phases respectively. The results were compared to the muscular exertion of the knee measured via Electromyography (EMG).
Dissertation/Thesis
Masters Thesis Engineering 2020

abstract: Human walking has been a highly studied topic in research communities because of its extreme importance to human functionality and mobility. A complex system of interconnected gait mechanisms in humans is responsible for generating robust and consistent walking motion over unpredictable ground and through challenging obstacles. One interesting aspect of human gait is the ability to adjust in order to accommodate varying surface grades. Typical approaches to investigating this gait function focus on incline and decline surface angles, but most experiments fail to address the effects of surface grades that cause ankle inversion and eversion. There have been several studies of ankle angle perturbation over wider ranges of grade orientations in static conditions; however, these studies do not account for effects during the gait cycle. Furthermore, contemporary studies on this topic neglect critical sources of unnatural stimulus in the design of investigative technology. It is hypothesized that the investigation of ankle angle perturbations in the frontal plane, particularly in the context of inter-leg coordination mechanisms, results in a more complete characterization of the effects of surface grade on human gait mechanisms. This greater understanding could potentially lead to significant applications in gait rehabilitation, especially for individuals who suffer from impairment as a result of stroke. A wearable pneumatic device was designed to impose inversion and eversion perturbations on the ankle through simulated surface grade changes. This prototype device was fabricated, characterized, and tested in order to assess its effectiveness. After testing and characterizing this device, it was used in a series of experiments on human subjects while data was gathered on muscular activation and gait kinematics. The results of the characterization show success in imposing inversion and eversion angle perturbations of approximately 9° with a response time of 0.5 s. Preliminary experiments focusing on inter-leg coordination with healthy human subjects show that one-sided inversion and eversion perturbations have virtually no effect on gait kinematics. However, changes in muscular activation from one-sided perturbations show statistical significance in key lower limb muscles. Thus, the prototype device demonstrates novelty in the context of human gait research for potential applications in rehabilitation.
Dissertation/Thesis
Masters Thesis Mechanical Engineering 2016

Robotics is increasingly involving many aspects of daily life and robotic-based assistance to physically impaired people is considered one of the most promising application of this largely investigated technology. However, as of today, hand exoskeletons design can still be considered a hurdle task and, even in modern robotics, providing assistance to those patients who have lost or injured their hand skills, assuring them an independent and healthy life through the design of exoskeleton technologies is, surely, one of the most challenging goal. In this framework, the research activity carried out during the PhD period concentrated on the development of wearable devices, with special focus given to hand exoskeletons which support patients suffering from hand disabilities during the Activities of Daily Living (ADLs). The studied devices have been designed to be also used during rehabilitative sessions in specific tasks trying to restore the dexterity of the user's hands. Starting from current solutions identified within the state of the art, the work was conducted heading to the development of portable, wearable and highly customizable devices. The last aspect will be fully endorsed by the definition of patient-centered design strategies leading to tailor-made devices specifically developed on the users' needs. Two hand exoskeletons solutions will be presented throughout the thesis. The first consists of a compact and lightweight solution which exploits a novel 1-DOF kinematic chain of the finger mechanism to accurately reproduce the physiological finger trajectory. The applicability of topology optimization to the wearable technologies field has then been deeply investigated in the design of the second exoskeleton, which has yielded a high-performance aluminum-alloy solution. The performance of the resulting systems was evaluated by means of simulations and tested during experimental validation campaigns by producing several prototypes which allowed to assess their effectiveness in a real-use scenario; the obtained results were satisfying, indicating that the derived solutions may constitute a valid alternative to existing hand exoskeletons so far studied in the rehabilitation and assistance fields.

abstract: According to the Center for Disease Control and Prevention report around 29,668 United States residents aged greater than 65 years had died as a result of a fall in 2016. Other injuries like wrist fractures, hip fractures, and head injuries occur as a result of a fall. Certain groups of people are more prone to experience falls than others, one of which being individuals with stroke. The two most common issues with individuals with strokes are ankle weakness and foot drop, both of which contribute to falls. To mitigate this issue, the most popular clinical remedy given to these users is thermoplastic Ankle Foot Orthosis. These AFO's help improving gait velocity, stride length, and cadence. However, studies have shown that a continuous restraint on the ankle harms the compensatory stepping response and forward propulsion. It has been shown in previous studies that compensatory stepping and forward propulsion are crucial for the user's ability to recover from postural perturbations. Hence, there is a need for active devices that can supply a plantarflexion during the push-off and dorsiflexion during the swing phase of gait. Although advancements in the orthotic research have shown major improvements in supporting the ankle joint for rehabilitation, there is a lack of available active devices that can help impaired users in daily activities. In this study, our primary focus is to build an unobtrusive, cost-effective, and easy to wear active device for gait rehabilitation and fall prevention in individuals who are at risk. The device will be using a double-acting cylinder that can be easily incorporated into the user's footwear using a novel custom-designed powered ankle brace. The device will use Inertial Measurement Units to measure kinematic parameters of the lower body and a custom control algorithm to actuate the device based on the measurements. The study can be used to advance the field of gait assistance, rehabilitation, and potentially fall prevention of individuals with lower-limb impairments through the use of Active Ankle Foot Orthosis.
Dissertation/Thesis
Masters Thesis Electrical Engineering 2020

Wearable robots are person-oriented robots worn by human operators and aimed at assisting users' movements. They provide human limbs with physical support and functional supplement by enhancing the strength of wearer's joint in order to give people with mobility impairments the chance to regain the ability to walk over the ground, upstairs and downstairs, or to augment the performance of able-bodied wearers. Research in the field of wearable robots started in late 1960s in USA and Yugoslavia for military and medical purposes respectively and even though a lot of progresses have been done especially in the last two decades, a lot of challenges are still associated with them and several research contributions aim to overcome current limitations. Portability is one of the main requirement of wearable robots. It is conceived as the capability to be worn and carried around by users who need to be supported in a large variety of operational scenarios and for an extended length of time. Comfortable and ergonomic mechanical structures, as well as efficient and convenient actuation systems ensure portability of these robotic devices. Current actuation technologies challenge the development of portable and effective wearable robots. Actuation of these devices must fulfil often opposing requirements which are hard to conciliate at the same time. They must be powerful enough for providing the high peak of torque and power demanded in a gait cycle of locomotion tasks, they should have a low energy consumption in order to increase the operating range of the device and finally they must be as small and lightweight as possible in order to decrease the metabolic expenditure and facilitate portability. Efficient actuatosr capable of exploiting the passive dynamic of human walking by storing and releasing energy according to the phases of the gait cycle, can reduce the energy requirement of the motor leading to the development of long lasting and lightweight systems. More than the joint power augmentation, also the balance challenges the development of portable wearable robots. Most of wearable robots have been not primarily designed to assist balance and users have to count on conventional assistive technologies, such as canes or crutches, to prevent the risk of falling. However, these external assistive devices are hold in the hands and this is not convenient for people with limited strength in upper limbs. Furthermore, they can interfere with balance in some situations and they reduce the effectiveness of wearable robots in comparison to wheel chairs. Multi degree of freedom actuated joints would improve gait stability, despite the increase of the weight and of the control complexity. Robotic assistive technologies, such as moment exchange actuators, have the potential of providing balance assistance to the wearer in his daily life actions and consistently with human balance control. They detect the subject�s loss of balance and exert corrective actions to avoid or delay the risk of falling. Balance assistive devices can either be included in powered wearable robots or be worn separately by subjects suffering balance disorders to control and improve their balance. This thesis gives a contribution to the development of portable wearable robots in terms of energetic efficiency and safety. The current actuation technologies for joint power augmentation and balance assistance have been investigated with the aim of finding novel solutions that could improve the portability of wearable robots for human locomotion assistance and human strength augmentation. The investigation resulted in the development of two concepts of actuated devices focused on enhancing joint strength and on balance compensation respectively.

abstract: Current exosuit technologies utilizing soft inflatable actuators for gait assistance have drawbacks of having slow dynamics and limited portability. The first part of this thesis focuses on addressing the aforementioned issues by using inflatable actuator composites (IAC) and a portable pneumatic source. Design, fabrication and finite element modeling of the IAC are presented. Volume optimization of the IAC is done by varying its internal volume using finite element methods. A portable air source for use in pneumatically actuated wearable devices is also presented. Evaluation of the system is carried out by analyzing its maximum pressure and flow output. Electro-pneumatic setup, design and fabrication of the developed air source are also shown. To provide assistance to the user using the exosuit in appropriate gait phases, a gait detection system is needed. In the second part of this thesis, a gait sensing system utilizing soft fabric based inflatable sensors embedded in a silicone based shoe insole is developed. Design, fabrication and mechanical characterization of the soft gait detection sensors are given. In addition, integration of the sensors, each capable of measuring loads of 700N in a silicone based shoe insole is also shown along with its possible application in detection of various gait phases. Finally, a possible integration of the actuators, air source and gait detection shoes in making of a portable soft exosuit for knee assistance is given.
Dissertation/Thesis
Masters Thesis Mechanical Engineering 2020

Soft materials have gained increasing prominence in science and technology over the last few decades. This shift from traditional rigid materials to soft, compliant materials have led to the emergence of a new class of devices which can interact with humans safely, as well as reduce the disparity in mechanical compliance at the interface of soft human tissue and rigid devices.

One of the largest application of soft materials has been in the field of flexible electronics, especially in wearable sensors. While wearable sensors for physical attributes such as strain, temperature, etc. have been popular, they lack applications and significance from a healthcare perspective. Point-of-care (POC) devices, on the other hand, provide exceptional healthcare value, bringing useful diagnostic tests to the bedside of the patient. POC devices, however, have been developed for only a limited number of health attributes. In this dissertation I propose and demonstrate wireless, wearable POC devices to measure and communicate the level of various analytes in and the properties of multiple biofluids: blood, urine, wound exudate, and sweat.

Along with sensors, another prominent area of soft materials application has been in actuators and robots which mimic biological systems not only in their action but also in their soft structure and actuation mechanisms. In this dissertation I develop design strategies to improve upon current soft robots by programming the storage of elastic strain energy. This strategy enables us to fabricate soft actuators capable of programmable and low energy consuming, yet high speed motion. Collectively, this dissertation demonstrates the use of soft compliant materials as the foundation for developing new sensors and actuators for human use and interaction.

The research here presented is focused on the phenomenological analysis of the bodily self-perception and social self-presentation in Human-Technology Interplay, while this interplay is aimed at human habits change or recovery. The three main ingredients are thus Phenomenology, HTI and Habits. The core issue is represented by this interaction with technology (HTI) and the related implications of phenomenological analysis for our understanding of this field, and potentially for improving specific design decisions or therapy. One of the primary purposes is aimed at showing how philosophy, and in particular phenomenology, can actually help to bridge the gap between AI technology (robotics, gaming) and bodily self-perception and social self-presentation. Concepts like Leib, Korper, Body-image, Social self presentation, Bodily-self perception and acceptance are major keywords that can profit from being analyzed in the context of HTI from a phenomenological perspective. Moreover, the way in which technology or robotics can affect or change human habits (both in terms of their acquisition and restoration), is another central theme.