Dissertations / Theses on the topic 'Rehabilitation Glove'

This thesis examines how the pressure sensors can be used in rehabilitation for patients with weakened hand strength. The rehabilitation process usually contains everyday tasks to evaluate the patient’s capability and the tools for this part of the rehabilitation process are few. The challenges will be to find a suitable sensor for the application and how to implement the sensor in a versatile prototype with direct feedback for the user. To solve this problem, research will be conducted on different pressure sensor types to determine the most suitable one for this implementation. The resulting prototype is utilizing a force sensing resistor (FSR) mounted on a glove together with a module that presents direct feedback to the patient and caretaker. The glove has pressure sensors in each fingertip to detect the applied force for each individual finger when the patient grips an object. To present the feedback, a visual interface is created in the form of a hand with a LED for each finger, which provides direct visual feedback and a display to present numerical data.
Denna avhandling undersöker hur trycksensorer kan användas vid rehabilitering av patienter med försvagad handstyrka. Rehabiliteringsprocessen innehåller vanligtvis vardagliga uppgifter för att utvärdera patientens förmåga och nuvarande hjälpmedel är få. Utmaningarna är att hitta en lämplig sensor för applikationen och hur man kan implementera sensorn i en mångsidig prototyp med en direkt återkoppling för användaren. För att lösa detta problem kommer forskning att genomföras på olika typer av trycksensorer. Detta görs för att kunna bestämma den mest lämpade sensortypen för denna implementering. Den resulterande prototypen består av en handske med kraft känsliga resistorer (FSR) och en separat modul som ger direkt återkoppling till patienten och vårdtagaren. Handsken har en sensor i varje fingertopp för att detektera applicerad kraft för varje enskilt finger när patienten greppar ett föremål. För att presentera data från sensorerna skapas ett visuellt gränssnitt. Gränssnittet är i form av en hand med lysdioder i varje finger för direkt återkoppling och en bildskärm för att presentera numeriska data.

This thesis presents both a control scheme for naturalistic control of an exoskeleton glove and a glove design. Exoskeleton development has been focused primarily on design, improving soft actuator and cable-driven systems, with only limited focus on intelligent control. There is a need for control that is not limited to position or force reference signals and is user-driven. By implementing a motion amplification controller to increase weak movements of an impaired individual, a finger joint trajectory can be observed and used to predict their grasping intention. The motion amplification functions off of a virtual dynamical system that safely enforces the range of motion of the finger joints and ensures stability. Three grasp prediction algorithms are developed with improved levels of accuracy: regression, trajectory, and deep learning based. These algorithms were tested on published finger joint trajectories. The fusion of the amplification and prediction could be used to achieve naturalistic, user-guided control of an exoskeleton glove. The key to accomplishing this is series elastic actuators to move the finger joints, thereby allowing the wearer to deflect against the glove and inform the controller of their intention. These actuators are used to move the fingers in a nine degree of freedom exoskeleton that is capable of achieving all the grasps used most frequently in daily life. The controllers and exoskeleton presented here are the basis for improved exoskeleton glove control that can be used to assist or rehabilitate impaired individuals.
Master of Science
Millions of Americans report difficulty holding small or even lightweight objects. In many of these cases, their difficulty stems from a condition such as a stroke or arthritis, requiring either rehabilitation or assistance. For both treatments, exoskeleton gloves are a potential solution; however, widespread deployment of exoskeletons in the treatment of hand conditions requires significant advancement. Towards that end, the research community has devoted itself to improving the design of exoskeletons. Systems that use soft actuation or are driven by artificial tendons have merit in that they are comfortable to the wearer, but lack the rigidity required for monitoring the state of the hand and controlling it. Electromyography sensors are also a commonly explored technology for determining motion intention; however, only primitive conclusions can be drawn when using these sensors on the muscles that control the human hand. This thesis proposes a system that does not rely on soft actuation but rather a deflectable exoskeleton that can be used in rehabilitation or assistance. By using series elastic actuators to move the exoskeleton, the wearer of the glove can exert their influence over the machine. Additionally, more intelligent control is needed in the exoskeleton. The approach taken here is twofold. First, a motion amplification controller increases the finger movements of the wearer. Second, the amplified motion is processed using machine learning algorithms to predict what type of grasp the user is attempting. The controller would then be able to fuse the two, the amplification and prediction, to control the glove naturalistically.

In the western world there is an issue in healthcare being created by an increasing number of people who experience disability. Whilst the reasons for these occurring are multiple, the common treatment to aid recovery from this condition is therapy that requires manual stimulation of the musculature form [sic] a therapist. Due to the physical demands that this process places on the therapist it is thought that a possible solution to meeting the increasing future demand for therapy is with developments in robotic technology. This thesis proposes and develops the design of a cable-driven glove to assist patients to grasp, this direction of design was chosen after a consultation with former patients found that this was the activity of upper limb motion that they felt was the most difficult to control after therapy. Their design requirements resulted in the creation of a lightweight glove that maximised the performance of the cable driven system through the use of a vacuum to secure the cable and use the joints of their body to control the flexion. This design resulted in the development of a first generation prototype that was assessed firstly by operating a 3D printed hand to grasp a collection of balls and cubes. After this the prototype was tested by unimpaired volunteers to provide feedback on the comfort and control they have when using the device, which was then compared to the findings from the initial consultation. This showed that the glove was successful in performing the intended motion and was considered comfortable (3.5/5) as well as providing them control (3.83/5). The device was used in a consultation with medical workers as well, who were impressed with the strength of the device, but highlighted improvements that could be made to refine it further.

The repetitive and sometimes mundane nature of conventional rehabilitation therapy provides an ideal opportunity for development of interactive and challenging therapeutic games that have the potential to engage and motivate the players. Different game design techniques can be used to design rehabilitation games that work alongside robotics to provide an augmentative therapy to stroke patients in order to increase their compliance and motivation towards therapy. The strategy we followed to develop such a system was to (i) identify the key design parameters that can influence compliance, prolonged activity, active participation and patient motivation, (ii) use these parameters to design rehabilitation games for robot-mediated stroke-rehabilitation, (iii) investigate the effects of these parameters on motivation and performance of patients undergoing home-based rehabilitation therapy. Three main studies were conducted with healthy subjects and stroke subjects. The first study identified the effects of the design parameters on healthy players' motivation. Using the results from this study, we incorporated the parameters into rehabilitation games, following player-centric iterative design process, which were formatively evaluated during the second study with healthy subjects, stroke patients, and health-care professionals. The final study investigated the research outcomes from use of these games in three patient's homes during a 6 weeks clinical evaluation. In summary, the research undertaken during this PhD successfully identified the design techniques influencing patient motivation and adherence as well as highlighted further important elements that contribute to maintaining therapeutic interaction between patients and the therapy medium, mainly the technological usability and reliability of the system.

This thesis explores the field of hand exoskeleton robotic systems with slip detection and its applications. It presents the design and control of the intelligent sensing and force- feedback exoskeleton robotic (iSAFER) glove to create a system capable of intelligent object grasping initiated by detection of the user’s intentions through motion amplification. Using a combination of sensory feedback streams from the glove, the system has the ability to identify and prevent object slippage, as well as adapting grip geometry to the object properties. The slip detection algorithm provides updated inputs to the force controller to prevent an object from being dropped, while only requiring minimal input from a user who may have varying degrees of functionality in their injured hand. This thesis proposes the use of a high dynamic range, low cost conductive elastomer sensor coupled with a negative force derivative trigger that can be leveraged in order to create a controller that can intelligently respond to slip conditions through state machine architecture, and improve the grasping robustness of the exoskeleton. The mechanical and electrical improvements to the previous design, the sensing and force- feedback exoskeleton robotic (SAFER) glove, are described while details of the controller design and the proposed assistive and rehabilitative applications are explained. Experimental results confirming the validity of the proposed system are also presented. In closing, this thesis concludes with topics for future exploration.
Master of Science
Exoskeletons are robotic systems that have rigid external covering, such as links, joints, and/or soft artificial tendons or muscles, for the desired body part to provide support and/or protection. These are typically used to enhance power and strength, provide rehabilitation and assistance, and teleoperate other robots from a distance. While the US Army developed exoskeletons for strengthening purposes, another potential purpose of exoskeletons, which is serving medical needs, such as rehabilitation, attracted a lot of attention. Among numerous illnesses and injuries that may lead to impaired hand functionality, the U.S. Department of Health and Human Services estimated that approximately 470,000 people survive strokes every year in the United States and require continuous rehabilitation to recover their motor functions. Though medical professionals believe that the intensity and duration of rehabilitation is the key for maximizing the rate of recovery, it is often limited due to many reasons, such as cost or difficulty in attending rehabilitation sessions. To augment the availability and quality of rehabilitation, the study of exoskeletons has earned popularity. Beyond the capability of providing simple movements, such as passive rehabilitation, many scientists researched to provide active rehabilitation, which involves active participation from the patients. Furthermore, detecting the patient’s intention to activate the rehabilitation glove became a topic of interest, and many types of sensors were utilized in research. This thesis explores the design and control of the intelligent sensing and force- feedback exoskeleton robotic (iSAFER) glove, which detects the user’s intentions to activate the system through motion amplification. The iSAFER glove performs soft initial grasp until the fingers touch an object. After the object is gently grabbed and lifted, the grasp is autonomously adjusted through slip detection until there is no more slip. To facilitate this idea, a low cost force sensor was created and leveraged to improve the grasping control of the exoskeleton. The mechanical and electrical improvements to the previous design, the sensing and force-feedback exoskeleton robotic (SAFER) glove, are described while details of the controller design and the proposed assistive and rehabilitative applications are explained. Experimental results confirming the validity of the proposed system are also presented. In closing, this thesis concludes with topics for future exploration.

In this paper, the research focused on the development of a hand rehabilitation device which could perform extension, opposition and reposition movements. Firstly, the anatomy of the hand is analyzed and studied to understand where the problem resides; since the mechanism will be applied to post-stroke patients, it is necessary to comprehend the structure and the articulations of the hand, the muscles involved in the mentioned movements and how a healthy hand works. Then, the causes of the problem are studied, what are the consequences on the hand and how to solve every issue. Brunnström Approach is taken as reference for the rehabilitation therapy steps. After the performance target is defined and which function has the priority, a brief research on the state of the art is made. Six different devices are analyzed, taking into account their strengths and weaknesses, evaluating them and trying to find possible lacks to solve. An evaluation of possible solutions is done, in order to find the optimal solution for the problem. Various types of actuation and structure of the mechanism are considered. Defined which are the best choices between the ones proposed, the next step is to design a first prototype with the purpose of bringing together the solutions selected. The CAD used is PTC Creo Parametric. Once the first prototype was designed, it was partially printed with 3D technique (additive manufacturing) and tested; tests were made on the actuation and on the device to evaluated its efficacy. The results are visible in this paper. Finally, a conclusion is discussed with a short resume of the experiments made and the results obtained. Furthermore, remaining problems and future works are analyzed and debated.

With improvements in actuation technology and sensory systems, it is becoming increasingly feasible to create powered exoskeletal garments that can assist with the movement of human limbs. This class of robotics referred to as human-machine interfaces will one day be used for the rehabilitation of paralysed, damaged or weak upper and lower extremities. The focus of this project was the development of an exoskeletal interface for the rehabilitation of the hands. A novel sensor was designed for use in such a device. The sensor uses simple optical mechanisms centred on a spring to measure force and position simultaneously. In addition, the sensor introduces an elastic element between the actuator and its corresponding hand joint. This will allow series elastic actuation (SEA) to improve control and safely of the system. The Hand Rehabilitation Device requires multiple actuators. To stay within volume and weight constraints, it is therefore imperative to reduce the size, mass and efficiency of each actuator without losing power. A method was devised that allows small efficient actuating subunits to work together and produce a combined collective output. This work summation method was successfully implemented with Shape Memory Alloy (SMA) based actuators. The actuation, sensory, control system and human-machine interface concepts proposed were evaluated together using a single-joint electromechanical harness. This experimental setup was used with volunteer subjects to assess the potentials of a full-hand device to be used for therapy, assessment and function of the hand. The Rehabilitation Glove aims to bring significant new benefits for improving hand function, an important aspect of human independence. Furthermore, the developments in this project may one day be used for other parts of the body helping bring human-machine interface technology into the fields of rehabilitation and therapy.

Doctor of Philosophy (PhD)
With improvements in actuation technology and sensory systems, it is becoming increasingly feasible to create powered exoskeletal garments that can assist with the movement of human limbs. This class of robotics referred to as human-machine interfaces will one day be used for the rehabilitation of paralysed, damaged or weak upper and lower extremities. The focus of this project was the development of an exoskeletal interface for the rehabilitation of the hands. A novel sensor was designed for use in such a device. The sensor uses simple optical mechanisms centred on a spring to measure force and position simultaneously. In addition, the sensor introduces an elastic element between the actuator and its corresponding hand joint. This will allow series elastic actuation (SEA) to improve control and safely of the system. The Hand Rehabilitation Device requires multiple actuators. To stay within volume and weight constraints, it is therefore imperative to reduce the size, mass and efficiency of each actuator without losing power. A method was devised that allows small efficient actuating subunits to work together and produce a combined collective output. This work summation method was successfully implemented with Shape Memory Alloy (SMA) based actuators. The actuation, sensory, control system and human-machine interface concepts proposed were evaluated together using a single-joint electromechanical harness. This experimental setup was used with volunteer subjects to assess the potentials of a full-hand device to be used for therapy, assessment and function of the hand. The Rehabilitation Glove aims to bring significant new benefits for improving hand function, an important aspect of human independence. Furthermore, the developments in this project may one day be used for other parts of the body helping bring human-machine interface technology into the fields of rehabilitation and therapy.

The aim of the study was to evaluate the visual and anatomic/structural outcomes of severe ocular injuries and their predictive factors. The objectives of the study: 1. To evaluate the risk factors for severe ocular injuries. 2. To evaluate the differences between open globe and closed globe ocular injuries 3. To evaluate visual and anatomic/structural outcomes in severe open globe and closed globe injuries. 4. To evaluate visual and structural outcomes in globe ruptures and penetrating injuries. 5. To evaluate the final visual outcomes in intraocular foreign body injuries. The study was carried out in the Laboratory of Ophfthalmology of the Institute of Biomedical Research and the Eye Clinic of Kaunas University of Medicine. The prospective study is based on the initial examination and the six month follow-up data of the patients with severe ocular injuries, treated in the Department of Ophthalmology of Kaunas Medical University Hospital in the period 2001-2005 (approval of the Kaunas Regional Comitee of Ethics No.BE-2-23). The inclusion criteria – the severe eye injury, defined as injury resulting in permanent and significant (measurable and observable on rutine eye examination) structural and/or functional changes of the eye. Severe eye injuries were classified by BETT system and mechanical eye injury clasiffication. According to final visual acuity visual outcomes was defined as: • Poor VA=0-0.02. • Satisfactory VA=0.03-0.4. • Bad VA≥0.5 [55]. Study population The... [to full text]
Darbo tikslas – įvertinti akių struktūrinius ir regos pokyčius sunkių akių traumų atvejais bei nustatyti juos sąlygojančius veiksnius. Pagrindiniai darbo uždaviniai: 1) nustatyti tikėtinus sunkių akių traumų rizikos veiksnius; 2) palyginti uždaro ir atviro tipo sunkias akių traumas; 3) įvertinti blogą regą ir akies anatominę struktūrą sąlygojančius pokyčius sunkių uždaro ir atviro tipo akių traumų atvejais; 4) nustatyti regos rezultatus ir įvertinti akies struktūrinius pokyčius akies plyšimų ir penetruojančių žaizdų atvejais; 5) nustatyti akių sužalojimų, sukeltų intraokuliniais svetimkūniais, regos rezultatus. Įtraukimo į tyrimą kriterijus – sunki akies trauma. Akies trauma yra sunki, kai ji sukelia pastovius ir žymius funkcinius bei anatominius akies pokyčius. Sunkios akies traumos klasifikuotos, remiantis BETT sistema ir mechaninių akies sužalojimų klasifikacija. Atviro tipo akių traumos suskirstytos pagal: 1) rūšį (A. Plyšimas; B. Penetruojanti ��aizda; C. IOSv; D. Perforuojanti žaizda); 2) laipsnį – regėjimo aštrumą (RA)(1˚ 0,5; 2˚ 0,2-0,4; 3˚ 0,03-0,1; 4˚ 1/∞-0,02; E˚ 0); zoną – žaizdos lokalizaciją (I. ragena; II. ragenos limbas ir 5 mm į odeną; III. nuo 5 mm orientyro odenoje į užpakalinį polių). Uždaro tipo traumos suskirstytos pagal: laipsnį (1˚ 0,5; 2˚ 0,2-0,4; 3˚ 0,03-0,1; 4˚ 1/∞-0,02; 5˚ 0). Regos rezultatas vertintas pagal galutinį koreguotą RA: 1) blogas (RA=0-0,02); 2) patenkinamas (RA=0,03-0,4); 3) geras (RA≥0,5). Ištirtas 1261 sunkių akių traumų atvejis (... [toliau žr. visą tekstą]

碩士
南臺科技大學
創新產品設計系
107
The number of strokes is approximately 17 million per year and the post-stroke “learned nonuse phenomenon” of the upper limbs often results in poorer recovery than that of lower limbs, even though functional upper limbs are essential for handling daily activities in patient’s life. With the science and technology advancement, there are many new innovative behavioral activities, such as mirror therapy, robot-assisted therapy and Virtual Reality therapy, which have become quite a relatively new clinical rehabilitation approach in recent years. The objective of this study was to develop the exoskeletal rehabilitation aids for upper extremities of patient with subacute hemiplegic stroke based on physical medicine and rehabilitation and human factors engineering, that the theoretical basis of mirror therapy and robot-assisted therapy was applied in prototyping design of such exoskeleton to take into account of ergonomics, where such design was further assessed through modeling deduction, device verification and user testing as wearables. The test result showed that the fundamental theory proposed in this study as implemented in practice through design was able to satisfy the needs of most users and such design provided sufficient safety and operability. The same trajectory was obtained every time in the tests, confirming the correctness and the actual practicability of the established construction model in the study. The twelve subjects wearing the device in the user testing, all fell within the targeted percentile that they were able to wear the exoskeletal gloves to perform tasks. This study would continue to recruit from the Chi Mei Medical Center for more Clinical Trials of the auxiliary exoskeletal rehabilitation aids, to prove its efficacy in helping recovery of post-stroke patients, as well as patients with subacute hemiplegic stroke in upper extremities, to assist them in achieving daily self-care and life activities.

碩士
國立臺灣大學
電機工程學研究所
96
A data glove finger movements can be transformed into digital signals, and to do with computers, can be used in virtual reality rehabilitation interface. However, because of existing products in terms of convenience and prices have a lot of room for improvement. And this is facilitated by the cheap three-axis sensors to speed up research and development data gloves, use of the accelerator sensor in the direction of gravity to accelerate, in order to determine that state . The R & D devices can be measured each fingers refers to their static state, palm angle, and restrictions under the dynamic conditions that state.

碩士
國立中正大學
電機工程研究所
105
In recent years, data gloves have become one of the popular researching topics, although data glove products are not common now. Data gloves can provide easier control by direct hand actions. Many researchers use it in their research areas which include media, industrial design, and medical area. In the medical area, most of data gloves are used just as control interface of rehabilitation systems. The measuring results are rough approximations. It is rarely applied as a diagnosis supporting device in a rehabilitation process. We want to develop a data glove as a diagnosis device for rehabilitation. The new data glove can detect hand attitude and hand joint bend angles. Doctor and therapist can use the data glove to diagnose hands ability of patients. This is helpful for patients after stroke and hand surgery. In the thesis, we get the hand motion by the attitude detecting data glove. Sixteen motion sensors are set on the back of the glove. The motion sensor includes an accelerometer, a gyroscope, and a magnetometer. Those are MEMS (Micro Electro Mechanical Systems) sensors. Data of the inertial sensor and the magnetic sensor are fused to get the attitude by AHRS algorithm. The attitude detection refers the magnetic field of the earth. The attitudes of 16 sensors are gathered into a socket and the socket is sent to the computer by Wi-Fi. The hand attitude simulation and the joint angles are computed with Vpython on the computer. Finally, the hand attitude is presented on screen with the limitation for impossible hand action. The bend angles of joints can be fetched by the vector computing. The result can be a reference for diagnosis.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, Johannesburg, April 2020
Hand therapy for patients suffering with hand impairment, caused by physical injury or neurological disorders is often inaccessible to patients that live far away from local clinics. Apart from accessibility, developing countries face additional issues such as high patient referral rates and time limitations. Therefore, it is imperative that there are accessible and low-cost means for hand rehabilitation and impairment diagnosis. A low-cost flexible sensor was developed to measure the range of motion of the fingers for the application of rehabilitation in developing countries. Flexible sensors were attached to the proximal interphalangeal (PIP) and metacarpophalangeal (MCP) joints of the fingers and the interphalangeal (IP) joint of the thumb. The gloves were validated through testing each joint at 30, 45 and 60_ degrees. Fluctuations had a maximum variation of +/-5°. The glove measured the range of motion in 50 healthy subjects performing daily activities that were derived from the ICF(Inter- national Classication of Functioning, Disability and Health) guide. The testing was split into dynamic (10 participants) and static (40 participants) phases. There were no criteria for subject participation apart from the fit of the gloves. The gloves proved capable of measuring the range of motion of the finger joints. The IP join of the thumb had the most variation throughout the dynamic tests. The statictests resulted in a ROM of 39.88_-69.42_, 18.92_- 78.1_ and 13.42_-60.15_ for the MCP, PIP and IP joints, respectively. The data collected provided the range of motion required for an individual to perform activities of daily living and thus validating the gloves use as a_finger motion measurement tool. Therefore, the glove can be applied to monitoring patient recovery, hand impairment diagnosis and providing rehabilitation therapy.
PH2020

碩士
國立臺灣科技大學
機械工程系
103
This study aims to develop a fine motor training glove that integrate a virtual re-ality based interactive environment with vibrotactile feedback for more effective post stroke hand rehabilitation. The proposed haptic rehabilitation device is equipped with small DC vibration motors for vibrotactile feedback stimulation and piezoresistive thin-film pressure sensors for motor function evaluation. Two virtual- reality based games, “gopher hitting” and “musical note hitting”, were developed as a haptic inter-face. According to the designed rehabilitation program, patients intuitively push and practice their fingers to improve the finger isolation function. This study has been cooperated with the physical therapists in Taipei MacKay Memorial Hospital for clin-ical trials. The recruited stroke patients were asked to wear our developed vibrotactile glove for a series of clinical tests. This study specifically discusses the effectiveness of adding vibrotactile feedback and the efficiency of repeated hand rehabilitation. The experiments confirm that giving vibration stimulations at the affected side can in-crease the reaction response of stroke patients.

abstract: Stroke accounts for high rates of mortality and disability in the United States. It levies great economic burden on the affected subjects, their family and the society at large. Motor impairments after stroke mainly manifest themselves as hemiplegia or hemiparesis in the upper and lower limbs. Motor recovery is highly variable but can be enhanced through motor rehabilitation with sufficient movement repetition and intensity. Cost effective assistive devices that can augment therapy by increasing movement repetition both at home and in the clinic may facilitate recovery. This thesis aims to develop a Smart Glove that can enhance motor recovery by providing feedback to both the therapist and the patient on the number of hand movements (wrist and finger extensions) performed during therapy. The design implements resistive flex sensors for detecting the extensions and processes the information using the Lightblue bean microcontroller mounted on the wrist. Communication between the processing unit and display module is wireless and executes Bluetooth 4.0 communication protocol. The capacity for the glove to measure and record hand movements was tested on three stroke and one traumatic brain injured patient while performing a box and blocks test. During testing many design flaws were noted and several were adapted during testing to improve the function of the glove. Results of the testing showed that the glove could detect wrist and finger extensions but that the sensitivity had to be calibrated for each patient. It also allowed both the therapist and patient to know whether the patient was actually performing the task in the manner requested by the therapist. Further work will reveal whether this feedback can enhance recovery of hand function in neurologically impaired patients.
Dissertation/Thesis
Masters Thesis Bioengineering 2015