Статті в журналах: "Transhumeral prosthesis control"

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Tereshenko, Vlad, Riccardo Giorgino, Kyle R. Eberlin, Ian L. Valerio, Jason M. Souza, Mario Alessandri-Bonetti, Giuseppe M. Peretti, and Oskar C. Aszmann. "Emerging Value of Osseointegration for Intuitive Prosthetic Control after Transhumeral Amputations: A Systematic Review." Plastic and Reconstructive Surgery - Global Open 12, no. 5 (May 2024): e5850. http://dx.doi.org/10.1097/gox.0000000000005850.

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Background: Upper extremity limb loss profoundly impacts a patient’s quality of life and well-being and carries a significant societal cost. Although osseointegration allows the attachment of the prosthesis directly to the bone, it is a relatively recent development as an alternative to conventional socket prostheses. The objective of this review was to identify reports on osseointegrated prosthetic embodiment for transhumeral amputations and assess the implant systems used, postoperative outcomes, and complications. Methods: A systematic review following PRISMA and AMSTAR guidelines assessed functional outcomes, implant longevity and retention, activities of daily living, and complications associated with osseointegrated prostheses in transhumeral amputees. Results: The literature search yielded 794 articles, with eight of these articles (retrospective analyses and case series) meeting the inclusion criteria. Myoelectric systems equipped with Osseointegrated Prostheses for the Rehabilitation of Amputees implants have been commonly used as transhumeral osseointegration systems. The transhumeral osseointegrated prostheses offered considerable improvements in functional outcomes, with participants demonstrating enhanced range of motion and improved performance of activities compared with traditional socket-based prostheses. One study demonstrated the advantage of an osseointegrated implant as a bidirectional gateway for signal transmission, enabling intuitive control of a bionic hand. Conclusions: Osseointegrated prostheses hold the potential to significantly improve the quality of life for individuals with transhumeral amputations. Continued research and clinical expansion are expected to lead to the realization of enhanced efficacy and safety in this technique, accompanied by cost reductions over time as a result of improved efficiencies and advancements in device design.

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de Backer-Bes, Femke, Maaike Lange, Michael Brouwers, and Iris van Wijk. "De Hoogstraat Xperience Prosthesis Transhumeral: An Innovative Test Prosthesis." JPO Journal of Prosthetics and Orthotics 36, no. 3 (July 2024): 193–97. http://dx.doi.org/10.1097/jpo.0000000000000510.

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ABSTRACT Introduction To choose a suitable prosthesis, clients need to experience both the weight and the control of a prosthesis. A few years ago, De Hoogstraat Rehabilitation Center developed the Xperience Prosthesis for children and adults with a transradial congenital or acquired limb deficiency. Because of the positive effects, we developed a reusable test prosthesis for the transhumeral level. Xperience Prosthesis Transhumeral is an innovative test prosthesis and an essential tool in managing expectations when providing clients with a suitable upper-limb prosthesis. Xperience Prosthesis Transhumeral is a 3D-printed, reusable adjustable socket system with a passive elbow unit and the possibility to fit and experience myoelectric, static, and passive terminal devices. Conclusions Xperience Prosthesis Transhumeral is a practical and easy-to-handle tool for professionals. For clients, this tool is a unique way to experience the weight, function, and control of a prosthesis before making a final choice. Clinical Relevance Using Xperience Prosthesis Transhumeral in an expert rehabilitation center for upper-limb clients guides professionals to choose the right prosthesis with the client.

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Sattar, Neelum Yousaf, Zareena Kausar, Syed Ali Usama, Umer Farooq, Muhammad Faizan Shah, Shaheer Muhammad, Razaullah Khan, and Mohamed Badran. "fNIRS-Based Upper Limb Motion Intention Recognition Using an Artificial Neural Network for Transhumeral Amputees." Sensors 22, no. 3 (January 18, 2022): 726. http://dx.doi.org/10.3390/s22030726.

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Prosthetic arms are designed to assist amputated individuals in the performance of the activities of daily life. Brain machine interfaces are currently employed to enhance the accuracy as well as number of control commands for upper limb prostheses. However, the motion prediction for prosthetic arms and the rehabilitation of amputees suffering from transhumeral amputations is limited. In this paper, functional near-infrared spectroscopy (fNIRS)-based approach for the recognition of human intention for six upper limb motions is proposed. The data were extracted from the study of fifteen healthy subjects and three transhumeral amputees for elbow extension, elbow flexion, wrist pronation, wrist supination, hand open, and hand close. The fNIRS signals were acquired from the motor cortex region of the brain by the commercial NIRSport device. The acquired data samples were filtered using finite impulse response (FIR) filter. Furthermore, signal mean, signal peak and minimum values were computed as feature set. An artificial neural network (ANN) was applied to these data samples. The results show the likelihood of classifying the six arm actions with an accuracy of 78%. The attained results have not yet been reported in any identical study. These achieved fNIRS results for intention detection are promising and suggest that they can be applied for the real-time control of the transhumeral prosthesis.

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Molina Arias, Ludwin, Marek Iwaniec, Paulina Pirowska, Magdalena Smoleń, and Piotr Augustyniak. "Head and Voice-Controlled Human-Machine Interface System for Transhumeral Prosthesis." Electronics 12, no. 23 (November 24, 2023): 4770. http://dx.doi.org/10.3390/electronics12234770.

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The design of artificial limbs is a research topic that has, over time, attracted considerable interest from researchers in various fields of study, such as mechanics, electronics, robotics, and neuroscience. Continuous efforts are being made to build electromechanical systems functionally equivalent to the original limbs and to develop strategies to control them appropriately according to the intentions of the user. The development of Human–Machine Interfaces (HMIs) is a key point in the development of upper limb prostheses, since the actions carried out with the upper limbs lack fixed patterns, in contrast to the more predictable nature of lower limb movements. This paper presents the development of an HMI system for the control of a transhumeral prosthesis. The HMI is based on a hybrid control strategy that uses voice commands to trigger prosthesis movements and regulates the applied grip strength when the user turns his head. A prototype prosthesis was built using 3D technology and trials were conducted to test the proposed control strategy under laboratory conditions. Numerical simulations were also performed to estimate the grip strength generated. The results obtained show that the proposed prosthesis with the dedicated HMI is a promising low-cost alternative to the current solutions. The proposed hybrid control system is capable of recognizing the user’s voice with an accuracy of up to 90%, controlling the prosthesis joints and adjusting the grip strength according to the user’s wishes.

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Alshammary, Nasser A., Daniel A. Bennett, and Michael Goldfarb. "Synergistic Elbow Control for a Myoelectric Transhumeral Prosthesis." IEEE Transactions on Neural Systems and Rehabilitation Engineering 26, no. 2 (February 2018): 468–76. http://dx.doi.org/10.1109/tnsre.2017.2781719.

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Ahmed, Muhammad Hannan, Jiazheng Chai, Shingo Shimoda, and Mitsuhiro Hayashibe. "Synergy-Space Recurrent Neural Network for Transferable Forearm Motion Prediction from Residual Limb Motion." Sensors 23, no. 9 (April 22, 2023): 4188. http://dx.doi.org/10.3390/s23094188.

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Transhumeral amputees experience considerable difficulties with controlling a multifunctional prosthesis (powered hand, wrist, and elbow) due to the lack of available muscles to provide electromyographic (EMG) signals. The residual limb motion strategy has become a popular alternative for transhumeral prosthesis control. It provides an intuitive way to estimate the motion of the prosthesis based on the residual shoulder motion, especially for target reaching tasks. Conventionally, a predictive model, typically an artificial neural network (ANN), is directly trained and relied upon to map the shoulder–elbow kinematics using the data from able-bodied subjects without extracting any prior synergistic information. However, it is essential to explicitly identify effective synergies and make them transferable across amputee users for higher accuracy and robustness. To overcome this limitation of the conventional ANN learning approach, this study explicitly combines the kinematic synergies with a recurrent neural network (RNN) to propose a synergy-space neural network for estimating forearm motions (i.e., elbow joint flexion–extension and pronation–supination angles) based on residual shoulder motions. We tested 36 training strategies for each of the 14 subjects, comparing the proposed synergy-space and conventional neural network learning approaches, and we statistically evaluated the results using Pearson’s correlation method and the analysis of variance (ANOVA) test. The offline cross-subject analysis indicates that the synergy-space neural network exhibits superior robustness to inter-individual variability, demonstrating the potential of this approach as a transferable and generalized control strategy for transhumeral prosthesis control.

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OʼShaughnessy, Kristina D., Gregory A. Dumanian, Robert D. Lipschutz, Laura A. Miller, Kathy Stubblefield, and Todd A. Kuiken. "Targeted Reinnervation to Improve Prosthesis Control in Transhumeral Amputees." Journal of Bone & Joint Surgery 90, no. 2 (February 2008): 393–400. http://dx.doi.org/10.2106/jbjs.g.00268.

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Nsugbe, Ejay, Oluwarotimi Williams Samuel, Mojisola Grace Asogbon, and Guanglin Li. "A Self-Learning and Adaptive Control Scheme for Phantom Prosthesis Control Using Combined Neuromuscular and Brain-Wave Bio-Signals." Engineering Proceedings 2, no. 1 (November 14, 2020): 59. http://dx.doi.org/10.3390/ecsa-7-08169.

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The control scheme in a myoelectric prosthesis includes a pattern recognition section whose task is to decode an input signal, produce a respective actuation signal and drive the motors in the prosthesis limb towards the completion of the user’s intended gesture motion. The pattern recognition architecture works with a classifier which is typically trained and calibrated offline with a supervised learning framework. This method involves the training of classifiers which form part of the pattern recognition scheme, but also induces additional and often undesired lead time in the prosthesis design phase. In this study, a three-phase identification framework is formulated to design a control architecture capable of self-learning patterns from bio-signal inputs from electromyography (neuromuscular) and electroencephalography (brain wave) biosensors, for a transhumeral amputee case study. The results show that the designed self-learning framework can help reduce lead time in prosthesis control interface customisation, and can also be extended as an adaptive control scheme to minimise the performance degradation of the prosthesis controller.

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Nsugbe, Ejay, Carol Phillips, Mike Fraser, and Jess McIntosh. "Gesture recognition for transhumeral prosthesis control using EMG and NIR." IET Cyber-Systems and Robotics 2, no. 3 (September 1, 2020): 122–31. http://dx.doi.org/10.1049/iet-csr.2020.0008.

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Hebert, Jacqueline S., K. Ming Chan, and Michael R. Dawson. "Cutaneous sensory outcomes from three transhumeral targeted reinnervation cases." Prosthetics and Orthotics International 40, no. 3 (March 2016): 303–10. http://dx.doi.org/10.1177/0309364616633919.

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Background: Although targeted muscle reinnervation has been shown to be effective in enhancing prosthetic control for upper limb amputees, restored hand sensations have been variable. An understanding of possible sensory feedback channels is crucial in working toward more effective closed-loop prosthetic control. Objectives: To compare sensory outcomes of different targeted sensory reinnervation approaches. Study design: Case series, cross-sectional, and retrospective. Methods: Three transhumeral amputees that had undergone different sensory reinnervation approaches were recruited. Skin pressure sensitivity thresholds and anatomic sensory mapping were performed using Semmes-Weinstein monofilaments. The clinical charts of the subjects were reviewed to compare the sensory maps performed during the earlier post-reinnervation period. Results: While the first two subjects achieved return of hand sensations on the stump skin in early follow-up, the maps showed attenuation over time. The last subject developed discrete sensations of all digits in the recipient cutaneous nerve territories away from the reinnervated muscles. Conclusions: These findings confirm that it is feasible to restore hand sensation after transhumeral targeted reinnervation, but there is a significant intersubject variability. The intrafascicular approach may be particularly effective in restoring digit sensation and deserves further exploration, as do factors affecting stability of the hand maps over time. Clinical relevance In addition to enabling intuitive motor control of myoelectric prosthesis, targeted reinnervation can also result in sensory restoration of the hand. Documentation of sensory mapping present after reinnervation may assist with exploring future techniques for sensory enhancement, with the goal of working toward closed-loop prosthetic control.

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Cifuentes-Cuadros, Alonso A., Enzo Romero, Sebastian Caballa, Daniela Vega-Centeno, and Dante A. Elias. "The LIBRA NeuroLimb: Hybrid Real-Time Control and Mechatronic Design for Affordable Prosthetics in Developing Regions." Sensors 24, no. 1 (December 22, 2023): 70. http://dx.doi.org/10.3390/s24010070.

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Globally, 2.5% of upper limb amputations are transhumeral, and both mechanical and electronic prosthetics are being developed for individuals with this condition. Mechanics often require compensatory movements that can lead to awkward gestures. Electronic types are mainly controlled by superficial electromyography (sEMG). However, in proximal amputations, the residual limb is utilized less frequently in daily activities. Muscle shortening increases with time and results in weakened sEMG readings. Therefore, sEMG-controlled models exhibit a low success rate in executing gestures. The LIBRA NeuroLimb prosthesis is introduced to address this problem. It features three active and four passive degrees of freedom (DOF), offers up to 8 h of operation, and employs a hybrid control system that combines sEMG and electroencephalography (EEG) signal classification. The sEMG and EEG classification models achieve up to 99% and 76% accuracy, respectively, enabling precise real-time control. The prosthesis can perform a grip within as little as 0.3 s, exerting up to 21.26 N of pinch force. Training and validation sessions were conducted with two volunteers. Assessed with the “AM-ULA” test, scores of 222 and 144 demonstrated the prosthesis’s potential to improve the user’s ability to perform daily activities. Future work will prioritize enhancing the mechanical strength, increasing active DOF, and refining real-world usability.

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Fite, Kevin B., Thomas J. Withrow, Xiangrong Shen, Keith W. Wait, Jason E. Mitchell, and Michael Goldfarb. "A Gas-Actuated Anthropomorphic Prosthesis for Transhumeral Amputees." IEEE Transactions on Robotics 24, no. 1 (February 2008): 159–69. http://dx.doi.org/10.1109/tro.2007.914845.

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Lenzi, Tommaso, James Lipsey, and Jonathon W. Sensinger. "The RIC Arm—A Small Anthropomorphic Transhumeral Prosthesis." IEEE/ASME Transactions on Mechatronics 21, no. 6 (December 2016): 2660–71. http://dx.doi.org/10.1109/tmech.2016.2596104.

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Simon, Ann M., Kristi L. Turner, Laura A. Miller, Gregory A. Dumanian, Benjamin K. Potter, Mark D. Beachler, Levi J. Hargrove, and Todd A. Kuiken. "Myoelectric prosthesis hand grasp control following targeted muscle reinnervation in individuals with transradial amputation." PLOS ONE 18, no. 1 (January 26, 2023): e0280210. http://dx.doi.org/10.1371/journal.pone.0280210.

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Background Despite the growing availability of multifunctional prosthetic hands, users’ control and overall functional abilities with these hands remain limited. The combination of pattern recognition control and targeted muscle reinnervation (TMR) surgery, an innovative technique where amputated nerves are transferred to reinnervate new muscle targets in the residual limb, has been used to improve prosthesis control of individuals with more proximal upper limb amputations (i.e., shoulder disarticulation and transhumeral amputation). Objective The goal of this study was to determine if prosthesis hand grasp control improves following transradial TMR surgery. Methods Eight participants were trained to use a multi-articulating hand prosthesis under myoelectric pattern recognition control. All participated in home usage trials pre- and post-TMR surgery. Upper limb outcome measures were collected following each home trial. Results Three outcome measures (Southampton Hand Assessment Procedure, Jebsen-Taylor Hand Function Test, and Box and Blocks Test) improved 9–12 months post-TMR surgery compared with pre-surgery measures. The Assessment of Capacity for Myoelectric Control and Activities Measure for Upper Limb Amputees outcome measures had no difference pre- and post-surgery. An offline electromyography analysis showed a decrease in grip classification error post-TMR surgery compared to pre-TMR surgery. Additionally, a majority of subjects noted qualitative improvements in their residual limb and phantom limb sensations post-TMR. Conclusions The potential for TMR surgery to result in more repeatable muscle contractions, possibly due to the reduction in pain levels and/or changes to phantom limb sensations, may increase functional use of many of the clinically available dexterous prosthetic hands.

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Maas, Bart, Zack A. Wright, Blair A. Lock, Corry K. van der Sluis, and Raoul M. Bongers. "Using Serious Games to Measure Upper-Limb Myoelectric Pattern Recognition Prosthesis Control Performance in an At-Home Environment." JPO Journal of Prosthetics and Orthotics 36, no. 3 (April 3, 2024): 153–60. http://dx.doi.org/10.1097/jpo.0000000000000503.

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Abstract Introduction Upper-limb prostheses have undergone substantial technological improvements in the last two decades, but user complaints and abandonment rates have hardly changed. This may follow from the use of laboratory-based tests when assessing new technology instead of measuring prosthesis use in at-home situations. Serious games might be used to assess prosthesis use at home. Objectives The aim of this study was to assess the feasibility, validity, and reliability of using serious games to measure myocontrol in at-home situations. Study Design The design of this study is a cohort study with repeated measurements. Methods All 10 participants (five males; seven transradial and three transhumeral defects) used pattern recognition (PR) to control their prosthesis. Two serious games were included in the PR software: Simon Says and In-The-Zone. Participants were instructed to use their prosthesis as they normally would for 2 weeks with the additional instruction to play at least 18 serious games (±90 minutes in total). Outcome measures for aspects of prosthesis use were wear time, months of prosthesis use, and user experiences, and serious games outcomes were success rate and completion time. Results For feasibility, all but one participant completed the minimum of 18 games, and user experiences were mostly positive. For validity, no relationships were found between the aspects of prosthesis use and performance in the serious games. For reliability, test-retest reliability for success rate was high (intraclass correlation [ICC], 0.79), but low for completion time (ICC, 0.18) in both games. Conclusions Feasibility and reliability of using serious games as an assessment instrument for prosthesis control in at-home situations appeared to be good; however, validity could not be established. The serious games should be improved to increase validity. Furthermore, more outcome measures that reveal aspects of prosthesis use should be considered. Clinical Relevance Statement Assessing myocontrol in at-home situations by using serious games is feasible and reliable, but validity needs further attention.

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Gu, Yikun, Dapeng Yang, Luke Osborn, Daniel Candrea, Hong Liu, and Nitish Thakor. "An adaptive socket with auto-adjusting air bladders for interfacing transhumeral prosthesis: A pilot study." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 233, no. 8 (June 5, 2019): 812–22. http://dx.doi.org/10.1177/0954411919853960.

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Comfort is a critical aspect in the application of wearable device, such as rehabilitation robots and upper limb prostheses. As a physical interface between human body and prosthetic limb, the socket and its comfort largely contribute to the user’s acceptance. Traditional sockets are static, lacking dynamic adjustment mechanism for the contact pressure. To ensure a reliable suspension during daily activities, the socket is usually designed to be tightly attached, with a large stress, on the residual limb, which may introduce considerable discomfort during long-term use. In this article, we present a novel adaptive transhumeral socket, in which we employ four independent bladders contacting with the stump. Not only can these bladders provide a necessary suspension for the device but also form an air cushion (soft body) that helps relieve the pressure concentration between the biological body and physical prosthesis. In real time, this adaptive socket continuously monitors the limb posture, the operating load, and the contacting pressure between the socket and the limb, and then dynamically adjusts the clamping force to ensure a reliable attachment during various daily activities. Since well adapting to the contours of the stump, the bladders can effectively accommodate the volume change of the stump, making a balanced load distribution on load-tolerant areas. Through modeling and numerical analysis, we established a dynamic strategy for estimating the external load and an automatic scheme for adjusting the bladders’ air pressure. Finally, a close-loop control was constructed based on the contact pressure measured by our self-developed force sensors. Our preliminary experiments on one normal (i.e. non-amputee) subject verified the effectiveness of the proposed method, showing that the adaptive socket can considerably reduce the socket–limb contact pressure while sustaining a secure suspension on the upper arm.

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Segura, Diego, Enzo Romero, Victoria E. Abarca, and Dante A. Elias. "Upper Limb Prostheses by the Level of Amputation: A Systematic Review." Prosthesis 6, no. 2 (March 19, 2024): 277–300. http://dx.doi.org/10.3390/prosthesis6020022.

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This review article aims to provide an updated and comprehensive overview of the latest trends in adult upper limb prostheses, specifically targeting various amputation levels such as transradial, transmetacarpal, transcarpal, and transhumeral. A systematic search was conducted across multiple databases, including IEEE Xplore, MDPI, Scopus, Frontiers, and Espacenet, covering from 2018 to 2023. After applying exclusion criteria, 49 scientific articles (33 patents and 16 commercial prostheses) were meticulously selected for review. The article offers an in-depth analysis of several critical aspects of upper limb prostheses. It discusses the evolution and current state of input control mechanisms, the number of degrees of freedom, and the variety of grips available in prostheses, all tailored according to the level of amputation. Additionally, the review delves into the selection of materials used in developing these prostheses and examines the progression of technology readiness levels. A significant focus is also placed on the evolution of prosthesis weight over the years for different amputation levels. Moreover, the review identifies and explores critical technological challenges and prospects in upper limb prostheses. Finally, the article culminates with a conclusion that encapsulates the key findings and insights on the advancements and ongoing developments in this field.

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Wang, Bingbin, Levi Hargrove, Xinqi Bao, and Ernest N. Kamavuako. "Surface EMG Statistical and Performance Analysis of Targeted-Muscle-Reinnervated (TMR) Transhumeral Prosthesis Users in Home and Laboratory Settings." Sensors 22, no. 24 (December 14, 2022): 9849. http://dx.doi.org/10.3390/s22249849.

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A pattern-recognition (PR)-based myoelectric control system is the trend of future prostheses development. Compared with conventional prosthetic control systems, PR-based control systems provide high dexterity, with many studies achieving >95% accuracy in the last two decades. However, most research studies have been conducted in the laboratory. There is limited research investigating how EMG signals are acquired when users operate PR-based systems in their home and community environments. This study compares the statistical properties of surface electromyography (sEMG) signals used to calibrate prostheses and quantifies the quality of calibration sEMG data through separability indices, repeatability indices, and correlation coefficients in home and laboratory settings. The results demonstrate no significant differences in classification performance between home and laboratory environments in within-calibration classification error (home: 6.33 ± 2.13%, laboratory: 7.57 ± 3.44%). However, between-calibration classification errors (home: 40.61 ± 9.19%, laboratory: 44.98 ± 12.15%) were statistically different. Furthermore, the difference in all statistical properties of sEMG signals is significant (p < 0.05). Separability indices reveal that motion classes are more diverse in the home setting. In summary, differences in sEMG signals generated between home and laboratory only affect between-calibration performance.

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Ahmed, Muhammad Hannan, Kyo Kutsuzawa, and Mitsuhiro Hayashibe. "Transhumeral Arm Reaching Motion Prediction through Deep Reinforcement Learning-Based Synthetic Motion Cloning." Biomimetics 8, no. 4 (August 15, 2023): 367. http://dx.doi.org/10.3390/biomimetics8040367.

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The lack of intuitive controllability remains a primary challenge in enabling transhumeral amputees to control a prosthesis for arm reaching with residual limb kinematics. Recent advancements in prosthetic arm control have focused on leveraging the predictive capabilities of artificial neural networks (ANNs) to automate elbow joint motion and wrist pronation–supination during target reaching tasks. However, large quantities of human motion data collected from different subjects for various activities of daily living (ADL) tasks are required to train these ANNs. For example, the reaching motion can be altered when the height of the desk is changed; however, it is cumbersome to conduct human experiments for all conditions. This paper proposes a framework for cloning motion datasets using deep reinforcement learning (DRL) to cater to training data requirements. DRL algorithms have been demonstrated to create human-like synergistic motion in humanoid agents to handle redundancy and optimize movements. In our study, we collected real motion data from six individuals performing multi-directional arm reaching tasks in the horizontal plane. We generated synthetic motion data that mimicked similar arm reaching tasks by utilizing a physics simulation and DRL-based arm manipulation. We then trained a CNN-LSTM network with different configurations of training motion data, including DRL, real, and hybrid datasets, to test the efficacy of the cloned motion data. The results of our evaluation showcase the effectiveness of the cloned motion data in training the ANN to predict natural elbow motion accurately across multiple subjects. Furthermore, motion data augmentation through combining real and cloned motion datasets has demonstrated the enhanced robustness of the ANN by supplementing and diversifying the limited training data. These findings have significant implications for creating synthetic dataset resources for various arm movements and fostering strategies for automatized prosthetic elbow motion.

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Nsugbe, Ejay, Oluwarotimi Williams Samuel, Mojisola Grace Asogbon, and Guanglin Li. "Phantom motion intent decoding for transhumeral prosthesis control with fused neuromuscular and brain wave signals." IET Cyber-Systems and Robotics 3, no. 1 (March 2021): 77–88. http://dx.doi.org/10.1049/csy2.12009.

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Schlüter, Christoph, Washington Caraguay, and Doris Cáliz Ramos. "Development of a low-cost EMG-data acquisition armband to control an above-elbow prosthesis." Journal of Physics: Conference Series 2232, no. 1 (May 1, 2022): 012019. http://dx.doi.org/10.1088/1742-6596/2232/1/012019.

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Abstract This work presents the development and implementation of an armband for EMG-data acquisition of the upper arm. The developed prototype serves for investigations on EMG-signal processing with the final objective of reliably controlling a prosthesis for a transhumeral amputee. To make the product available for a greatest possible number of people one of the main characteristics will be a design of very low cost. A focus is put on the electric circuit design. In order to manufacture the prototype without difficulties, it is exclusively designed with components, which are available on the Ecuadorian market. The development is based on previous investigations and approaches of other researchers. With help of electric circuit simulations, the design was adapted and optimized step by step and a reliable low-noise circuit was established. All components are arranged on printed circuit boards in a way to keep the device as small as possible. To optimally avoid noise the length of the connection from the electrodes to the amplifier is minimized. Compact 3D-printed housings cover all the electric components. All housings consist of only two parts and are intuitive to assemble. Holes in the bottom offer space to fix electrodes via a snap-fastener connection. 3D-printed elastic straps are designed to connect the subsystems and hold the device in place. The armband including two sensors weighs 92 g and is capable of measuring two muscles with a bipolar EMG-setting each, sharing one reference electrode, which is aligned on the side of the upper arm between the biceps and triceps muscles. The amplification of the sensors is adjustable individually by potentiometers, facilitating a gain factor range of 211 to 2016 V/V. The data is recorded by a microcontroller board and send to a computer for processing via wire or Bluetooth. For wireless operation, rechargeable batteries are integrated. Test measurements on an able-bodied human prove the functionality of the device.

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Schofield, Jonathon S., Katherine R. Schoepp, Michael Stobbe, Paul D. Marasco, and Jacqueline S. Hebert. "Fabrication and application of an adjustable myoelectric transhumeral prosthetic socket." Prosthetics and Orthotics International 43, no. 5 (March 29, 2019): 564–67. http://dx.doi.org/10.1177/0309364619836353.

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Background and Aim: Although upper limb myoelectric prostheses can offer improved functionality and dexterity over body-powered systems, abandonment rates remain high. User dissatisfaction in comfort and control are among the top contributors. The design of the prosthetic socket must be comfortable, while maintaining contact of control electrodes with the residual limb throughout the day. We present a myoelectric socket design that provides user-adjustable compression over electrode control sites to promote consistent control, while maintaining comfort and fit. Technique: A cable tensioning system was threaded through a series of paneled windows in the socket wall over electrode sites. Adjusting tension provided tuning of electrode contact. Discussion: A case study of a single transhumeral prosthetic user with a follow-up interview 11 months post delivery suggests that our adjustable design has the potential to address control and comfort challenges, critical factors in myoelectric prosthetic use, and abandonment. Clinical relevance Achieving consistent electrode contact with muscle control sites in traditional rigid sockets is a critical challenge for myoelectric prostheses. We present a unique solution via user-adjustable electrode contacts built into the socket.

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Li, Sujiao, Wanjing Sun, Wei Li, and Hongliu Yu. "Enhancing Robustness of Surface Electromyography Pattern Recognition at Different Arm Positions for Transhumeral Amputees Using Deep Adversarial Inception Domain Adaptation." Applied Sciences 14, no. 8 (April 18, 2024): 3417. http://dx.doi.org/10.3390/app14083417.

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Pattern recognition in myoelectric control that relies on the myoelectric activity associated with arm motions is an effective control method applied to myoelectric prostheses. Individuals with transhumeral amputation face significant challenges in effectively controlling their prosthetics, as muscle activation varies with changes in arm positions, leading to a notable decrease in the accuracy of motion pattern recognition and consequently resulting in a high rejection rate of prosthetic devices. Therefore, to achieve high accuracy and arm position stability in upper-arm motion recognition, we propose a Deep Adversarial Inception Domain Adaptation (DAIDA) based on the Inception feature module to enhance the generalization ability of the model. Surface electromyography (sEMG) signals were collected from 10 healthy subjects and two transhumeral amputees while performing hand, wrist, and elbow motions at three arm positions. The recognition performance of different feature modules was compared, and ultimately, accurate recognition of upper-arm motions was achieved using the Inception C module with a recognition accuracy of 90.70% ± 9.27%. Subsequently, validation was performed using data from different arm positions as source and target domains, and the results showed that compared to the direct use of a convolutional neural network (CNN), the recognition accuracy on untrained arm positions increased by 75.71% (p < 0.05), with a recognition accuracy of 91.25% ± 6.59%. Similarly, in testing scenarios involving multiple arm positions, there was a significant improvement in recognition accuracy, with recognition accuracy exceeding 90% for both healthy subjects and transhumeral amputees.

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Pulliam, Christopher L., Joris M. Lambrecht, and Robert F. Kirsch. "Electromyogram-based neural network control of transhumeral prostheses." Journal of Rehabilitation Research and Development 48, no. 6 (2011): 739. http://dx.doi.org/10.1682/jrrd.2010.12.0237.

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Hallworth, Ben W., James A. Austin, Heather E. Williams, Mayank Rehani, Ahmed W. Shehata, and Jacqueline S. Hebert. "A Modular Adjustable Transhumeral Prosthetic Socket for Evaluating Myoelectric Control." IEEE Journal of Translational Engineering in Health and Medicine 8 (2020): 1–10. http://dx.doi.org/10.1109/jtehm.2020.3006416.

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Merad, M., E. de Montalivet, M. Legrand, E. Mastinu, M. Ortiz-Catalan, A. Touillet, N. Martinet, J. Paysant, A. Roby-Brami, and N. Jarrasse. "Assessment of an Automatic Prosthetic Elbow Control Strategy Using Residual Limb Motion for Transhumeral Amputated Individuals With Socket or Osseointegrated Prostheses." IEEE Transactions on Medical Robotics and Bionics 2, no. 1 (February 2020): 38–49. http://dx.doi.org/10.1109/tmrb.2020.2970065.

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KALIKI, RAHUL R., RAHMAN DAVOODI, and GERALD E. LOEB. "PREDICTION OF ELBOW TRAJECTORY FROM SHOULDER ANGLES USING NEURAL NETWORKS." International Journal of Computational Intelligence and Applications 07, no. 03 (September 2008): 333–49. http://dx.doi.org/10.1142/s1469026808002296.

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Patients with transhumeral amputations and C5/C6 quadriplegia may be able to use voluntary shoulder motion as command signals for powered prostheses and functional electrical stimulation, respectively. Spatiotemporal synergies exist between the shoulder and elbow joints for goal-oriented reaching movements as performed by able-bodied subjects. We are using a multi-layer perceptron neural network to discover and embody these synergies. Such a network could be used as a high-level controller that could predict the desired distal arm joint kinematics from the voluntary movements of the shoulder joint of an able-bodied subject. We evaluated this for a task that involved reaching to 16 targets in a horizontal plane. After reaching reasonable offline prediction accuracy for our neural networks, we then deployed the best network to make real-time predictions of the elbow angles and examined its performance on both inter- and intra-subject trials. Finally, we extended the model to utilize the five degrees-of-freedom at the shoulder to control the five degrees-of-freedom required for a prosthetic arm and hand to reach and grasp variously oriented objects in the extrapersonal workspace. Such a system, although very simple, was readily controllable for a reach and grasp task presented to the subject in a virtual reality environment.

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Jarrasse, N., D. Müller, E. De Montalivet, F. Richer, M. Merad, A. Touillet, N. Martinet, and J. Paysant. "A simple movement based control approach to ease the control of a myoelectric elbow prosthetics in transhumeral amputees." Annals of Physical and Rehabilitation Medicine 61 (July 2018): e471. http://dx.doi.org/10.1016/j.rehab.2018.05.1100.

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Cooke, Deirdre M., Matthew Ames, and Saul Geffen. "Life without limbs: Technology to the rescue." Prosthetics and Orthotics International 40, no. 4 (April 27, 2015): 517–21. http://dx.doi.org/10.1177/0309364615579316.

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Background:This article reports a rare and inspirational case of a four-limb amputee, the range of integrated technology solutions that enable him to be a productive member of his family and the process and pitfalls of seeking technology solutions.Case description and methods:A complex case of bilateral transhumeral amputation and bilateral transfemoral amputation with residual upper limbs too short to oppose is presented. The multiple ‘high-tech’ and ‘low-tech’ devices used on a daily basis to move around his house and community, control his environment, communicate and feed himself without the use of limbs, prostheses or a second person are outlined.Findings and outcomes:Recent advances in electronics, computing and telecommunications technologies provide him with capabilities not possible 10 years ago.Conclusion:The process and pitfalls in sourcing technology solutions and the innovative solutions to meet the unique functional needs of this individual provide guidance to those with similarly severe and profound limitations to independence.Clinical relevanceDescriptions of technology solutions to improve independent functioning of those with quadruple amputation without prostheses as well as those with high-level spinal cord injury are of value to occupational therapists, patients and families alike.

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Lontis, Eugen Romulus, Ken Yoshida, and Winnie Jensen. "Non-Invasive Sensory Input Results in Changes in Non-Painful and Painful Sensations in Two Upper-Limb Amputees." Prosthesis 6, no. 1 (December 19, 2023): 1–23. http://dx.doi.org/10.3390/prosthesis6010001.

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Designs of active prostheses attempt to compensate for various functional losses following amputation. Integration of sensory feedback with the functional control re-enables sensory interaction with the environment through the prosthetic. Besides the functional and sensory loss, amputation induces anatomical and physiological changes of the sensory neural pathways, both peripherally and centrally, which can lead to phantom limb pain (PLP). Additionally, referred sensation areas (RSAs) likely originating from peripheral nerve sprouting, regeneration, and sensory reinnervation may develop. RSAs might provide a non-invasive access point to sensory neural pathways that project to the lost limb. This paper aims to report on the sensory input features, elicited using non-invasive electrical stimulation of RSAs that over time alleviated PLP in two upper-limb amputees. The distinct features of RSAs and sensation evoked using mechanical and electrical stimuli were characterized for the two participants over a period of 7 and 9 weeks, respectively. Both participants received transradial and transhumeral amputation following traumatic injuries. In one participant, a relatively low but stable number of RSAs provided a large variety of types of evoked phantom hand (PH) sensations. These included non-painful touch, vibration, tingling, stabbing, pressure, warmth/cold as well as the perception of various positions and movements of the phantom hand upon stimulation. Discomforting and painful sensations were induced with both mechanical and electrical stimuli. The other participant had a relatively large number of RSAs which varied over time. Stimulation of the RSAs provided mostly non-painful sensations of touch in the phantom hand. Temporary PLP alleviation and a change in the perception of the phantom hand from a tight to a more open fist were reported by both participants. The specificity of RSAs, dynamics in perception of the sensory input, and the associated alleviation of PLP could be effectively exploited by designs of future active prostheses. As such, techniques for the modulation of the sensory input associated with paradigms from interaction with the environment may add another dimension of protheses towards integrating personalized therapy for PLP.

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WATANABE, Takahiro, Kengo OHNISHI, and Keiji IMADO. "B211 Fundamental experiment for mechanics-based adjustment of the Bowden cable control system for body-powered transhumeral prostheses." Proceedings of the JSME Conference on Frontiers in Bioengineering 2007.18 (2007): 133–34. http://dx.doi.org/10.1299/jsmebiofro.2007.18.133.

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32

Zbinden, Jan, Paolo Sassu, Enzo Mastinu, Eric J. Earley, Maria Munoz-Novoa, Rickard Brånemark, and Max Ortiz-Catalan. "Improved control of a prosthetic limb by surgically creating electro-neuromuscular constructs with implanted electrodes." Science Translational Medicine 15, no. 704 (July 12, 2023). http://dx.doi.org/10.1126/scitranslmed.abq3665.

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Remnant muscles in the residual limb after amputation are the most common source of control signals for prosthetic hands, because myoelectric signals can be generated by the user at will. However, for individuals with amputation higher up the arm, such as an above-elbow (transhumeral) amputation, insufficient muscles remain to generate myoelectric signals to enable control of the lost arm and hand joints, thus making intuitive control of wrist and finger prosthetic joints unattainable. We show that severed nerves can be divided along their fascicles and redistributed to concurrently innervate different types of muscle targets, particularly native denervated muscles and nonvascularized free muscle grafts. We engineered these neuromuscular constructs with implanted electrodes that were accessible via a permanent osseointegrated interface, allowing for bidirectional communication with the prosthesis while also providing direct skeletal attachment. We found that the transferred nerves effectively innervated their new targets as shown by a gradual increase in myoelectric signal strength. This allowed for individual flexion and extension of all five fingers of a prosthetic hand by a patient with a transhumeral amputation. Improved prosthetic function in tasks representative of daily life was also observed. This proof-of-concept study indicates that motor neural commands can be increased by creating electro-neuromuscular constructs using distributed nerve transfers to different muscle targets with implanted electrodes, enabling improved control of a limb prosthesis.

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Earley, Eric J., Anton Berneving, Jan Zbinden, and Max Ortiz-Catalan. "Neurostimulation artifact removal for implantable sensors improves signal clarity and decoding of motor volition." Frontiers in Human Neuroscience 16 (October 19, 2022). http://dx.doi.org/10.3389/fnhum.2022.1030207.

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As the demand for prosthetic limbs with reliable and multi-functional control increases, recent advances in myoelectric pattern recognition and implanted sensors have proven considerably advantageous. Additionally, sensory feedback from the prosthesis can be achieved via stimulation of the residual nerves, enabling closed-loop control over the prosthesis. However, this stimulation can cause interfering artifacts in the electromyographic (EMG) signals which deteriorate the reliability and function of the prosthesis. Here, we implement two real-time stimulation artifact removal algorithms, Template Subtraction (TS) and ε-Normalized Least Mean Squares (ε-NLMS), and investigate their performance in offline and real-time myoelectric pattern recognition in two transhumeral amputees implanted with nerve cuff and EMG electrodes. We show that both algorithms are capable of significantly improving signal-to-noise ratio (SNR) and offline pattern recognition accuracy of artifact-corrupted EMG signals. Furthermore, both algorithms improved real-time decoding of motor intention during active neurostimulation. Although these outcomes are dependent on the user-specific sensor locations and neurostimulation settings, they nonetheless represent progress toward bi-directional neuromusculoskeletal prostheses capable of multifunction control and simultaneous sensory feedback.

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Razak, N. A. Abd, H. Gholizadeh, N. Hasnan, N. A. Abu Osman, S. S. Mohd Fadzil, and N. A. Hashim. "An anthropomorphic transhumeral prosthesis socket developed based on an oscillometric pump and controlled by force-sensitive resistor pressure signals." Biomedical Engineering / Biomedizinische Technik 62, no. 1 (January 1, 2017). http://dx.doi.org/10.1515/bmt-2015-0106.

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AbstractWhile considering the importance of the interface between amputees and prosthesis sockets, we study an anthropomorphic prosthesis socket whose size can be dynamically changed according to the requirements of the residual limb. First, we introduce the structure and function of the anthropomorphic prosthesis socket. Second, we study the dynamic model of the prosthesis system and analyze the dynamic characteristics of the prosthesis socket system, the inputs of an oscillometric pump, and the control mechanism of force-sensitive resistor (FSR) pressure signals. Experiments on 10 healthy subjects using the designed system yield an average detection result between 102 and 112 kPa for the FSR pressure sensor and 39 and 41 kPa for the oscillometric pump. Results show the function of the FSR pressure signal in maintaining the contact pressure between the sockets and the residual limb. The potential development of an auto-adjusted socket that uses an oscillometric pump system will provide prosthetic sockets with controllable contact pressure at the residual limb. Moreover, this development is an attractive research area for researchers involved in rehabilitation engineering, prosthetics, and orthotics.

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"Towards Control of a Transhumeral Prosthesis with EEG Signals." Bioengineering 5, no. 2 (March 22, 2018): 26. http://dx.doi.org/10.3390/bioengineering5020026.

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Toedtheide, Alexander, Edmundo Pozo Fortunić, Johannes Kühn, Elisabeth Jensen, and Sami Haddadin. "A transhumeral prosthesis with an artificial neuromuscular system: Sim2real-guided design, modeling, and control." International Journal of Robotics Research, February 20, 2024. http://dx.doi.org/10.1177/02783649231218719.

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In this work we introduce a new type of human-inspired upper-limb prostheses. The Artificial Neuromuscular Prosthesis (ANP) imitates the human neuromuscular system in the sense of its compliance, backdrivability, natural motion, proprioceptive sensing, and kinesthetics. To realize this challenging goal, we introduce a novel human-inspired and simulation-based development paradigm to design the prosthesis mechatronics in correspondence to the human body. The ANP provides body awareness, contact awareness, and human-like contact response, realized via floating base rigid-body models, disturbance observers, and joint impedance control—concepts known from established state-of-the-art robotics. The ANP mechatronics is characterized by a four degrees of freedom (dof) torque-controlled human-like kinematics, a tendon-driven 2-dof wrist, and spatial orientation sensing at a weight of 1.7 kg (without hand and battery). The paper deals with the rigorous mathematical modeling, control, design and evaluation of this device type along initially defined requirements within a single prototype only. The proposed systemic and grasping capabilities are verified under laboratory conditions by an unimpaired user. Future work will increase the technology readiness level of the next generation device, where human studies with impaired users will be done.

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Sattar, Neelum Yousaf, Zareena Kausar, Syed Ali Usama, Umer Farooq, and Umar Shahbaz Khan. "EMG Based Control of Transhumeral Prosthesis Using Machine Learning Algorithms." International Journal of Control, Automation and Systems, July 27, 2021. http://dx.doi.org/10.1007/s12555-019-1058-5.

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Said, Hakim, Todd Kuiken, Robert Lipzchutz, Laura Miller, and Gregory Dumanian. "Nerve Transfers in Transhumeral Amputation: Creating Myoneurosomes for Improved Myoelectric Prosthesis Control." Journal of Reconstructive Microsurgery 21, no. 07 (October 13, 2005). http://dx.doi.org/10.1055/s-2005-918994.

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Mastinu, Enzo, Leonard F. Engels, Francesco Clemente, Mariama Dione, Paolo Sassu, Oskar Aszmann, Rickard Brånemark, et al. "Neural feedback strategies to improve grasping coordination in neuromusculoskeletal prostheses." Scientific Reports 10, no. 1 (July 16, 2020). http://dx.doi.org/10.1038/s41598-020-67985-5.

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Abstract Conventional prosthetic arms suffer from poor controllability and lack of sensory feedback. Owing to the absence of tactile sensory information, prosthetic users must rely on incidental visual and auditory cues. In this study, we investigated the effect of providing tactile perception on motor coordination during routine grasping and grasping under uncertainty. Three transhumeral amputees were implanted with an osseointegrated percutaneous implant system for direct skeletal attachment and bidirectional communication with implanted neuromuscular electrodes. This neuromusculoskeletal prosthesis is a novel concept of artificial limb replacement that allows to extract control signals from electrodes implanted on viable muscle tissue, and to stimulate severed afferent nerve fibers to provide somatosensory feedback. Subjects received tactile feedback using three biologically inspired stimulation paradigms while performing a pick and lift test. The grasped object was instrumented to record grasping and lifting forces and its weight was either constant or unexpectedly changed in between trials. The results were also compared to the no-feedback control condition. Our findings confirm, in line with the neuroscientific literature, that somatosensory feedback is necessary for motor coordination during grasping. Our results also indicate that feedback is more relevant under uncertainty, and its effectiveness can be influenced by the selected neuromodulation paradigm and arguably also the prior experience of the prosthesis user.

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Segas, Effie, Sébastien Mick, Vincent Leconte, Océane Dubois, Rémi Klotz, Daniel Cattaert, and Aymar de Rugy. "Intuitive movement-based prosthesis control enables arm amputees to reach naturally in virtual reality." eLife 12 (October 17, 2023). http://dx.doi.org/10.7554/elife.87317.3.

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Impressive progress is being made in bionic limbs design and control. Yet, controlling the numerous joints of a prosthetic arm necessary to place the hand at a correct position and orientation to grasp objects remains challenging. Here, we designed an intuitive, movement-based prosthesis control that leverages natural arm coordination to predict distal joints missing in people with transhumeral limb loss based on proximal residual limb motion and knowledge of the movement goal. This control was validated on 29 participants, including seven with above-elbow limb loss, who picked and placed bottles in a wide range of locations in virtual reality, with median success rates over 99% and movement times identical to those of natural movements. This control also enabled 15 participants, including three with limb differences, to reach and grasp real objects with a robotic arm operated according to the same principle. Remarkably, this was achieved without any prior training, indicating that this control is intuitive and instantaneously usable. It could be used for phantom limb pain management in virtual reality, or to augment the reaching capabilities of invasive neural interfaces usually more focused on hand and grasp control.

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Jarrassé, Nathanaël, Etienne de Montalivet, Florian Richer, Caroline Nicol, Amélie Touillet, Noël Martinet, Jean Paysant, and Jozina B. de Graaf. "Phantom-Mobility-Based Prosthesis Control in Transhumeral Amputees Without Surgical Reinnervation: A Preliminary Study." Frontiers in Bioengineering and Biotechnology 6 (November 29, 2018). http://dx.doi.org/10.3389/fbioe.2018.00164.

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Jasti, Harshitha. "Utilizing EEG Signal Data and Motion to Aid in Prosthetic Hand Motion." Journal of Student Research 12, no. 4 (November 30, 2023). http://dx.doi.org/10.47611/jsrhs.v12i4.5883.

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Current prosthetic arm technologies are often difficult to use intuitively by amputees, require invasive surgical procedures, and can be extremely costly with prices ranging from $20,000 to $80,000. To address these challenges, the engineering goal of this project aims to design a smart, low-cost, mind-controlled transhumeral prosthesis by integrating the brain-interfacing capabilities of electroencephalography (EEG), the economical means of 3D printing technology, and gesture-detecting attributes of an accelerometer-gyroscope. Single-channel brain signals are transmitted through Bluetooth to be interpreted by a novel EEG decoding algorithm and head gestures from the inertial measurement unit actuate movement within the arm. Force sensitive resistors were employed to regulate force control in real-time to optimize grasp type. An LCD screen is integrated within the arm’s design to display the type of touch it is exerting on an object. The arm itself was printed with an original design utilizing PLA plastic filament making it extremely durable and lightweight. After thoroughly testing the prosthesis, the novel EEG decoding system boasts an accuracy of 94.7% and a user cognition to machine delay of 1.64 + - 0.37 seconds. The inertial measurement unit system recognizes user gestures with a delay of .136 seconds. With a bill of materials approximately $375 USD and ability to be moved in 4 degrees of motion, this novel upper limb prosthesis serves as a promising alternative to existing units on the market. The algorithms developed within this project have a wide range of use within other brain control interface projects.

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Toedtheide, Alexander, Edmundo Pozo Fortunić, Johannes Kühn, Elisabeth Rose Jensen, and Sami Haddadin. "A Wearable Force-Sensitive and Body-Aware Exoprosthesis for a Transhumeral Prosthesis Socket." IEEE Transactions on Robotics, 2023, 1–21. http://dx.doi.org/10.1109/tro.2023.3251947.

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Chateaux, Manon, Olivier Rossel, Fabien Vérité, Caroline Nicol, Amélie Touillet, Jean Paysant, Nathanaël Jarrassé, and Jozina B. De Graaf. "New insights into muscle activity associated with phantom hand movements in transhumeral amputees." Frontiers in Human Neuroscience 18 (August 30, 2024). http://dx.doi.org/10.3389/fnhum.2024.1443833.

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IntroductionMuscle activity patterns in the residual arm are systematically present during phantom hand movements (PHM) in transhumeral amputees. However, their characteristics have not been directly investigated yet, leaving their neurophysiological origin poorly understood. This study pioneers a neurophysiological perspective in examining PHM-related muscle activity patterns by characterizing and comparing them with those in the arm, forearm, and hand muscles of control participants executing intact hand movements (IHM) of similar types.MethodsTo enable rigorous comparison, we developed meta-variables independent of electrode placement, quantifying the phasic profile of recorded surface EMG signals and the specificity of their patterns across electrode sites and movement types.ResultsSimilar to the forearm and hand muscles during IHM, each signal recorded from the residual upper arm during PHM displays a phasic profile, synchronized with the onset and offset of each movement repetition. Furthermore, the PHM-related patterns of phasic muscle activity are specific not only to the type of movement but also to the electrode site, even within the same upper arm muscle, while these muscles exhibit homogeneous activities in intact arms.DiscussionOur results suggest the existence of peripheral reorganization, eventually leading to the emergence of independently controlled muscular sub-volumes. This reorganization potentially occurs through the sprouting of severed axons and the recapture of muscle fibers in the residual limb. Further research is imperative to comprehend this mechanism and its relationship with PHM, holding significant implications for the rehabilitation process and myoelectric prosthesis control.

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Chi, Albert. "Improved Control of a Virtual Prosthesis Using a Pattern Recognition Algorithm and an Interactive Training Environment in a Transhumeral Amputee Demonstrating Local Reinnervation." Biomedical Journal of Scientific & Technical Research 18, no. 3 (May 28, 2019). http://dx.doi.org/10.26717/bjstr.2019.18.003143.

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Brauckmann, Vesta, Jorge Mayor, Luisa Ernst, and Jennifer Ernst. "How a robotic visualization system can facilitate targeted muscle reinnervation." Journal of Reconstructive Microsurgery Open, July 21, 2023. http://dx.doi.org/10.1055/a-2134-8633.

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Background:To enable and further improve microsurgical outcomes, different loupes and optic based microscopes have been proposed in recent years. In amputation surgery continuous progress and prosthetic developments have provided amputees with improved degree of function and quality of life.We present a 17-year-old patient who suffered traumatic loss of the left upper limb and underwent TMR-surgery facilitated by a 3D-robotic-exoscope-system. Methods:The rerouting of the distal ends of the arm-nerves (Targeted Muscle Reinnervation) was performed in the upper limb of a traumatic transhumeral amputee patient using 3D-robotic-exoscope-system (RS, RoboticScope). Perioperative data was collected and compared to standard. Users’ evaluation of the system during the surgical procedure was done using a 5-point-Likert-Scale. Results:Operation time was 311 minutes, the robotic system was used for 101 minutes. Overall users´ evaluation revealed 4,5 for selected items on the Likert-Scale. The evaluation showed similar results in evaluation of the system by main and assistant surgeons. No special training was required beforehand. The bimanual control allowed for improved personal freedom in the surgical field at a comfortable position. The imaging of colors will need future improvements until authentic representation of in situ structures is achieved. Conclusions:Major advantages of a robotic Scope-3D-exoscope-system are improved image quality, ergonomic position, and increased accessibility in a wider operating field due to system implied features. Another benefit is digital documentation, simultaneous education through possibility of capturing images and videos and easy transportation between operating rooms without risk to harm the vulnerable optic. Digital microscopes are still not yet implemented as standard of care.

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