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Maas B, Van Der Sluis CK, Bongers RM. Assessing the effectiveness of serious game training designed to assist in upper limb prothesis rehabilitation. FRONTIERS IN REHABILITATION SCIENCES 2024; 5:1353077. [PMID: 38348457 PMCID: PMC10859406 DOI: 10.3389/fresc.2024.1353077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 01/16/2024] [Indexed: 02/15/2024]
Abstract
Introduction Controlling a myoelectric upper limb prosthesis is difficult, therefore training is required. Since training with serious games showed promising results, the current paper focuses on game design and its effectivity for transfer between in-game skill to actual prosthesis use for proportional control of hand opening and control of switching between grips. We also examined training duration and individual differences. Method Thirty-six participants were randomly assigned to one of three groups: a task-specific serious game training group, a non-task-specific serious game training group and a control group. Each group performed a pre-test, mid-test and a post-test with five training sessions between each test moment. Test sessions assessed proportional control using the Cylinder test, a test designed to measure scaling of hand aperture during grabbing actions, and the combined use of proportional and switch control using the Clothespin Relocation Test, part of the Southampton Hand Assessment Procedure and Tray Test. Switch control was assessed during training by measuring amplitude difference and phasing of co-contraction triggers. Results Differences between groups over test sessions were observed for proportional control tasks, however there was lack of structure in these findings. Maximum aperture changed with test moment and some participants adjusted maximum aperture for smaller objects. For proportional and switch control tasks no differences between groups were observed. The effect of test moment suggests a testing effect. For learning switch control, an overall improvement across groups was found in phasing of the co-contraction peaks. Importantly, individual differences were found in all analyses. Conclusion As improvements over test sessions were found, but no relevant differences between groups were revealed, we conclude that transfer effects from game training to actual prosthesis use did not take place. Task specificity nor training duration had effects on outcomes. Our results imply testing effects instead of transfer effects, in which individual differences played a significant role. How transfer from serious game training in upper limb prosthesis use can be enhanced, needs further attention.
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Affiliation(s)
- Bart Maas
- Department of Human Movement Sciences, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Corry K. Van Der Sluis
- Department of Rehabilitation Medicine, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Raoul M. Bongers
- Department of Human Movement Sciences, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
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Li W, Shi P, Li S, Yu H. Current status and clinical perspectives of extended reality for myoelectric prostheses: review. Front Bioeng Biotechnol 2024; 11:1334771. [PMID: 38260728 PMCID: PMC10800532 DOI: 10.3389/fbioe.2023.1334771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 12/13/2023] [Indexed: 01/24/2024] Open
Abstract
Training with "Extended Reality" or X-Reality (XR) systems can undoubtedly enhance the control of the myoelectric prostheses. However, there is no consensus on which factors improve the efficiency of skill transfer from virtual training to actual prosthesis abilities. This review examines the current status and clinical applications of XR in the field of myoelectric prosthesis training and analyses possible influences on skill migration. We have conducted a thorough search on databases in the field of prostheses using keywords such as extended reality, virtual reality and serious gaming. Our scoping review encompassed relevant applications, control methods, performance evaluation and assessment metrics. Our findings indicate that the implementation of XR technology for myoelectric rehabilitative training on prostheses provides considerable benefits. Additionally, there are numerous standardised methods available for evaluating training effectiveness. Recently, there has been a surge in the number of XR-based training tools for myoelectric prostheses, with an emphasis on user engagement and virtual training evaluation. Insufficient attention has been paid to significant limitations in the behaviour, functionality, and usage patterns of XR and myoelectric prostheses, potentially obstructing the transfer of skills and prospects for clinical application. Improvements are recommended in four critical areas: activities of daily living, training strategies, feedback, and the alignment of the virtual environment with the physical devices.
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Affiliation(s)
- Wei Li
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
- Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
- Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai, China
| | - Ping Shi
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
- Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
- Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai, China
| | - Sujiao Li
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
- Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
- Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai, China
| | - Hongliu Yu
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
- Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
- Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai, China
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Sparling T, Iyer L, Pasquina P, Petrus E. Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery. J Neurosci 2024; 44:e1051232024. [PMID: 38171645 PMCID: PMC10851691 DOI: 10.1523/jneurosci.1051-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/28/2023] [Accepted: 09/29/2023] [Indexed: 01/05/2024] Open
Abstract
Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.
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Affiliation(s)
- Tawnee Sparling
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Laxmi Iyer
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland 20817
| | - Paul Pasquina
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Emily Petrus
- Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, Maryland 20814
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Heerschop A, van der Sluis CK, Bongers RM. Training prosthesis users to switch between modes of a multi-articulating prosthetic hand. Disabil Rehabil 2024; 46:187-198. [PMID: 36541182 DOI: 10.1080/09638288.2022.2157055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE Producing triggers to switch between modes of myoelectric prosthetic hands has proven to be difficult. We evaluated whether digital training methods were feasible in individuals with an upper limb defect (ULD), whether myosignals in these individuals differ from those of non-impaired individuals and whether acquired skills transfer to prosthesis use. MATERIALS AND METHODS Two groups participated in a 9-day pre-test-post-test design study with seven 45-minute training sessions. One group trained using a serious game, the other with their myosignals digitally displayed. Both groups also trained using a prosthesis. The pre- and post-tests consisted of an adapted Clothespin Relocation Test and the spherical subset of the Southampton Hand Assessment Procedure. After the post-test, the System Usability Scale (SUS) was administered. Clinically relevant performance measures and myosignal features were analysed. RESULTS Four individuals with a ULD participated. SUS-scores deemed both training methods feasible. Three participants produced only a few correct triggers. Myosignals features indicated larger variability for individuals with a ULD compared to non-impaired individuals (previously published data [1]). Three participants indicated transfer of skill. CONCLUSIONS Even though both training methods were deemed feasible and most participants showed transfer, seven training sessions were insufficient to learn reliable switching behaviour.Trial registration: The study was approved by the medical ethics committee of the University Medical Center Groningen (METc 2018.268).Implications for rehabilitationSwitching between pre-programmed modes of a myoelectric prosthetic hand can be learned, however it does require training.Serious games can be considered useful training tools for trigger production in early phases of myoelectric prosthesis control training.In order to evoke transfer of skill from training to daily life both task-specificity and focus of attention during training should be taken into account.
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Affiliation(s)
- A Heerschop
- Department of Human Movement Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - C K van der Sluis
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - R M Bongers
- Department of Human Movement Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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Liu X, Zhang D, Miao K, Guo Y, Jiang X, Zhang X, Jia F, Tang H, Dai C. A Review on the Usability, Flexibility, Affinity, and Affordability of Virtual Technology for Rehabilitation Training of Upper Limb Amputees. Bioengineering (Basel) 2023; 10:1301. [PMID: 38002425 PMCID: PMC10669061 DOI: 10.3390/bioengineering10111301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/16/2023] [Accepted: 10/18/2023] [Indexed: 11/26/2023] Open
Abstract
(1) Background: Prosthetic rehabilitation is essential for upper limb amputees to regain their ability to work. However, the abandonment rate of prosthetics is higher than 50% due to the high cost of rehabilitation. Virtual technology shows potential for improving the availability and cost-effectiveness of prosthetic rehabilitation. This article systematically reviews the application of virtual technology for the prosthetic rehabilitation of upper limb amputees. (2) Methods: We followed PRISMA review guidance, STROBE, and CASP to evaluate the included articles. Finally, 17 articles were screened from 22,609 articles. (3) Results: This study reviews the possible benefits of using virtual technology from four aspects: usability, flexibility, psychological affinity, and long-term affordability. Three significant challenges are also discussed: realism, closed-loop control, and multi-modality integration. (4) Conclusions: Virtual technology allows for flexible and configurable control rehabilitation, both during hospital admissions and after discharge, at a relatively low cost. The technology shows promise in addressing the critical barrier of current prosthetic training issues, potentially improving the practical availability of prosthesis techniques for upper limb amputees.
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Affiliation(s)
- Xiangyu Liu
- College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai 200093, China; (X.L.); (K.M.)
| | - Di Zhang
- Department of Geriatrics, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China;
| | - Ke Miao
- College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai 200093, China; (X.L.); (K.M.)
| | - Yao Guo
- School of Information Science and Technology, Fudan University, Shanghai 200433, China;
| | - Xinyu Jiang
- School of Informatics, The University of Edinburgh, Edinburgh EH8 9AB, UK;
| | - Xi Zhang
- Department of Industrial Design, Hanyang University, Ansan 15586, Republic of Korea;
| | - Fumin Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Hao Tang
- College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai 200093, China; (X.L.); (K.M.)
| | - Chenyun Dai
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200241, China;
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Nazari V, Zheng YP. Controlling Upper Limb Prostheses Using Sonomyography (SMG): A Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:1885. [PMID: 36850483 PMCID: PMC9959820 DOI: 10.3390/s23041885] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/01/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
This paper presents a critical review and comparison of the results of recently published studies in the fields of human-machine interface and the use of sonomyography (SMG) for the control of upper limb prothesis. For this review paper, a combination of the keywords "Human Machine Interface", "Sonomyography", "Ultrasound", "Upper Limb Prosthesis", "Artificial Intelligence", and "Non-Invasive Sensors" was used to search for articles on Google Scholar and PubMed. Sixty-one articles were found, of which fifty-nine were used in this review. For a comparison of the different ultrasound modes, feature extraction methods, and machine learning algorithms, 16 articles were used. Various modes of ultrasound devices for prosthetic control, various machine learning algorithms for classifying different hand gestures, and various feature extraction methods for increasing the accuracy of artificial intelligence used in their controlling systems are reviewed in this article. The results of the review article show that ultrasound sensing has the potential to be used as a viable human-machine interface in order to control bionic hands with multiple degrees of freedom. Moreover, different hand gestures can be classified by different machine learning algorithms trained with extracted features from collected data with an accuracy of around 95%.
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Affiliation(s)
- Vaheh Nazari
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Yong-Ping Zheng
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong SAR, China
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Touillet A, Gouzien A, Badin M, Herbe P, Martinet N, Jarrassé N, Roby-Brami A. Kinematic analysis of impairments and compensatory motor behavior during prosthetic grasping in below-elbow amputees. PLoS One 2022; 17:e0277917. [PMID: 36399487 PMCID: PMC9674132 DOI: 10.1371/journal.pone.0277917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 11/06/2022] [Indexed: 11/19/2022] Open
Abstract
After a major upper limb amputation, the use of myoelectric prosthesis as assistive devices is possible. However, these prostheses remain quite difficult to control for grasping and manipulation of daily life objects. The aim of the present observational case study is to document the kinematics of grasping in a group of 10 below-elbow amputated patients fitted with a myoelectric prosthesis in order to describe and better understand their compensatory strategies. They performed a grasping to lift task toward 3 objects (a mug, a cylinder and a cone) placed at two distances within the reaching area in front of the patients. The kinematics of the trunk and upper-limb on the non-amputated and prosthetic sides were recorded with 3 electromagnetic Polhemus sensors placed on the hand, the forearm (or the corresponding site on the prosthesis) and the ipsilateral acromion. The 3D position of the elbow joint and the shoulder and elbow angles were calculated thanks to a preliminary calibration of the sensor position. We examined first the effect of side, distance and objects with non-parametric statistics. Prosthetic grasping was characterized by severe temporo-spatial impairments consistent with previous clinical or kinematic observations. The grasping phase was prolonged and the reaching and grasping components uncoupled. The 3D hand displacement was symmetrical in average, but with some differences according to the objects. Compensatory strategies involved the trunk and the proximal part of the upper-limb, as shown by a greater 3D displacement of the elbow for close target and a greater forward displacement of the acromion, particularly for far targets. The hand orientation at the time of grasping showed marked side differences with a more frontal azimuth, and a more "thumb-up" roll. The variation of hand orientation with the object on the prosthetic side, suggested that the lack of finger and wrist mobility imposed some adaptation of hand pose relative to the object. The detailed kinematic analysis allows more insight into the mechanisms of the compensatory strategies that could be due to both increased distal or proximal kinematic constraints. A better knowledge of those compensatory strategies is important for the prevention of musculoskeletal disorders and the development of innovative prosthetics.
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Affiliation(s)
- Amélie Touillet
- Louis Pierquin Centre of the Regional Institute of Rehabilitation, UGECAM Nord Est, Nancy, France
| | - Adrienne Gouzien
- Service de psychiatrie, Pôle Paris Centre, Hôpitaux de Saint-Maurice, Saint-Maurice, France
| | - Marina Badin
- Louis Pierquin Centre of the Regional Institute of Rehabilitation, UGECAM Nord Est, Nancy, France
| | - Pierrick Herbe
- Louis Pierquin Centre of the Regional Institute of Rehabilitation, UGECAM Nord Est, Nancy, France
| | - Noël Martinet
- Louis Pierquin Centre of the Regional Institute of Rehabilitation, UGECAM Nord Est, Nancy, France
| | - Nathanaël Jarrassé
- Institute of Intelligent Systems and Robotics (ISIR), UMR 7222, CNRS/INSERM, U1150 Agathe-ISIR, Sorbonne University, Paris, France
| | - Agnès Roby-Brami
- Institute of Intelligent Systems and Robotics (ISIR), UMR 7222, CNRS/INSERM, U1150 Agathe-ISIR, Sorbonne University, Paris, France
- * E-mail:
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Gaballa A, Cavalcante RS, Lamounier E, Soares A, Cabibihan JJ. Extended Reality "X-Reality" for Prosthesis Training of Upper-Limb Amputees: A Review on Current and Future Clinical Potential. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1652-1663. [PMID: 35635835 DOI: 10.1109/tnsre.2022.3179327] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The rejection rates of upper-limb prosthetic devices in adults are high, currently averaging 26% and 23% for body-powered and electric devices, respectively. While many factors influence acceptance, prosthesis training methods relying on novel virtual reality systems have been cited as a critical factor capable of increasing the likelihood of long-term, full-time use. Despite that, these implementations have not yet garnered widespread traction in the clinical setting, and their use remains immaterial. This review aims to explore the reasons behind this situation by identifying trends in existing research that seek to advance Extended Reality "X-Reality" systems for the sake of upper-limb prosthesis rehabilitation and, secondly, analyzing barriers and presenting potential pathways to deployment for successful adoption in the future. The search yielded 42 research papers that were divided into two categories. The first category included articles that focused on the technical aspect of virtual prosthesis training. Articles in the second category utilize user evaluation procedures to ensure applicability in a clinical environment. The review showed that 75% of articles that conducted whole system testing experimented with non-immersive virtual systems. Furthermore, there is a shortage of experiments performed with amputee subjects. From the large-scale studies analyzed, 71% of those recruited solely able-bodied participants. This paper shows that X-Reality technologies for prosthesis rehabilitation of upper-limb amputees carry significant benefits. Nevertheless, much still must be done so that the technology reaches widespread clinical use.
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Sinke M, Chadwell A, Smit G. State of the art of prosthesis simulators for the upper limb: A narrative review. Ann Phys Rehabil Med 2022; 65:101635. [PMID: 35091112 DOI: 10.1016/j.rehab.2022.101635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 11/09/2021] [Accepted: 11/11/2021] [Indexed: 10/18/2022]
Abstract
BACKGROUND Research into prosthesis training and design puts a burden on the small population of people with upper-limb absence who can participate in these studies. One solution is to use a prosthetic hand simulator, which allows for attaching a hand prosthesis to an intact limb. However, whether the results of prosthesis simulator studies can be translated to people with upper-limb absence using a hand prosthesis is unclear. OBJECTIVE To review the literature on prosthetic hand simulators, provide an overview of current designs, and highlight the differences and similarities between prosthesis simulators and traditional prostheses. METHODS A Boolean combination of keywords was used to search 3 electronic databases: PubMed, Scopus and Web of Science. Relevant articles in English were selected. RESULTS In total, 52 papers were included in the review, and an overview of the state of the art was presented. We identified the key differences between prosthesis simulators and traditional prostheses as the position of the terminal device and the available degrees of freedom of the arm and (prosthetic) wrist. CONCLUSIONS This paper provides an overview of prosthesis simulator designs over the past 27 years and an overview of the similarities and differences between prosthesis simulators and prostheses. The literature does not provide enough evidence to establish whether the results obtained from simulator studies could be translated to prostheses. A recommendation for future simulator design is to constrain pro- and supination of the forearm of anatomically intact participants and add a prosthetic wrist that can pro- and supinate. Additional research is required to find the ideal terminal device position for a prosthesis simulator with respect to the person's hand.
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Affiliation(s)
- Maaike Sinke
- BioMechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands
| | - Alix Chadwell
- Health Sciences Research Centre, University of Salford, Salford, M6 6PU, UK
| | - Gerwin Smit
- BioMechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands.
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Aydin T, Kesiktaş FN, Akbulut YD, Çorum M, Öneş K, Kizilkurt T, Buğdayci ND, Karacan I. The efficacy of robot-assisted training for patients with upper limb amputations who use myoelectric prostheses: a randomized controlled pilot study. Int J Rehabil Res 2022; 45:39-46. [PMID: 34775437 DOI: 10.1097/mrr.0000000000000506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
The aim of this pilot study was to investigate whether a movement therapy robot can improve skills in using a myoelectric prosthesis by patients with upper limb amputations. This prospective randomized, controlled study included a total of eleven patients with upper limb amputations who use myoelectric prostheses. The patients were randomized into a robot-assisted exercise group (n = 6) and a control group (n = 5). The robot group received robot-assisted training. No training program was provided to the control group. The outcome measure was kinematic data (A-goal hand-path ratio, A-goal deviation, A-goal instability and A-move) evaluated by the Armeo®Spring movement therapy robot. Significant improvements were noted in the A-goal hand-path ratio; A-goal deviation and A-goal instability in the robot group after treatment while compared with control group. No significant changes in A-move scores. We concluded that robot-assisted training may improve myoelectric prosthesis use skills in patients with upper limb amputation.
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Affiliation(s)
- Tuğba Aydin
- Istanbul Physical Medicine Rehabilitation Training and Research Hospital
| | - Fatma Nur Kesiktaş
- Istanbul Physical Medicine Rehabilitation Training and Research Hospital
| | | | - Mustafa Çorum
- Istanbul Physical Medicine Rehabilitation Training and Research Hospital
| | - Kadriye Öneş
- Istanbul Physical Medicine Rehabilitation Training and Research Hospital
| | - Taha Kizilkurt
- Orthopedics and Traumatology Department, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | | | - Ilhan Karacan
- Istanbul Physical Medicine Rehabilitation Training and Research Hospital
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11
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Wrist and finger motion recognition via M-mode ultrasound signal: A feasibility study. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103112] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Garske CA, Dyson M, Dupan S, Morgan G, Nazarpour K. Serious Games Are Not Serious Enough for Myoelectric Prosthetics. JMIR Serious Games 2021; 9:e28079. [PMID: 34747715 PMCID: PMC8663510 DOI: 10.2196/28079] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 06/09/2021] [Accepted: 08/25/2021] [Indexed: 02/07/2023] Open
Abstract
Serious games show a lot of potential for use in movement rehabilitation (eg, after a stroke, injury to the spinal cord, or limb loss). However, the nature of this research leads to diversity both in the background of the researchers and in the approaches of their investigation. Our close examination and categorization of virtual training software for upper limb prosthetic rehabilitation found that researchers typically followed one of two broad approaches: (1) focusing on the game design aspects to increase engagement and muscle training and (2) concentrating on an accurate representation of prosthetic training tasks, to induce task-specific skill transfer. Previous studies indicate muscle training alone does not lead to improved prosthetic control without a transfer-enabling task structure. However, the literature shows a recent surge in the number of game-based prosthetic training tools, which focus on engagement without heeding the importance of skill transfer. This influx appears to have been strongly influenced by the availability of both software and hardware, specifically the launch of a commercially available acquisition device and freely available high-profile game development engines. In this Viewpoint, we share our perspective on the current trends and progress of serious games for prosthetic training.
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Affiliation(s)
- Christian Alexander Garske
- Intelligent Sensing Laboratory, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Matthew Dyson
- Intelligent Sensing Laboratory, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sigrid Dupan
- Edinburgh Neuroprosthetics Laboratory, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Graham Morgan
- Networked and Ubiquitous Systems Engineering Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Kianoush Nazarpour
- Edinburgh Neuroprosthetics Laboratory, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
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Heerschop A, van der Sluis CK, Bongers RM. Transfer of mode switching performance: from training to upper-limb prosthesis use. J Neuroeng Rehabil 2021; 18:85. [PMID: 34022945 PMCID: PMC8141154 DOI: 10.1186/s12984-021-00878-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 05/11/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Current myoelectric prostheses are multi-articulated and offer multiple modes. Switching between modes is often done through pre-defined myosignals, so-called triggers, of which the training hardly is studied. We evaluated if switching skills trained without using a prosthesis transfer to actual prosthesis use and whether the available feedback during training influences this transfer. Furthermore we examined which clinically relevant performance measures and which myosignal features were adapted during training. METHODS Two experimental groups and one control group participated in a five day pre-test-post-test design study. Both experimental groups used their myosignals to perform a task. One group performed a serious game without seeing their myosignals, the second group was presented their myosignal on a screen. The control group played the serious game using the touchpad of the laptop. Each training session lasted 15 min. The pre- and post-test were identical for all groups and consisted of performing a task with an actual prosthesis, where switches had to be produced to change grip mode to relocate clothespins. Both clinically relevant performance measures and myosignal features were analysed. RESULTS 10 participants trained using the serious game, 10 participants trained with the visual myosignal and 8 the control task. All participants were unimpaired. Both experimental groups showed significant transfer of skill from training to prosthesis use, the control group did not. The degree of transfer did not differ between the two training groups. Clinically relevant measure 'accuracy' and feature of the myosignals 'variation in phasing' changed during training. CONCLUSIONS Training switching skills appeared to be successful. The skills trained in the game transferred to performance in a functional task. Learning switching skills is independent of the type of feedback used during training. Outcome measures hardly changed during training and further research is needed to explain this. It should be noted that five training sessions did not result in a level of performance needed for actual prosthesis use. Trial registration The study was approved by the local ethics committee (ECB 2014.02.28_1) and was included in the Dutch trial registry (NTR5876).
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Affiliation(s)
- Anniek Heerschop
- Department of Human Movement Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Corry K. van der Sluis
- Department of Rehabilitation Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Raoul M. Bongers
- Department of Human Movement Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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14
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Kristoffersen MB, Franzke AW, Bongers RM, Wand M, Murgia A, van der Sluis CK. User training for machine learning controlled upper limb prostheses: a serious game approach. J Neuroeng Rehabil 2021; 18:32. [PMID: 33579326 PMCID: PMC7881655 DOI: 10.1186/s12984-021-00831-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 01/26/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Upper limb prosthetics with multiple degrees of freedom (DoFs) are still mostly operated through the clinical standard Direct Control scheme. Machine learning control, on the other hand, allows controlling multiple DoFs although it requires separable and consistent electromyogram (EMG) patterns. Whereas user training can improve EMG pattern quality, conventional training methods might limit user potential. Training with serious games might lead to higher quality EMG patterns and better functional outcomes. In this explorative study we compare outcomes of serious game training with conventional training, and machine learning control with the users' own one DoF prosthesis. METHODS Participants with upper limb absence participated in 7 training sessions where they learned to control a 3 DoF prosthesis with two grips which was fitted. Participants received either game training or conventional training. Conventional training was based on coaching, as described in the literature. Game-based training was conducted using two games that trained EMG pattern separability and functional use. Both groups also trained functional use with the prosthesis donned. The prosthesis system was controlled using a neural network regressor. Outcome measures were EMG metrics, number of DoFs used, the spherical subset of the Southampton Hand Assessment Procedure and the Clothespin Relocation Test. RESULTS Eight participants were recruited and four completed the study. Training did not lead to consistent improvements in EMG pattern quality or functional use, but some participants improved in some metrics. No differences were observed between the groups. Participants achieved consistently better results using their own prosthesis than the machine-learning controlled prosthesis used in this study. CONCLUSION Our explorative study showed in a small group of participants that serious game training seems to achieve similar results as conventional training. No consistent improvements were found in either group in terms of EMG metrics or functional use, which might be due to insufficient training. This study highlights the need for more research in user training for machine learning controlled prosthetics. In addition, this study contributes with more data comparing machine learning controlled prosthetics with Direct Controlled prosthetics.
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Affiliation(s)
- Morten B Kristoffersen
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.
| | - Andreas W Franzke
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Raoul M Bongers
- Department of Human Movement Sciences, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | | | - Alessio Murgia
- Department of Human Movement Sciences, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Corry K van der Sluis
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
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15
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Chadwell A, Kenney L, Thies S, Head J, Galpin A, Baker R. Addressing unpredictability may be the key to improving performance with current clinically prescribed myoelectric prostheses. Sci Rep 2021; 11:3300. [PMID: 33558547 PMCID: PMC7870859 DOI: 10.1038/s41598-021-82764-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 12/17/2020] [Indexed: 11/29/2022] Open
Abstract
The efferent control chain for an upper-limb myoelectric prosthesis can be separated into 3 key areas: signal generation, signal acquisition, and device response. Data were collected from twenty trans-radial myoelectric prosthesis users using their own clinically prescribed devices, to establish the relative impact of these potential control factors on user performance (user functionality and everyday prosthesis usage). By identifying the key factor(s), we can guide future developments to ensure clinical impact. Skill in generating muscle signals was assessed via reaction times and signal tracking. To assess the predictability of signal acquisition, we inspected reaction time spread and undesired hand activations. As a measure of device response, we recorded the electromechanical delay between electrode stimulation and the onset of hand movement. Results suggest abstract measures of skill in controlling muscle signals are poorly correlated with performance. Undesired activations of the hand or incorrect responses were correlated with almost all kinematics and gaze measures suggesting unpredictability is a key factor. Significant correlations were also found between several measures of performance and the electromechanical delay; however, unexpectedly, longer electromechanical delays correlated with better performance. Future research should focus on exploring causes of unpredictability, their relative impacts on performance and interventions to address this.
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Affiliation(s)
- A Chadwell
- Centre for Health Sciences Research, University of Salford, Salford, UK.
| | - L Kenney
- Centre for Health Sciences Research, University of Salford, Salford, UK
| | - S Thies
- Centre for Health Sciences Research, University of Salford, Salford, UK
| | - J Head
- Centre for Health Sciences Research, University of Salford, Salford, UK
| | - A Galpin
- Centre for Health Sciences Research, University of Salford, Salford, UK
| | - R Baker
- Salford Business School, University of Salford, Salford, UK
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16
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Garske CA, Dyson M, Dupan S, Nazarpour K. Perception of Game-Based Rehabilitation in Upper Limb Prosthetic Training: Survey of Users and Researchers. JMIR Serious Games 2021; 9:e23710. [PMID: 33522975 PMCID: PMC7884217 DOI: 10.2196/23710] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/17/2020] [Accepted: 11/26/2020] [Indexed: 12/16/2022] Open
Abstract
Background Serious games have been investigated for their use in multiple forms of rehabilitation for decades. The rising trend to use games for physical fitness in more recent years has also provided more options and garnered more interest for their use in physical rehabilitation and motor learning. In this study, we report the results of an opinion survey of serious games in upper limb prosthetic training. Objective This study investigates and contrasts the expectations and preferences for game-based prosthetic rehabilitation of people with limb difference and researchers. Methods Both participant groups answered open and closed questions as well as a questionnaire to assess their user types. The distribution of the user types was compared with a Pearson chi-square test against a sample population. The data were analyzed using the thematic framework method; answers fell within the themes of usability, training, and game design. Researchers shared their views on current challenges and what could be done to tackle these. Results A total of 14 people with limb difference and 12 researchers participated in this survey. The open questions resulted in an overview of the different views on prosthetic training games between the groups. The user types of people with limb difference and researchers were both significantly different from the sample population, with χ25=12.3 and χ25=26.5, respectively. Conclusions We found that the respondents not only showed a general willingness and tentative optimism toward the topic but also acknowledged hurdles limiting the adoption of these games by both clinics and users. The results indicate a noteworthy difference between researchers and people with limb difference in their game preferences, which could lead to design choices that do not represent the target audience. Furthermore, focus on long-term in-home experiments is expected to shed more light on the validity of games in upper limb prosthetic rehabilitation.
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Affiliation(s)
- Christian Alexander Garske
- Intelligent Sensing Laboratory, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Matthew Dyson
- Intelligent Sensing Laboratory, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sigrid Dupan
- Edinburgh Neuroprosthetics Laboratory, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Kianoush Nazarpour
- Edinburgh Neuroprosthetics Laboratory, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
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17
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Kristoffersen MB, Franzke AW, van der Sluis CK, Murgia A, Bongers RM. Serious gaming to generate separated and consistent EMG patterns in pattern-recognition prosthesis control. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2020.102140] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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18
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Nelson AJ, Hall PT, Saul KR, Crouch DL. Effect of Mechanically Passive, Wearable Shoulder Exoskeletons on Muscle Output During Dynamic Upper Extremity Movements: A Computational Simulation Study. J Appl Biomech 2020; 36:59-67. [PMID: 31968306 DOI: 10.1123/jab.2018-0369] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 12/12/2019] [Accepted: 12/12/2019] [Indexed: 10/27/2023]
Abstract
Wearable passive (ie, spring powered) shoulder exoskeletons could reduce muscle output during motor tasks to help prevent or treat shoulder musculoskeletal disorders. However, most wearable passive shoulder exoskeletons have been designed and evaluated for static tasks, so it is unclear how they affect muscle output during dynamic tasks. The authors used a musculoskeletal model and Computed Muscle Control optimization to estimate muscle output with and without a wearable passive shoulder exoskeleton during 2 simulated dynamic tasks: abduction and upward reach. To an existing upper extremity musculoskeletal model, the authors added an exoskeleton model with 3-dimensional representations of the exoskeleton components, including a spring, cam wheel, force-transmitting shoulder cable, and wrapping surfaces that permitted the shoulder cable to wrap over the shoulder. The exoskeleton reduced net muscle-generated moments in positive shoulder elevation by 28% and 62% during the abduction and upward reach, respectively. However, muscle outputs (joint moments and muscle effort) were higher with the exoskeleton than without at some points of the movement. Muscle output was higher with the exoskeleton because the exoskeleton moment opposed the muscle-generated moment in some postures. The results of this study highlight the importance of evaluating muscle output for passive exoskeletons designed to support dynamic movements to ensure that the exoskeletons assist, rather than impede, movement.
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Affiliation(s)
- Allison J Nelson
- University of Tennessee
- Virginia Polytechnic Institute and State University
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19
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Heerschop A, van der Sluis CK, Otten E, Bongers RM. Performance among different types of myocontrolled tasks is not related. Hum Mov Sci 2020; 70:102592. [PMID: 32217210 DOI: 10.1016/j.humov.2020.102592] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Revised: 12/23/2019] [Accepted: 02/08/2020] [Indexed: 01/08/2023]
Abstract
Studies on myocontrolled assistive technology (AT), such as myoelectric prostheses, as well as rehabilitation practice using myoelectric controlled interfaces, commonly assume the existence of a general myocontrol skill. This is the skill to control myosignals in such a way that they are employable in multiple tasks. If this skill exists, training any myocontrolled task using a certain set of muscles would improve the use of myocontrolled AT when the AT is controlled using these muscles. We examined whether a general myocontrol skill exists in myocontrolled tasks with and without a prosthesis. Unimpaired, right-handed adults used the sEMG of wrist flexors and extensors to perform several tasks in two experiments. In Experiment 1, twelve participants trained a myoelectric prosthesis-simulator task and a myocontrolled serious game for five consecutive days. Performance was compared between tasks and over the course of the training period. In Experiment 2, thirty-one participants performed five myocontrolled tasks consisting of two serious games, two prosthesis-simulator tasks and one digital signal matching task. All tasks were based on tasks currently used in clinical practice or research settings. Kendall rank correlation coefficients were computed to analyze correlations between the performance on different tasks. In Experiment 1 performance on the tasks showed no correlation for multiple outcome measures. Rankings within tasks did not change over the training period. In Experiment 2 performance did not correlate between any of the tasks. Since performance between different tasks did not correlate, results suggest that a general myocontrol skill does not exist and that each myocontrolled task requires a specific skill. Generalization of those findings to amputees using AT should be done with caution since in both experiments unimpaired participants were included. Moreover, training duration in Experiment 2 was short. Our findings indicate that training and assessment methods for myocontrolled AT use should focus on tasks frequently performed in daily life by the individual using the AT instead of merely focusing on training myosignals.
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Affiliation(s)
- Anniek Heerschop
- University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Groningen, the Netherlands.
| | - Corry K van der Sluis
- University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Groningen, the Netherlands.
| | - Egbert Otten
- University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Groningen, the Netherlands.
| | - Raoul M Bongers
- University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Groningen, the Netherlands.
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20
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Heerschop A, van der Sluis CK, Otten E, Bongers RM. Looking beyond proportional control: The relevance of mode switching in learning to operate multi-articulating myoelectric upper-limb prostheses. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2019.101647] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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21
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Pan L, Crouch DL, Huang H. Comparing EMG-Based Human-Machine Interfaces for Estimating Continuous, Coordinated Movements. IEEE Trans Neural Syst Rehabil Eng 2019; 27:2145-2154. [PMID: 31478862 DOI: 10.1109/tnsre.2019.2937929] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Electromyography (EMG)-based interfaces are trending toward continuous, simultaneous control with multiple degrees of freedom. Emerging methods range from data-driven approaches to biomechanical model-based methods. However, there has been no direct comparison between these two types of continuous EMG-based interfaces. The aim of this study was to compare a musculoskeletal model (MM) with two data-driven approaches, linear regression (LR) and artificial neural network (ANN), for predicting continuous wrist and hand motions for EMG-based interfaces. Six able-bodied subjects and one transradial amputee subject performed (missing) metacarpophalangeal (MCP) and wrist flexion/extension, simultaneously or independently, while four EMG signals were recorded from forearm muscles. To add variation to the EMG signals, the subjects repeated the MCP and wrist motions at various upper extremity postures. For each subject, the EMG signals collected from the neutral posture were used to build the EMG interfaces; the EMG signals collected from all postures were used to evaluate the interfaces. The performance of the interface was quantified by Pearson's correlation coefficient (r) and the normalized root mean square error (NRMSE) between measured and estimated joint angles. The results demonstrated that the MM predicted movements more accurately, with higher r values and lower NRMSE, than either LR or ANN. Similar results were observed in the transradial amputee. Additionally, the variation in r across postures, an indicator of reliability against posture changes, was significantly lower (better) for the MM than for either LR or ANN. Our findings suggest that incorporating musculoskeletal knowledge into EMG-based human-machine interfaces could improve the estimation of continuous, coordinated motion.
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Proprioceptive Sonomyographic Control: A novel method for intuitive and proportional control of multiple degrees-of-freedom for individuals with upper extremity limb loss. Sci Rep 2019; 9:9499. [PMID: 31263115 PMCID: PMC6602937 DOI: 10.1038/s41598-019-45459-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 06/05/2019] [Indexed: 11/17/2022] Open
Abstract
Technological advances in multi-articulated prosthetic hands have outpaced the development of methods to intuitively control these devices. In fact, prosthetic users often cite "difficulty of use" as a key contributing factor for abandoning their prostheses. To overcome the limitations of the currently pervasive myoelectric control strategies, namely unintuitive proportional control of multiple degrees-of-freedom, we propose a novel approach: proprioceptive sonomyographiccontrol. Unlike myoelectric control strategies which measure electrical activation of muscles and use the extracted signals to determine the velocity of an end-effector; our sonomyography-based strategy measures mechanical muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Therefore, our sonomyography-based control is congruent with a prosthetic user’s innate proprioception of muscle deformation in the residual limb. In this work, we evaluated proprioceptive sonomyographic control with 5 prosthetic users and 5 able-bodied participants in a virtual target achievement and holding task for 5 different hand motions. We observed that with limited training, the performance of prosthetic users was comparable to that of able-bodied participants and thus conclude that proprioceptive sonomyographic control is a robust and intuitive prosthetic control strategy.
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23
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Roche AD, Lakey B, Mendez I, Vujaklija I, Farina D, Aszmann OC. Clinical Perspectives in Upper Limb Prostheses: An Update. CURRENT SURGERY REPORTS 2019. [DOI: 10.1007/s40137-019-0227-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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24
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Prahm C, Kayali F, Sturma A, Aszmann O. PlayBionic: Game-Based Interventions to Encourage Patient Engagement and Performance in Prosthetic Motor Rehabilitation. PM R 2018; 10:1252-1260. [DOI: 10.1016/j.pmrj.2018.09.027] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Revised: 07/25/2018] [Accepted: 09/13/2018] [Indexed: 11/25/2022]
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25
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Perry BN, Armiger RS, Yu KE, Alattar AA, Moran CW, Wolde M, McFarland K, Pasquina PF, Tsao JW. Virtual Integration Environment as an Advanced Prosthetic Limb Training Platform. Front Neurol 2018; 9:785. [PMID: 30459696 PMCID: PMC6232892 DOI: 10.3389/fneur.2018.00785] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2018] [Accepted: 08/30/2018] [Indexed: 11/13/2022] Open
Abstract
Background: Despite advances in prosthetic development and neurorehabilitation, individuals with upper extremity (UE) loss continue to face functional and psychosocial challenges following amputation. Recent advanced myoelectric prostheses offer intuitive control over multiple, simultaneous degrees of motion and promise sensory feedback integration, but require complex training to effectively manipulate. We explored whether a virtual reality simulator could be used to teach dexterous prosthetic control paradigms to individuals with UE loss. Methods: Thirteen active-duty military personnel with UE loss (14 limbs) completed twenty, 30-min passive motor training sessions over 1-2 months. Participants were asked to follow the motions of a virtual avatar using residual and phantom limbs, and electrical activity from the residual limb was recorded using surface electromyography. Eight participants (nine limbs), also completed twenty, 30-min active motor training sessions. Participants controlled a virtual avatar through three motion sets of increasing complexity (Basic, Advanced, and Digit) and were scored on how accurately they performed requested motions. Score trajectory was assessed as a function of time using longitudinal mixed effects linear regression. Results: Mean classification accuracy for passive motor training was 43.8 ± 10.7% (14 limbs, 277 passive sessions). In active motor sessions, >95% classification accuracy (which we used as the threshold for prosthetic acceptance) was achieved by all participants for Basic sets and by 50% of participants in Advanced and Digit sets. Significant improvement in active motor scores over time was observed in Basic and Advanced sets (per additional session: β-coefficient 0.125, p = 0.022; β-coefficient 0.45, p = 0.001, respectively), and trended toward significance for Digit sets (β-coefficient 0.594, p = 0.077). Conclusions: These results offer robust evidence that a virtual reality training platform can be used to quickly and efficiently train individuals with UE loss to operate advanced prosthetic control paradigms. Participants can be trained to generate muscle contraction patterns in residual limbs that are interpreted with high accuracy by computer software as distinct active motion commands. These results support the potential viability of advanced myoelectric prostheses relying on pattern recognition feedback or similar controls systems.
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Affiliation(s)
- Briana N Perry
- Walter Reed National Military Medical Center, Bethesda, MD, United States
| | - Robert S Armiger
- Applied Physics Laboratory, Johns Hopkins University, Laurel, MD, United States
| | - Kristin E Yu
- Henry M. Jackson Foundation, Bethesda, MD, United States
| | - Ali A Alattar
- School of Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Courtney W Moran
- Applied Physics Laboratory, Johns Hopkins University, Laurel, MD, United States
| | - Mikias Wolde
- Walter Reed National Military Medical Center, Bethesda, MD, United States
| | - Kayla McFarland
- Walter Reed National Military Medical Center, Bethesda, MD, United States
| | - Paul F Pasquina
- Walter Reed National Military Medical Center, Bethesda, MD, United States.,Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Jack W Tsao
- Walter Reed National Military Medical Center, Bethesda, MD, United States.,Uniformed Services University of the Health Sciences, Bethesda, MD, United States.,University of Tennessee Health Science Center, Memphis, TN, United States
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26
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Hargrove L, Miller L, Turner K, Kuiken T. Control within a virtual environment is correlated to functional outcomes when using a physical prosthesis. J Neuroeng Rehabil 2018; 15:60. [PMID: 30255800 PMCID: PMC6157245 DOI: 10.1186/s12984-018-0402-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Background Advances such as targeted muscle reinnervation and pattern recognition control may provide improved control of upper limb myoelectric prostheses, but evaluating user function remains challenging. Virtual environments are cost-effective and immersive tools that are increasingly used to provide practice and evaluate prosthesis control, but the relationship between virtual and physical outcomes—i.e., whether practice in a virtual environment translates to improved physical performance—is not understood. Methods Nine people with transhumeral amputations who previously had targeted muscle reinnervation surgery were fitted with a myoelectric prosthesis comprising a commercially available elbow, wrist, terminal device, and pattern recognition control system. Virtual and physical outcome measures were obtained before and after a 6-week home trial of the prosthesis. Results After the home trial, subjects showed statistically significant improvements (p < 0.05) in offline classification error, the virtual Target Achievement Control test, and the physical Southampton Hand Assessment Procedure and Box and Blocks Test. A trend toward improvement was also observed in the physical Clothespin Relocation task and Jebsen-Taylor test; however, these changes were not statistically significant. The median completion time in the virtual test correlated strongly and significantly with the Southampton Hand Assessment Procedure (p = 0.05, R = − 0.86), Box and Blocks Test (p = 0.007, R = − 0.82), Jebsen-Taylor Test (p = 0.003, R = 0.87), and the Assessment of Capacity for Myoelectric Control (p = 0.005,R = − 0.85). The classification error performance only had a significant correlation with the Clothespin Relocation Test (p = 0.018, R = .76). Conclusions In-home practice with a pattern recognition-controlled prosthesis improves functional control, as measured by both virtual and physical outcome measures. However, virtual measures need to be validated and standardized to ensure reliability in a clinical or research setting. Trial registration This is a registered clinical trial: NCT03097978.
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Affiliation(s)
- Levi Hargrove
- Shirley Ryan AbilityLab, 355 E. Erie Street, Chicago, IL, 60611, USA. .,Departments of Physical Medicine and Rehabilitation and Biomedical Engineering, Northwestern University, 663 Clark St, Evanston, IL, 60208, USA.
| | - Laura Miller
- Shirley Ryan AbilityLab, 355 E. Erie Street, Chicago, IL, 60611, USA.,Departments of Physical Medicine and Rehabilitation and Biomedical Engineering, Northwestern University, 663 Clark St, Evanston, IL, 60208, USA
| | - Kristi Turner
- Shirley Ryan AbilityLab, 355 E. Erie Street, Chicago, IL, 60611, USA
| | - Todd Kuiken
- Shirley Ryan AbilityLab, 355 E. Erie Street, Chicago, IL, 60611, USA.,Departments of Physical Medicine and Rehabilitation and Biomedical Engineering, Northwestern University, 663 Clark St, Evanston, IL, 60208, USA
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Tabor A, Bateman S, Scheme E. Evaluation of Myoelectric Control Learning Using Multi-Session Game-Based Training. IEEE Trans Neural Syst Rehabil Eng 2018; 26:1680-1689. [PMID: 30010580 DOI: 10.1109/tnsre.2018.2855561] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
While training is critical for ensuring initial success as well as continued adoption of a myoelectric powered prosthesis, relatively little is known about the amount of training that is necessary. In previous studies, participants have completed only a small number of sessions, leaving doubt about whether the findings necessarily generalize to a longer-term clinical training program. Furthermore, a heavy emphasis has been placed on a functional prosthesis use when assessing the effectiveness of myoelectric training. Although well-motivated, this all-inclusive approach may obscure more subtle improvements made in underlying muscle control that could lead to tangible benefits. In this paper, a deeper exploration of the effects of myoelectric training was performed by following the progress of 30 participants as they completed a series of ten 30-min training sessions over multiple days. The progress was assessed using a newly developed set of metrics that was specifically designed to quantify the aspects of muscle control that are foundational to the strong myoelectric prosthesis use. It was determined that, while myoelectric training can lead to improvements in muscle control, these improvements may take longer than previously considered, even occurring after improvements in the training game itself. These results suggest the need to reconsider how and when transfer from training activities is assessed.
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van Dijk L, Heerschop A, van der Sluis CK, Bongers RM. The Anatomy of Action Systems: Task Differentiation When Learning an EMG Controlled Game. Front Psychol 2016; 7:1945. [PMID: 28018278 PMCID: PMC5156961 DOI: 10.3389/fpsyg.2016.01945] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Accepted: 11/28/2016] [Indexed: 11/21/2022] Open
Abstract
This study aims to determine to what extent the task for an action system in its initial development relies on functional and anatomical components. Fifty-two able-bodied participants were randomly assigned to one of three experimental groups or to a control group. As a pre- and post-test all groups performed a computer game with the same goal and using the same musculature. One experimental group also trained to perform this test, while the other two experimental groups learned to perform a game that differed either in its goal or in the musculature used. The observed change in accuracy indicated that retaining the goal of the task or the musculature used equally increased transfer performance relative to controls. Conversely, changing either the goal or the musculature equally decreased transfer relative to training the test. These results suggest that in the initial development of an action system, the task to which the system pertains is not specified solely by either the goal of the task or the anatomical structures involved. It is suggested that functional specificity and anatomical dependence might equally be outcomes of continuously differentiating activity.
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Affiliation(s)
- Ludger van Dijk
- Center for Human Movement Sciences, University of Groningen - University Medical Center Groningen Groningen, Netherlands
| | - Anniek Heerschop
- Center for Human Movement Sciences, University of Groningen - University Medical Center Groningen Groningen, Netherlands
| | - Corry K van der Sluis
- Department of Rehabilitation Medicine, University of Groningen - University Medical Center Groningen Groningen, Netherlands
| | - Raoul M Bongers
- Center for Human Movement Sciences, University of Groningen - University Medical Center Groningen Groningen, Netherlands
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29
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van Dijk L, van der Sluis CK, van Dijk HW, Bongers RM. Learning an EMG Controlled Game: Task-Specific Adaptations and Transfer. PLoS One 2016; 11:e0160817. [PMID: 27556154 PMCID: PMC4996424 DOI: 10.1371/journal.pone.0160817] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Accepted: 07/26/2016] [Indexed: 11/18/2022] Open
Abstract
Video games that aim to improve myoelectric control (myogames) are gaining popularity and are often part of the rehabilitation process following an upper limb amputation. However, direct evidence for their effect on prosthetic skill is limited. This study aimed to determine whether and how myogaming improves EMG control and whether performance improvements transfer to a prosthesis-simulator task. Able-bodied right-handed participants (N = 28) were randomly assigned to 1 of 2 groups. The intervention group was trained to control a video game (Breakout-EMG) using the myosignals of wrist flexors and extensors. Controls played a regular Mario computer game. Both groups trained 20 minutes a day for 4 consecutive days. Before and after training, two tests were conducted: one level of the Breakout-EMG game, and grasping objects with a prosthesis-simulator. Results showed a larger increase of in-game accuracy for the Breakout-EMG group than for controls. The Breakout-EMG group moreover showed increased adaptation of the EMG signal to the game. No differences were found in using a prosthesis-simulator. This study demonstrated that myogames lead to task-specific myocontrol skills. Transfer to a prosthesis task is therefore far from easy. We discuss several implications for future myogame designs.
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Affiliation(s)
- Ludger van Dijk
- University of Groningen, University Medical Center Groningen, Center for Human Movement Science, Groningen, The Netherlands
| | - Corry K. van der Sluis
- University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Groningen, The Netherlands
| | - Hylke W. van Dijk
- NHL University of Applied Sciences,Faculty of Engineering, Serious Gaming Group, Leeuwarden, The Netherlands
| | - Raoul M. Bongers
- University of Groningen, University Medical Center Groningen, Center for Human Movement Science, Groningen, The Netherlands
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