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Xiao Y, Bai H, Gao Y, Hu B, Zheng J, Cai X, Rao J, Li X, Hao A. Interactive Virtual Ankle Movement Controlled by Wrist sEMG Improves Motor Imagery: An Exploratory Study. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2024; 30:5507-5524. [PMID: 37432832 DOI: 10.1109/tvcg.2023.3294342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/13/2023]
Abstract
Virtual reality (VR) techniques can significantly enhance motor imagery training by creating a strong illusion of action for central sensory stimulation. In this article, we establish a precedent by using surface electromyography (sEMG) of contralateral wrist movement to trigger virtual ankle movement through an improved data-driven approach with a continuous sEMG signal for fast and accurate intention recognition. Our developed VR interactive system can provide feedback training for stroke patients in the early stages, even if there is no active ankle movement. Our objectives are to evaluate: 1) the effects of VR immersion mode on body illusion, kinesthetic illusion, and motor imagery performance in stroke patients; 2) the effects of motivation and attention when utilizing wrist sEMG as a trigger signal for virtual ankle motion; 3) the acute effects on motor function in stroke patients. Through a series of well-designed experiments, we have found that, compared to the 2D condition, VR significantly increases the degree of kinesthetic illusion and body ownership of the patients, and improves their motor imagery performance and motor memory. When compared to conditions without feedback, using contralateral wrist sEMG signals as trigger signals for virtual ankle movement enhances patients' sustained attention and motivation during repetitive tasks. Furthermore, the combination of VR and feedback has an acute impact on motor function. Our exploratory study suggests that the sEMG-based immersive virtual interactive feedback provides an effective option for active rehabilitation training for severe hemiplegia patients in the early stages, with great potential for clinical application.
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Li X, Zeng H, Li Y, Song A. Quantitative Assessment via Multi-Domain Fusion of Muscle Synergy Associated With Upper-Limb Motor Function for Stroke Rehabilitation. IEEE Trans Biomed Eng 2024; 71:1430-1441. [PMID: 38051628 DOI: 10.1109/tbme.2023.3339634] [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: 12/07/2023]
Abstract
Quantitative assessment of upper limb motor function aids therapists in providing appropriate rehabilitation strategies, which plays an essential role in post-stroke rehabilitation. Traditional assessments, relying on clinical scales or kinematic metrics, often involve subjective scores or are influenced by compensatory strategies. Recently, the use of muscle synergies, representing simplified neuromuscular control, has emerged as a promising approach for post-stroke assessment. In general, muscle synergies are decomposed into two components: synergy vectors and synergy activation. Synergy vectors represent the relative weighting of each muscle within each synergy, that is muscle coordination; synergy activation represents the recruitment of the muscle synergy over time, that is muscle activation strength. Both components are vital for adequately assessing patients' motor function. Therefore, we integrate the spatial domain and temporal domain features extracted from synergy vectors and synergy activation, constructing a multi-domain assessment system using a Random Forest classifier, which may provide great qualitative classification accuracy. Furthermore, a novel functional score is generated from the probabilities belonging to the pathological group. Finally, A study involving ten healthy subjects and ten post-stroke patients validates the proposed method. The experimental results show that the classification accuracy was enhanced to 98.56% by fusing the characteristics derived from different domains, which was higher than that based on spatial domain (94.90%) and temporal domain (91.08%), respectively. Furthermore, the assessment score generated by multi-domain fusion framework exhibited a significant correlation with the clinical score. These promising results show the potential of applying the proposed method to clinical assessments for post-stroke patients.
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Seo G, Park JH, Park HS, Roh J. Developing new intermuscular coordination patterns through an electromyographic signal-guided training in the upper extremity. J Neuroeng Rehabil 2023; 20:112. [PMID: 37658406 PMCID: PMC10474681 DOI: 10.1186/s12984-023-01236-2] [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: 04/13/2023] [Accepted: 08/16/2023] [Indexed: 09/03/2023] Open
Abstract
BACKGROUND Muscle synergies, computationally identified intermuscular coordination patterns, have been utilized to characterize neuromuscular control and learning in humans. However, it is unclear whether it is possible to alter the existing muscle synergies or develop new ones in an intended way through a relatively short-term motor exercise in adulthood. This study aimed to test the feasibility of expanding the repertoire of intermuscular coordination patterns through an isometric, electromyographic (EMG) signal-guided exercise in the upper extremity (UE) of neurologically intact individuals. METHODS 10 participants were trained for six weeks to induce independent control of activating a pair of elbow flexor muscles that tended to be naturally co-activated in force generation. An untrained isometric force generation task was performed to assess the effect of the training on the intermuscular coordination of the trained UE. We applied a non-negative matrix factorization on the EMG signals recorded from 12 major UE muscles during the assessment to identify the muscle synergies. In addition, the performance of training tasks and the characteristics of individual muscles' activity in both time and frequency domains were quantified as the training outcomes. RESULTS Typically, in two weeks of the training, participants could use newly developed muscle synergies when requested to perform new, untrained motor tasks by activating their UE muscles in the trained way. Meanwhile, their habitually expressed muscle synergies, the synergistic muscle activation groups that were used before the training, were conserved throughout the entire training period. The number of muscle synergies activated for the task performance remained the same. As the new muscle synergies were developed, the neuromotor control of the trained muscles reflected in the metrics, such as the ratio between the targeted muscles, number of matched targets, and task completion time, was improved. CONCLUSION These findings suggest that our protocol can increase the repertoire of readily available muscle synergies and improve motor control by developing the activation of new muscle coordination patterns in healthy adults within a relatively short period. Furthermore, the study shows the potential of the isometric EMG-guided protocol as a neurorehabilitation tool for aiming motor deficits induced by abnormal intermuscular coordination after neurological disorders. TRIAL REGISTRATION This study was registered at the Clinical Research Information Service (CRiS) of the Korea National Institute of Health (KCT0005803) on 1/22/2021.
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Affiliation(s)
- Gang Seo
- Department of Biomedical Engineering, Cullen College of Engineering, University of Houston, Houston, TX, USA
| | - Jeong-Ho Park
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, South Korea
| | - Hyung-Soon Park
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, South Korea.
| | - Jinsook Roh
- Department of Biomedical Engineering, Cullen College of Engineering, University of Houston, Houston, TX, USA.
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Wang J, Cao D, Li Y, Wang J, Wu Y. Multi-user motion recognition using sEMG via discriminative canonical correlation analysis and adaptive dimensionality reduction. Front Neurorobot 2022; 16:997134. [PMID: 36386392 PMCID: PMC9650084 DOI: 10.3389/fnbot.2022.997134] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/06/2022] [Indexed: 03/23/2024] Open
Abstract
The inability of new users to adapt quickly to the surface electromyography (sEMG) interface has greatly hindered the development of sEMG in the field of rehabilitation. This is due mainly to the large differences in sEMG signals produced by muscles when different people perform the same motion. To address this issue, a multi-user sEMG framework is proposed, using discriminative canonical correlation analysis and adaptive dimensionality reduction (ADR). The interface projects the feature sets for training users and new users into a low-dimensional uniform style space, overcoming the problem of individual differences in sEMG. The ADR method removes the redundant information in sEMG features and improves the accuracy of system motion recognition. The presented framework was validated on eight subjects with intact limbs, with an average recognition accuracy of 92.23% in 12 categories of upper-limb movements. In rehabilitation laboratory experiments, the average recognition rate reached 90.52%. The experimental results suggest that the framework offers a good solution to enable new rehabilitation users to adapt quickly to the sEMG interface.
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Affiliation(s)
| | - Dianguo Cao
- School of Engineering, Qufu Normal University, Rizhao, China
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Fotopoulos D, Ladakis I, Kilintzis V, Chytas A, Koutsiana E, Loizidis T, Chouvarda I. Gamifying rehabilitation: MILORD platform as an upper limb motion rehabilitation service. FRONTIERS IN COMPUTER SCIENCE 2022. [DOI: 10.3389/fcomp.2022.932342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Motor learning is based on the correct repetition of specific movements for their permanent storage in the central nervous system (CNS). Rehabilitation relies heavily on the repetition of specific movements, and game scenarios are ideal environments to build routines of repetitive exercises that have entertaining characteristics. In this respect, the gamification of the rehabilitation program, through the introduction of game-specific techniques and design concepts, has gained attention as a complementary or alternative to routine rehabilitation programs. A gamified rehabilitation program promises to gain the patient's attention, to reduce the monotony of the process and preserve motivation to attend, and to create virtual incentives through the game, toward maintaining compliance to the “prescribed” program. This is often achieved through goal-oriented tasks and real-time feedback in the form of points and other in-game rewards. This paper describes MILORD rehabilitation platform, an affordable technological solution, which aims to support health professionals and enable remote rehabilitation, while maintaining health service characteristics and monitoring. MILORD is an end-to-end platform that consists of an interactive computer game, utilizing a leap motion sensor, a centralized user management system, an analysis platform that processes the data generated by the game, and an analysis dashboard presenting a set of meaningful features that describe upper limb movement. Our solution facilitates the monitoring of the patients' progress and provides an alternative way to analyze hand movement. The system was tested with normal subjects and patients and experts to record user's experience, receive feedback, identify any problems, and understand the system's value in monitoring and support motion defect and progress. This small-scale study indicated the capacity of the analysis to quantify the movement in a meaningful way and express the differences between normal and pathological movement, and the user experience was positive with both patients and normal subjects.
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Cotton RJ, Newman C. Commentary on: "Use of an EMG-Controlled Game as a Therapeutic Tool to Retrain Hand Muscle Activation Patterns Following Stroke: A Pilot Study". J Neurol Phys Ther 2022; 46:227-228. [PMID: 35580135 DOI: 10.1097/npt.0000000000000407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- R James Cotton
- Shirley Ryan AbilityLab, Chicago, Illinois (R.J.C., C.N.) and Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois (R.J.C.)
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Seo NJ, Barry A, Ghassemi M, Triandafilou KM, Stoykov ME, Vidakovic L, Roth E, Kamper DG. Use of an EMG-Controlled Game as a Therapeutic Tool to Retrain Hand Muscle Activation Patterns Following Stroke: A Pilot Study. J Neurol Phys Ther 2022; 46:198-205. [PMID: 35320135 PMCID: PMC9232857 DOI: 10.1097/npt.0000000000000398] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
BACKGROUND/PURPOSE To determine the feasibility of training with electromyographically (EMG) controlled games to improve control of muscle activation patterns in stroke survivors. METHODS Twenty chronic stroke survivors (>6 months) with moderate hand impairment were randomized to train either unilaterally (paretic only) or bilaterally over 9 one-hour training sessions. EMG signals from the unilateral or bilateral limbs controlled a cursor location on a computer screen for gameplay. The EMG muscle activation vector was projected onto the plane defined by the first 2 principal components of the activation workspace for the nonparetic hand. These principal components formed the x- and y-axes of the computer screen. RESULTS The recruitment goal (n = 20) was met over 9 months, with no screen failure, no attrition, and 97.8% adherence rate. After training, both groups significantly decreased the time to move the cursor to a novel sequence of targets (P = 0.006) by reducing normalized path length of the cursor movement (P = 0.005), and improved the Wolf Motor Function Test (WMFT) quality score (P = 0.01). No significant group difference was observed. No significant change was seen in the WMFT time or Box and Block Test. DISCUSSION/CONCLUSIONS Stroke survivors could successfully use the EMG-controlled games to train control of muscle activation patterns. While the nonparetic limb EMG was used in this study to create target EMG patterns, the system supports various means for creating target patterns per user desires. Future studies will employ training with the EMG-controlled games in conjunction with functional task practice for a longer intervention duration to improve overall hand function.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A379).
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Affiliation(s)
- Na Jin Seo
- Departments of Rehabilitation Sciences and Health Science and Research, Medical University of South Carolina, Charleston, and Ralph H. Johnson VA Medical Center, Charleston, South Carolina (N.J.S.); Shirley Ryan AbilityLab, Chicago, Illinois (A.B., K.M.T., M.E.S., L.V. E.R.); Joint Department of Biomedical Engineering, North Carolina State University/University of North Carolina at Chapel Hill, Raleigh, Chapel Hill (M.G., D.G.K); and Department of Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.E.S., L.V., E.R.)
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Zeng H, Yu W, Chen D, Hu X, Zhang D, Song A. Exploring Biomimetic Stiffness Modulation and Wearable Finger Haptics for Improving Myoelectric Control of Virtual Hand. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1601-1611. [PMID: 35675253 DOI: 10.1109/tnsre.2022.3181284] [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: 11/07/2022]
Abstract
The embodiment of virtual hand (VH) by the user is generally deemed to be important for virtual reality (VR) based hand rehabilitation applications, which may help to engage the user and promote motor skill relearning. In particular, it requires that the VH should produce task-dependent interaction behaviors from rigid to soft. While such a capability is inherent to humans via hand stiffness regulation and haptic interactions, yet it have not been successfully imitated by VH in existing studies. In this paper, we present a work which integrates biomimetic stiffness regulation and wearable finger force feedback in VR scenarios involving myoelectric control of VH. On one hand, the biomimetic stiffness modulation intuitively enables VH to imitate the stiffness profile of the user's hand in real time. On the other hand, the wearable finger force-feedback device elicits a natural and realistic sensation of external force on the fingertip, which provides the user a proper understanding of the environment for enhancing his/her stiffness regulation. The benefits of the proposed integrated system were evaluated with eight healthy subjects that performed two tasks with opposite stiffness requirements. The achieved performance is compared with reduced versions of the integrated system, where either biomimetic impedance control or wearable force feedback is excluded. The results suggest that the proposed integrated system enables the stiffness of VH to be adaptively regulated by the user through the perception of interaction torques and vision, resulting in task-dependent behaviors from rigid to soft for VH.
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Application of Digital Games for Speech Therapy in Children: A Systematic Review of Features and Challenges. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:4814945. [PMID: 35509705 PMCID: PMC9061057 DOI: 10.1155/2022/4814945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 02/22/2022] [Accepted: 03/02/2022] [Indexed: 11/17/2022]
Abstract
Introduction Treatment of speech disorders during childhood is essential. Many technologies can help speech and language pathologists (SLPs) to practice speech skills, one of which is digital games. This study aimed to systematically investigate the games developed to treat speech disorders and their challenges in children. Methods A comprehensive search was conducted in four databases, including Medline (through PubMed), Scopus, Web of Science, and IEEE Xplore, to retrieve English articles published by July 14, 2021. The articles in which a digital game was developed to treat speech disorders in children were included in the study. Then, the features of the designed games and their challenges were extracted from the studies. Results After reviewing the full texts of 69 articles and assessing them in terms of inclusion and exclusion criteria, 27 articles were included in the systematic review. In these articles, 59.25% of the games had been developed in English language and children with hearing impairments had received much attention from researchers compared to other patients. Also, the Mel-Frequency Cepstral Coefficients (MFCC) algorithm and the PocketSphinx speech recognition engine had been used more than any other speech recognition algorithm and tool. In terms of the games, 48.15% had been designed in a way that children could practice with the help of their parents. The evaluation of games showed a positive effect on children's satisfaction, motivation, and attention during speech therapy exercises. The biggest barriers and challenges mentioned in the studies included sense of frustration, low self-esteem after several failures in playing games, environmental noise, contradiction between games levels and the target group's needs, and problems related to speech recognition. Conclusion The results of this study showed that the games positively affect children's motivation to continue speech therapy, and they can also be used as the SLPs' aids. Before designing these tools, the obstacles and challenges should be considered, and also, the solutions should be suggested.
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Buyego P, Katwesigye E, Kebirungi G, Nsubuga M, Nakyejwe S, Cruz P, McCarthy MC, Hurt D, Kambugu A, Arinaitwe JW, Ssekabira U, Jjingo D. Feasibility of virtual reality based training for optimising COVID-19 case handling in Uganda. BMC MEDICAL EDUCATION 2022; 22:274. [PMID: 35418070 PMCID: PMC9006530 DOI: 10.1186/s12909-022-03294-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 03/22/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Epidemics and pandemics are causing high morbidity and mortality on a still-evolving scale exemplified by the COVID-19 pandemic. Infection prevention and control (IPC) training for frontline health workers is thus essential. However, classroom or hospital ward-based training portends an infection risk due to the in-person interaction of participants. We explored the use of Virtual Reality (VR) simulations for frontline health worker training since it trains participants without exposing them to infections that would arise from in-person training. It does away with the requirement for expensive personal protective equipment (PPE) that has been in acute shortage and improves learning, retention, and recall. This represents the first attempt in deploying VR-based pedagogy in a Ugandan medical education context. METHODS We used animated VR-based simulations of bedside and ward-based training scenarios for frontline health workers. The training covered the donning and doffing of PPE, case management of COVID-19 infected individuals, and hand hygiene. It used VR headsets to actualize an immersive experience, via a hybrid of fully-interactive VR and 360° videos. The level of knowledge acquisition between individuals trained using this method was compared to similar cohorts previously trained in a classroom setting. That evaluation was supplemented by a qualitative assessment based on feedback from participants about their experience. RESULTS The effort resulted in a COVID-19 IPC curriculum adapted into VR, corresponding VR content, and a pioneer cohort of VR trained frontline health workers. The formalized comparison with classroom-trained cohorts showed relatively better outcomes by way of skills acquired, speed of learning, and rates of information retention (P-value = 4.0e-09). In the qualitative assessment, 90% of the participants rated the method as very good, 58.1% strongly agreed that the activities met the course objectives, and 97.7% strongly indicated willingness to refer the course to colleagues. CONCLUSION VR-based COVID-19 IPC training is feasible, effective and achieves enhanced learning while protecting participants from infections within a pandemic setting in Uganda. It is a delivery medium transferable to the contexts of other highly infectious diseases.
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Affiliation(s)
- Paul Buyego
- Infectious Diseases Institute, Makerere University, Kampala, Uganda
| | | | - Grace Kebirungi
- Infectious Diseases Institute, Makerere University, Kampala, Uganda
- The African Center of Excellence in Bioinformatics and Data Intensive Sciences, Makerere University, Kampala, Uganda
| | - Mike Nsubuga
- Infectious Diseases Institute, Makerere University, Kampala, Uganda
- The African Center of Excellence in Bioinformatics and Data Intensive Sciences, Makerere University, Kampala, Uganda
| | - Shirley Nakyejwe
- The African Center of Excellence in Bioinformatics and Data Intensive Sciences, Makerere University, Kampala, Uganda
| | - Phillip Cruz
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Meghan C McCarthy
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Darrell Hurt
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Andrew Kambugu
- Infectious Diseases Institute, Makerere University, Kampala, Uganda
| | | | - Umaru Ssekabira
- Infectious Diseases Institute, Makerere University, Kampala, Uganda
| | - Daudi Jjingo
- Infectious Diseases Institute, Makerere University, Kampala, Uganda.
- The African Center of Excellence in Bioinformatics and Data Intensive Sciences, Makerere University, Kampala, Uganda.
- Department of Computer Science, College of Computing and Information Sciences, Makerere University, Kampala, Uganda.
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Mashayekhi M, Moghaddam MM. Emg-driven Fatigue-based Self-adapting Admittance Control of a Hand Rehabilitation Robot. J Biomech 2022; 138:111104. [DOI: 10.1016/j.jbiomech.2022.111104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 01/31/2022] [Accepted: 04/24/2022] [Indexed: 11/26/2022]
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Lin Y, Palaniappan R, De Wilde P, Li L. Reliability Analysis For Finger Movement Recognition With Raw Electromyographic Signal by Evidential Convolutional Networks. IEEE Trans Neural Syst Rehabil Eng 2022; 30:96-107. [PMID: 34995190 DOI: 10.1109/tnsre.2022.3141593] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Hand gesture recognition with surface electromyography (sEMG) is indispensable for Muscle-Gesture-Computer Interface. The usual focus of it is upon performance evaluation involving the accuracy and robustness of hand gesture recognition. However, addressing the reliability of such classifiers has been absent, to our best knowledge. This may be due to the lack of consensus on the definition of model reliability in this field. An uncertainty-aware model has the potential to self-evaluate the quality of its inference, thereby making it more reliable. Moreover, uncertainty-based rejection has been shown to improve the performance of sEMG-based hand gesture recognition. Therefore, we first define model reliability here as the quality of its uncertainty estimation and propose an offline framework to quantify it. To promote reliability analysis, we propose a novel end-to-end uncertainty-aware finger movement classifier, i.e., evidential convolutional neural network (ECNN), and illustrate the advantages of its multidimensional uncertainties such as vacuity and dissonance. Extensive comparisons of accuracy and reliability are conducted on NinaPro Database 5, exercise A, across CNN and three variants of ECNN based on different training strategies. The results of classifying 12 finger movements over 10 subjects show that the best mean accuracy achieved by ECNN is 76.34%, which is slightly higher than the state-of-the-art performance. Furthermore, ECNN variants are more reliable than CNN in general, where the highest improvement of reliability of 19.33% is observed. This work demonstrates the potential of ECNN and recommends using the proposed reliability analysis as a supplementary measure for studying sEMG-based hand gesture recognition.
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FUKUHARA S, OKA H. Pedaling stroke length effects on the muscle mechanical and electrical activity during recumbent cycling. GAZZETTA MEDICA ITALIANA ARCHIVIO PER LE SCIENZE MEDICHE 2021. [DOI: 10.23736/s0393-3660.20.04516-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Batista E, Moncusi MA, López-Aguilar P, Martínez-Ballesté A, Solanas A. Sensors for Context-Aware Smart Healthcare: A Security Perspective. SENSORS (BASEL, SWITZERLAND) 2021; 21:6886. [PMID: 34696099 PMCID: PMC8537585 DOI: 10.3390/s21206886] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/12/2021] [Accepted: 10/14/2021] [Indexed: 12/24/2022]
Abstract
The advances in the miniaturisation of electronic devices and the deployment of cheaper and faster data networks have propelled environments augmented with contextual and real-time information, such as smart homes and smart cities. These context-aware environments have opened the door to numerous opportunities for providing added-value, accurate and personalised services to citizens. In particular, smart healthcare, regarded as the natural evolution of electronic health and mobile health, contributes to enhance medical services and people's welfare, while shortening waiting times and decreasing healthcare expenditure. However, the large number, variety and complexity of devices and systems involved in smart health systems involve a number of challenging considerations to be considered, particularly from security and privacy perspectives. To this aim, this article provides a thorough technical review on the deployment of secure smart health services, ranging from the very collection of sensors data (either related to the medical conditions of individuals or to their immediate context), the transmission of these data through wireless communication networks, to the final storage and analysis of such information in the appropriate health information systems. As a result, we provide practitioners with a comprehensive overview of the existing vulnerabilities and solutions in the technical side of smart healthcare.
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Affiliation(s)
- Edgar Batista
- Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain; (E.B.); (M.A.M.); (A.M.-B.)
- SIMPPLE S.L., C. Joan Maragall 1A, 43003 Tarragona, Spain
| | - M. Angels Moncusi
- Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain; (E.B.); (M.A.M.); (A.M.-B.)
| | - Pablo López-Aguilar
- Anti-Phishing Working Group EU, Av. Diagonal 621–629, 08028 Barcelona, Spain;
| | - Antoni Martínez-Ballesté
- Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain; (E.B.); (M.A.M.); (A.M.-B.)
| | - Agusti Solanas
- Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain; (E.B.); (M.A.M.); (A.M.-B.)
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Hau CT, Gouwanda D, Gopalai AA, Low CY, Hanapiah FA. Gamification and Control of Nitinol Based Ankle Rehabilitation Robot. Biomimetics (Basel) 2021; 6:biomimetics6030053. [PMID: 34562877 PMCID: PMC8482156 DOI: 10.3390/biomimetics6030053] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 09/02/2021] [Accepted: 09/16/2021] [Indexed: 11/16/2022] Open
Abstract
Conventional ankle rehabilitation exercises can be monotonous and repetitive. The use of robots and games can complement the existing practices, provide an engaging environment for the patient and alleviate the physiotherapist’s workload. This paper presents an ankle rehabilitation robot that uses two nitinol wire actuators and a Pong game to provide foot plantarflexion and dorsiflexion exercises. Nitinol is a type of smart material that has high volumetric mechanical energy density and can produce translational motion. A two-state discrete antagonistic control is proposed to manipulate the actuators. The system was tested on healthy participants and stroke patients. The results showed that the robot was safe and compliant. The robot did not forcefully plantarflex or dorsiflex the foot when the participant exerted opposing force. The actuators worked antagonistically to flex to the foot as intended, in sync with the up and down motions of the player’s bat in the game. These behaviors demonstrated the feasibility of a nitinol-based ankle rehabilitation robot and a simple and yet intuitive game in providing interactive rehabilitation exercise. The robot is expected to enhance the patient’s experience, participation and compliance to the rehabilitation routine and to quantitatively monitor the patient’s recovery progress.
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Affiliation(s)
- Chong Tune Hau
- School of Engineering, Monash University Malaysia, Bandar Sunway 47500, Selangor, Malaysia; (C.T.H.); (A.A.G.)
| | - Darwin Gouwanda
- School of Engineering, Monash University Malaysia, Bandar Sunway 47500, Selangor, Malaysia; (C.T.H.); (A.A.G.)
- Correspondence:
| | - Alpha A. Gopalai
- School of Engineering, Monash University Malaysia, Bandar Sunway 47500, Selangor, Malaysia; (C.T.H.); (A.A.G.)
| | - Cheng Yee Low
- Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat 86400, Johor, Malaysia;
| | - Fazah A. Hanapiah
- Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh 47000, Selangor, Malaysia;
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16
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Hong YNG, Ballekere AN, Fregly BJ, Roh J. Are muscle synergies useful for stroke rehabilitation? CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021. [DOI: 10.1016/j.cobme.2021.100315] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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17
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Pacheco MM, Moraes R, Lemos TW, Bongers RM, Tani G. Convergence in myoelectric control: Between individual patterns of myoelectric learning. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.103057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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18
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Sawa R, Saitoh M, Morisawa T, Takahashi T, Morimoto Y, Kagiyama N, Kasai T, Dinesen B, Daida H. Potential of Commercially Available Active Video Game for Application to Cardiac Rehabilitation: A Scoping Review (Preprint). JMIR Serious Games 2021; 10:e31974. [PMID: 35302503 PMCID: PMC8976248 DOI: 10.2196/31974] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 01/04/2022] [Accepted: 01/16/2022] [Indexed: 11/22/2022] Open
Abstract
Background Commercially available active video games (AVGs) have recently been used for rehabilitation in some specific patient populations but rarely in those with cardiovascular disease (CVD). Commercially available AVGs are designed to increase motivation for continuous play, which could be applicable to the long-term cardiac rehabilitation process. Objective The objective of this scoping review was to assess the effectiveness of AVG-induced physical exercise, safety management, and patient adherence by applying commercially available AVGs to cardiac rehabilitation. Methods Four databases (CINAHL, MEDLINE, PubMed, and SPORTDiscus) were searched for all years up to August 12, 2020. Articles were retained if they were written in English, included patients with CVD who were aged 18 years or older, and used AVGs as part of a physical exercise program. The included studies were then evaluated from the viewpoints of effectiveness as physical exercise, safety, and adherence management. Results Among 120 nonduplicate articles reviewed, 5 (4.2%) were eligible for inclusion, of which 3 (2.5%) were reported by the same research group. The AVG consoles used were Xbox Kinect and Nintendo Wii, and sports-related programs were adopted for the intervention. No adverse cardiac events occurred in the identified studies, and dropout rates tended to be low. Conclusions AVGs appear to be safe and feasible for promoting an active lifestyle in patients with CVD. However, the effectiveness of AVGs alone as a therapeutic exercise to improve physical function may be limited.
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Affiliation(s)
- Ryuichi Sawa
- Department of Physical Therapy, Faculty of Health Science, Juntendo University, Tokyo, Japan
| | - Masakazu Saitoh
- Department of Physical Therapy, Faculty of Health Science, Juntendo University, Tokyo, Japan
| | - Tomoyuki Morisawa
- Department of Physical Therapy, Faculty of Health Science, Juntendo University, Tokyo, Japan
| | - Tetsuya Takahashi
- Department of Physical Therapy, Faculty of Health Science, Juntendo University, Tokyo, Japan
- Department of Digital Health and Telemedicine Research and Development, Faculty of Health Science, Juntendo University, Tokyo, Japan
| | - Yuh Morimoto
- Faculty of Health Science, Juntendo University, Tokyo, Japan
| | - Nobuyuki Kagiyama
- Department of Digital Health and Telemedicine Research and Development, Faculty of Health Science, Juntendo University, Tokyo, Japan
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Takatoshi Kasai
- Department of Digital Health and Telemedicine Research and Development, Faculty of Health Science, Juntendo University, Tokyo, Japan
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Birthe Dinesen
- Laboratory for Welfare Technologies - Telehealth & Telerehabilitation, Sport Sciences - Performance and Technology, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Hiroyuki Daida
- Department of Physical Therapy, Faculty of Health Science, Juntendo University, Tokyo, Japan
- Department of Digital Health and Telemedicine Research and Development, Faculty of Health Science, Juntendo University, Tokyo, Japan
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
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19
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Bouteraa Y, Abdallah IB, Ibrahim A, Ahanger TA. Fuzzy logic-based connected robot for home rehabilitation. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-201671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
In this paper, a robotic system dedicated to remote wrist rehabilitation is proposed as an Internet of Things (IoT) application. The system offers patients home rehabilitation. Since the physiotherapist and the patient are on different sites, the system guarantees that the physiotherapist controls and supervises the rehabilitation process and that the patient repeats the same gestures made by the physiotherapist. A human-machine interface (HMI) has been developed to allow the physiotherapist to remotely control the robot and supervise the rehabilitation process. Based on a computer vision system, physiotherapist gestures are sent to the robot in the form of control instructions. Wrist range of motion (RoM), EMG signal, sensor current measurement, and streaming from the patient’s environment are returned to the control station. The various acquired data are displayed in the HMI and recorded in its database, which allows later monitoring of the patient’s progress. During the rehabilitation process, the developed system makes it possible to follow the muscle contraction thanks to an extraction of the Electromyography (EMG) signal as well as the patient’s resistance thanks to a feedback from a current sensor. Feature extraction algorithms are implemented to transform the EMG raw signal into a relevant data reflecting the muscle contraction. The solution incorporates a cascade fuzzy-based decision system to indicate the patient’s pain. As measurement safety, when the pain exceeds a certain threshold, the robot should stop the action even if the desired angle is not yet reached. Information on the patient, the evolution of his state of health and the activities followed, are all recorded, which makes it possible to provide an electronic health record. Experiments on 3 different subjects showed the effectiveness of the developed robotic solution.
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Affiliation(s)
- Yassine Bouteraa
- Digital Research Center of Sfax & CEM Lab-ENIS, University of Sfax, Sfax, Tunisia
- Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | | | - Atef Ibrahim
- Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
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20
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Cote-Allard U, Gagnon-Turcotte G, Phinyomark A, Glette K, Scheme E, Laviolette F, Gosselin B. A Transferable Adaptive Domain Adversarial Neural Network for Virtual Reality Augmented EMG-Based Gesture Recognition. IEEE Trans Neural Syst Rehabil Eng 2021; 29:546-555. [PMID: 33591919 DOI: 10.1109/tnsre.2021.3059741] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Within the field of electromyography-based (EMG) gesture recognition, disparities exist between the offline accuracy reported in the literature and the real-time usability of a classifier. This gap mainly stems from two factors: 1) The absence of a controller, making the data collected dissimilar to actual control. 2) The difficulty of including the four main dynamic factors (gesture intensity, limb position, electrode shift, and transient changes in the signal), as including their permutations drastically increases the amount of data to be recorded. Contrarily, online datasets are limited to the exact EMG-based controller used to record them, necessitating the recording of a new dataset for each control method or variant to be tested. Consequently, this paper proposes a new type of dataset to serve as an intermediate between offline and online datasets, by recording the data using a real-time experimental protocol. The protocol, performed in virtual reality, includes the four main dynamic factors and uses an EMG-independent controller to guide movements. This EMG-independent feedback ensures that the user is in-the-loop during recording, while enabling the resulting dynamic dataset to be used as an EMG-based benchmark. The dataset is comprised of 20 able-bodied participants completing three to four sessions over a period of 14 to 21 days. The ability of the dynamic dataset to serve as a benchmark is leveraged to evaluate the impact of different recalibration techniques for long-term (across-day) gesture recognition, including a novel algorithm, named TADANN. TADANN consistently and significantly ( [Formula: see text]) outperforms using fine-tuning as the recalibration technique.
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21
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Koutsiana E, Ladakis I, Fotopoulos D, Chytas A, Kilintzis V, Chouvarda I. Serious Gaming Technology in Upper Extremity Rehabilitation: Scoping Review. JMIR Serious Games 2020; 8:e19071. [PMID: 33306029 PMCID: PMC7762690 DOI: 10.2196/19071] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 07/31/2020] [Accepted: 11/13/2020] [Indexed: 12/31/2022] Open
Abstract
Background Serious gaming has increasingly gained attention as a potential new component in clinical practice. Specifically, its use in the rehabilitation of motor dysfunctions has been intensively researched during the past three decades. Objective The aim of this scoping review was to evaluate the current role of serious games in upper extremity rehabilitation, and to identify common methods and practice as well as technology patterns. This objective was approached via the exploration of published research efforts over time. Methods The literature search, using the PubMed and Scopus databases, included articles published from 1999 to 2019. The eligibility criteria were (i) any form of game-based arm rehabilitation; (ii) published in a peer-reviewed journal or conference; (iii) introduce a game in an electronic format; (iv) published in English; and (v) not a review, meta-analysis, or conference abstract. The search strategy identified 169 relevant articles. Results The results indicated an increasing research trend in the domain of serious gaming deployment in upper extremity rehabilitation. Furthermore, differences regarding the number of publications and the game approach were noted between studies that used commercial devices in their rehabilitation systems and those that proposed a custom-made robotic arm, glove, or other devices for the connection and interaction with the game platform. A particularly relevant observation concerns the evaluation of the introduced systems. Although one-third of the studies evaluated their implementations with patients, in most cases, there is the need for a larger number of participants and better testing of the rehabilitation scheme efficiency over time. Most of the studies that included some form of assessment for the introduced rehabilitation game mentioned user experience as one of the factors considered for evaluation of the system. Besides user experience assessment, the most common evaluation method involving patients was the use of standard medical tests. Finally, a few studies attempted to extract game features to introduce quantitative measurements for the evaluation of patient improvement. Conclusions This paper presents an overview of a significant research topic and highlights the current state of the field. Despite extensive attempts for the development of gamified rehabilitation systems, there is no definite answer as to whether a serious game is a favorable means for upper extremity functionality improvement; however, this certainly constitutes a supplementary means for motivation. The development of a unified performance quantification framework and more extensive experiments could generate richer evidence and contribute toward this direction.
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Affiliation(s)
- Elisavet Koutsiana
- Lab of Computing, Medical Informatics, and Biomedical-Imaging Technologies, School of Medicine, Aristotle University, Thessaloniki, Greece
| | - Ioannis Ladakis
- Lab of Computing, Medical Informatics, and Biomedical-Imaging Technologies, School of Medicine, Aristotle University, Thessaloniki, Greece
| | - Dimitris Fotopoulos
- Lab of Computing, Medical Informatics, and Biomedical-Imaging Technologies, School of Medicine, Aristotle University, Thessaloniki, Greece
| | - Achilleas Chytas
- Lab of Computing, Medical Informatics, and Biomedical-Imaging Technologies, School of Medicine, Aristotle University, Thessaloniki, Greece
| | - Vassilis Kilintzis
- Lab of Computing, Medical Informatics, and Biomedical-Imaging Technologies, School of Medicine, Aristotle University, Thessaloniki, Greece
| | - Ioanna Chouvarda
- Lab of Computing, Medical Informatics, and Biomedical-Imaging Technologies, School of Medicine, Aristotle University, Thessaloniki, Greece
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22
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do Nascimento LMS, Bonfati LV, Freitas MLB, Mendes Junior JJA, Siqueira HV, Stevan SL. Sensors and Systems for Physical Rehabilitation and Health Monitoring-A Review. SENSORS (BASEL, SWITZERLAND) 2020; 20:E4063. [PMID: 32707749 PMCID: PMC7436073 DOI: 10.3390/s20154063] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 07/09/2020] [Accepted: 07/12/2020] [Indexed: 01/03/2023]
Abstract
The use of wearable equipment and sensing devices to monitor physical activities, whether for well-being, sports monitoring, or medical rehabilitation, has expanded rapidly due to the evolution of sensing techniques, cheaper integrated circuits, and the development of connectivity technologies. In this scenario, this paper presents a state-of-the-art review of sensors and systems for rehabilitation and health monitoring. Although we know the increasing importance of data processing techniques, our focus was on analyzing the implementation of sensors and biomedical applications. Although many themes overlap, we organized this review based on three groups: Sensors in Healthcare, Home Medical Assistance, and Continuous Health Monitoring; Systems and Sensors in Physical Rehabilitation; and Assistive Systems.
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Affiliation(s)
- Lucas Medeiros Souza do Nascimento
- Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology of Parana (UTFPR), Ponta Grossa (PR) 84016-210, Brazil; (L.M.S.d.N.); (L.V.B.); (M.L.B.F.); (H.V.S.)
| | - Lucas Vacilotto Bonfati
- Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology of Parana (UTFPR), Ponta Grossa (PR) 84016-210, Brazil; (L.M.S.d.N.); (L.V.B.); (M.L.B.F.); (H.V.S.)
| | - Melissa La Banca Freitas
- Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology of Parana (UTFPR), Ponta Grossa (PR) 84016-210, Brazil; (L.M.S.d.N.); (L.V.B.); (M.L.B.F.); (H.V.S.)
| | - José Jair Alves Mendes Junior
- Graduate Program in Electrical Engineering and Industrial Informatics (CPGEI), Federal University of Technology of Parana (UTFPR), Curitiba (PR) 80230-901, Brazil;
| | - Hugo Valadares Siqueira
- Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology of Parana (UTFPR), Ponta Grossa (PR) 84016-210, Brazil; (L.M.S.d.N.); (L.V.B.); (M.L.B.F.); (H.V.S.)
| | - Sergio Luiz Stevan
- Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology of Parana (UTFPR), Ponta Grossa (PR) 84016-210, Brazil; (L.M.S.d.N.); (L.V.B.); (M.L.B.F.); (H.V.S.)
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23
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Jayasinghe SAL, Ranganathan R. Effects of Short-Term Mental Imagery and Supplemental Visual Feedback on Muscle Coordination in a Myoelectric Task. J Mot Behav 2020; 53:59-71. [PMID: 32041488 DOI: 10.1080/00222895.2020.1723482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Changing muscle coordination patterns is a critical part of motor learning - yet there is a lack of simple, clinically feasible techniques to alter these patterns. Here, we investigated the effects of short-term mental imagery and supplemental visual feedback on muscle coordination using a myoelectric reaching task with complex mapping of arm and hand muscles to cursor position. Forty participants were divided into four groups, and practiced this task over 180 trials. During a short intervention period, the controls rested, the task- and muscle-imagery groups were given specific instructions meant to simplify the task, and the supplemental feedback group was provided extra visual information of muscle-to-cursor mapping. Results showed that there were no changes in task performance between groups. However, we found that in terms of muscle coordination, the supplemental visual feedback group showed the most efficient coordination. Furthermore, across all groups, individuals with greater efficiency and exploration showed better task performance at the end of practice. The results from this pilot study point to a greater need for understanding strategies for changing muscle coordination, which could be applicable in a rehabilitation setting.
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Affiliation(s)
| | - Rajiv Ranganathan
- Department of Kinesiology, Michigan State University, East Lansing, MI, USA.,Mechanical Engineering, Michigan State University, East Lansing, MI, USA
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24
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Dash A, Lahiri U. Design of Virtual Reality-Enabled Surface Electromyogram-Triggered Grip Exercise Platform. IEEE Trans Neural Syst Rehabil Eng 2019; 28:444-452. [PMID: 31841415 DOI: 10.1109/tnsre.2019.2959449] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Adequate grip ability is important for effective execution of daily living activities. Neurological disorders like stroke that result in muscle weakness, limited strength and poor control often lead to reduced grip ability in the affected limb. Conventional rehabilitation for grip training is often monotonous and subjective. Technology-assisted Virtual Reality (VR)-based rehabilitation offers a motivating environment to the participants for rehabilitation. However, the existing systems need specialized set-up architecture, thereby limiting their accessibility. Furthermore, these systems quantify the functional grip ability based on task performance, and do not explore physiological basis of grip ability. In this work, we develop a VR-based rehabilitation platform integrated with physiology-sensitive biofeedback. The developed platform, Gripx makes use of features extracted from sEMG data collected from upper limb muscles to adaptively provide audio-visual biofeedback through a VR environment. We compare task based performance, physiological indices and clinical measures to evaluate the potential of Gripx. The results of our study with 8 healthy and 12 post-stroke participants show the potential of Gripx to contribute to grip rehabilitation over multiple exposures. This approach of integrating VR-based task design with physiology-sensitive biofeedback helps patients to better assess their physiological responses and enhance the efficacy of rehabilitation.
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