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Tacca N, Baumgart I, Schlink BR, Kamath A, Dunlap C, Darrow MJ, Colachis Iv S, Putnam P, Branch J, Wengerd L, Friedenberg DA, Meyers EC. Identifying alterations in hand movement coordination from chronic stroke survivors using a wearable high-density EMG sleeve. J Neural Eng 2024; 21:046040. [PMID: 39008975 DOI: 10.1088/1741-2552/ad634d] [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: 01/02/2024] [Accepted: 07/15/2024] [Indexed: 07/17/2024]
Abstract
Objective.Non-invasive, high-density electromyography (HD-EMG) has emerged as a useful tool to collect a range of neurophysiological motor information. Recent studies have demonstrated changes in EMG features that occur after stroke, which correlate with functional ability, highlighting their potential use as biomarkers. However, previous studies have largely explored these EMG features in isolation with individual electrodes to assess gross movements, limiting their potential clinical utility. This study aims to predict hand function of stroke survivors by combining interpretable features extracted from a wearable HD-EMG forearm sleeve.Approach.Here, able-bodied (N= 7) and chronic stroke subjects (N= 7) performed 12 functional hand and wrist movements while HD-EMG was recorded using a wearable sleeve. A variety of HD-EMG features, or views, were decomposed to assess alterations in motor coordination.Main Results.Stroke subjects, on average, had higher co-contraction and reduced muscle coupling when attempting to open their hand and actuate their thumb. Additionally, muscle synergies decomposed in the stroke population were relatively preserved, with a large spatial overlap in composition of matched synergies. Alterations in synergy composition demonstrated reduced coupling between digit extensors and muscles that actuate the thumb, as well as an increase in flexor activity in the stroke group. Average synergy activations during movements revealed differences in coordination, highlighting overactivation of antagonist muscles and compensatory strategies. When combining co-contraction and muscle synergy features, the first principal component was strongly correlated with upper-extremity Fugl Meyer hand sub-score of stroke participants (R2= 0.86). Principal component embeddings of individual features revealed interpretable measures of motor coordination and muscle coupling alterations.Significance.These results demonstrate the feasibility of predicting motor function through features decomposed from a wearable HD-EMG sleeve, which could be leveraged to improve stroke research and clinical care.
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Affiliation(s)
- Nicholas Tacca
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Ian Baumgart
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Bryan R Schlink
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Ashwini Kamath
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Collin Dunlap
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Michael J Darrow
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Samuel Colachis Iv
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Philip Putnam
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Joshua Branch
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Lauren Wengerd
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
- NeuroTech Institute, The Ohio State University, Columbus, OH, United States of America
| | - David A Friedenberg
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
| | - Eric C Meyers
- Neurotechnology, Battelle Memorial Institute, Columbus, OH, United States of America
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Khan MA, Fares H, Ghayvat H, Brunner IC, Puthusserypady S, Razavi B, Lansberg M, Poon A, Meador KJ. A systematic review on functional electrical stimulation based rehabilitation systems for upper limb post-stroke recovery. Front Neurol 2023; 14:1272992. [PMID: 38145118 PMCID: PMC10739305 DOI: 10.3389/fneur.2023.1272992] [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: 08/05/2023] [Accepted: 11/20/2023] [Indexed: 12/26/2023] Open
Abstract
Background Stroke is one of the most common neurological conditions that often leads to upper limb motor impairments, significantly affecting individuals' quality of life. Rehabilitation strategies are crucial in facilitating post-stroke recovery and improving functional independence. Functional Electrical Stimulation (FES) systems have emerged as promising upper limb rehabilitation tools, offering innovative neuromuscular reeducation approaches. Objective The main objective of this paper is to provide a comprehensive systematic review of the start-of-the-art functional electrical stimulation (FES) systems for upper limb neurorehabilitation in post-stroke therapy. More specifically, this paper aims to review different types of FES systems, their feasibility testing, or randomized control trials (RCT) studies. Methods The FES systems classification is based on the involvement of patient feedback within the FES control, which mainly includes "Open-Loop FES Systems" (manually controlled) and "Closed-Loop FES Systems" (brain-computer interface-BCI and electromyography-EMG controlled). Thus, valuable insights are presented into the technological advantages and effectiveness of Manual FES, EEG-FES, and EMG-FES systems. Results and discussion The review analyzed 25 studies and found that the use of FES-based rehabilitation systems resulted in favorable outcomes for the stroke recovery of upper limb functional movements, as measured by the FMA (Fugl-Meyer Assessment) (Manually controlled FES: mean difference = 5.6, 95% CI (3.77, 7.5), P < 0.001; BCI-controlled FES: mean difference = 5.37, 95% CI (4.2, 6.6), P < 0.001; EMG-controlled FES: mean difference = 14.14, 95% CI (11.72, 16.6), P < 0.001) and ARAT (Action Research Arm Test) (EMG-controlled FES: mean difference = 11.9, 95% CI (8.8, 14.9), P < 0.001) scores. Furthermore, the shortcomings, clinical considerations, comparison to non-FES systems, design improvements, and possible future implications are also discussed for improving stroke rehabilitation systems and advancing post-stroke recovery. Thus, summarizing the existing literature, this review paper can help researchers identify areas for further investigation. This can lead to formulating research questions and developing new studies aimed at improving FES systems and their outcomes in upper limb rehabilitation.
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Affiliation(s)
- Muhammad Ahmed Khan
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
- Department of Electrical Engineering, Stanford University, Palo Alto, CA, United States
- Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Hoda Fares
- Department of Electrical, Electronic, Telecommunication Engineering and Naval Architecture (DITEN), University of Genoa, Genoa, Italy
| | - Hemant Ghayvat
- Department of Computer Science, Linnaeus University, Växjö, Sweden
| | | | | | - Babak Razavi
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
| | - Maarten Lansberg
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
| | - Ada Poon
- Department of Electrical Engineering, Stanford University, Palo Alto, CA, United States
| | - Kimford Jay Meador
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
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Zhou HX, Hu J, Yun RS, Zhao ZZ, Lai MH, Sun LHZ, Luo KL. Synergy-based functional electrical stimulation and robotic-assisted for retraining reach-to-grasp in stroke: a study protocol for a randomized controlled trial. BMC Neurol 2023; 23:324. [PMID: 37700225 PMCID: PMC10496180 DOI: 10.1186/s12883-023-03369-2] [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: 06/17/2023] [Accepted: 09/04/2023] [Indexed: 09/14/2023] Open
Abstract
BACKGROUND Stroke survivors have long-term upper limb impairment, which impacts the quality of life (QOL) and social reintegration, but there is lack of effective therapeutic strategies and novel technologies. Customized multi-muscle functional electrical stimulation (FES) based on the muscle synergy of healthy adults and robotic-assisted therapy (RAT) have been proved efficacy respectively. Synergy-based FES combined with RAT can be a novel and more effective therapy for upper limb recovery of stroke survivors from the perspective of synergistic enhancement. However, few studies have examined the effectiveness of combined synergy-based FES and RAT, especially for motor control evaluated by reach-to-grasp (RTG) movements. The main objective of the following research protocol is to evaluate the effectiveness and efficacy, as well as adoptability, of FES-RAT and FES or RAT rehabilitation program for upper limb function improvement after stroke. METHODS This will be an assessor-blinded randomized controlled trial involving a 12-week intervention and a 6-month follow-up. Stratified randomization will be used to equally and randomly assign 162 stroke patients into the FES + conventional rehabilitation program (CRP) group, RAT + CRP group and FES-RAT + CRP group. Interventions will be provided in 5 sessions per week, with a total of 60 sessions. The primary outcome measurements will include the Fugl-Meyer Assessment and Biomechanical Assessment of RTG movements. The secondary outcome measurements will include quality of life and brain neuroplasticity assessments by MRI. Evaluations will be performed at five time points, including at baseline, 6 weeks and 12 weeks from the start of treatment, and 3 months and 6 months following the end of treatment. A two-way analysis of variance with repeated measures will be applied to examine the main effects of the group, the time factor and group-time interaction effects. DISCUSSION The results of the study protocol will provide high quality evidence for integrated synergy-based FES and RAT, and synergy-based FES alone and guide the design of more effective treatment methods for stroke rehabilitation. TRIAL REGISTRATION ChiCTR2300071588.
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Affiliation(s)
- Huan-Xia Zhou
- Department of Rehabilitation Medical Center, Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jun Hu
- Department of Occupational Therapy, The Second Rehabilitation Hospital of Shanghai, No.25, Lane 860, Changjiang Road, Baoshan District, Shanghai, 200441, China.
| | - Rui-Sheng Yun
- Department of Mental Health Rehabilitation Center, Peking University Sixth Hospital, Beijing, China
| | - Zhong-Zhi Zhao
- Department of Rehabilitation Medical Center, Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Ming-Hui Lai
- Department of Rehabilitation Medical Center, Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Li-Hui-Zi Sun
- Department of Occupational Therapy, The Second Rehabilitation Hospital of Shanghai, No.25, Lane 860, Changjiang Road, Baoshan District, Shanghai, 200441, China
| | - Kai-Liang Luo
- Department of Rehabilitation, The First Affiliated Hospital of Fujian Medical University, Fujian, China
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Chen Z, Yan J, Song X, Qiao Y, Loh YJ, Xie Q, Niu CM. Heavier Load Alters Upper Limb Muscle Synergy with Correlated fNIRS Responses in BA4 and BA6. CYBORG AND BIONIC SYSTEMS 2023; 4:0033. [PMID: 37275578 PMCID: PMC10233656 DOI: 10.34133/cbsystems.0033] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 04/28/2023] [Indexed: 06/07/2023] Open
Abstract
In neurorehabilitation, motor performances may improve if patients could accomplish the training by overcoming mechanical loads. When the load inertia is increased, it has been found to trigger linear responses in motor-related cortices. The cortical responses, however, are unclear whether they also correlate to changes in muscular patterns. Therefore, it remains difficult to justify the magnitude of load during rehabilitation because of the gap between cortical and muscular activation. Here, we test the hypothesis that increases in load inertia may alter the muscle synergies, and the change in synergy may correlate with cortical activation. Twelve healthy subjects participated in the study. Each subject lifted dumbbells (either 0, 3, or 15 pounds) from the resting position to the armpit repetitively at 1 Hz. Surface electromyographic signals were collected from 8 muscles around the shoulder and the elbow, and hemodynamic signals were collected using functional near-infrared spectroscopy from motor-related regions Brodmann Area 4 (BA4) and BA6. Results showed that, given higher inertia, the synergy vectors differed farther from the baseline. Moreover, synergy similarity on the vector decreased linearly with cortical responses in BA4 and BA6, which associated with increases in inertia. Despite studies in literature that movements with similar kinematics tend not to differ in synergy vectors, we show a different possibility that the synergy vectors may deviate from a baseline. At least 2 consequences of adding inertia have been identified: to decrease synergy similarity and to increase motor cortical activity. The dual effects potentially provide a new benchmark for therapeutic goal setting.
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Affiliation(s)
- Zhi Chen
- Department of Rehabilitation Medicine, Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- School of Medicine,
Shanghai Jiao Tong University, Shanghai 200025, China
| | - Jin Yan
- Department of Rehabilitation Medicine, Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- School of Medicine,
Shanghai Jiao Tong University, Shanghai 200025, China
| | - Xiaohui Song
- Department of Rehabilitation Medicine, Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yongjun Qiao
- Department of Rehabilitation Medicine, Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yong Joo Loh
- Department of Rehabilitation Medicine,
Tan-Tock-Seng Hospital, Singapore
| | - Qing Xie
- Department of Rehabilitation Medicine, Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- School of Medicine,
Shanghai Jiao Tong University, Shanghai 200025, China
| | - Chuanxin M. Niu
- Department of Rehabilitation Medicine, Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- School of Medicine,
Shanghai Jiao Tong University, Shanghai 200025, China
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Zhao K, Zhang Z, Wen H, Liu B, Li J, Andrea d’Avella, Scano A. Muscle synergies for evaluating upper limb in clinical applications: A systematic review. Heliyon 2023; 9:e16202. [PMID: 37215841 PMCID: PMC10199229 DOI: 10.1016/j.heliyon.2023.e16202] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 04/11/2023] [Accepted: 05/09/2023] [Indexed: 09/28/2023] Open
Abstract
INTRODUCTION Muscle synergies have been proposed as a strategy employed by the central nervous system to control movements. Muscle synergy analysis is a well-established framework to examine the pathophysiological basis of neurological diseases and has been applied for analysis and assessment in clinical applications in the last decades, even if it has not yet been widely used in clinical diagnosis, rehabilitative treatment and interventions. Even if inconsistencies in the outputs among studies and lack of a normative pipeline including signal processing and synergy analysis limit the progress, common findings and results are identifiable as a basis for future research. Therefore, a literature review that summarizes methods and main findings of previous works on upper limb muscle synergies in clinical environment is needed to i) summarize the main findings so far, ii) highlight the barriers limiting their use in clinical applications, and iii) suggest future research directions needed for facilitating translation of experimental research to clinical scenarios. METHODS Articles in which muscle synergies were used to analyze and assess upper limb function in neurological impairments were reviewed. The literature research was conducted in Scopus, PubMed, and Web of Science. Experimental protocols (e.g., the aim of the study, number and type of participants, number and type of muscles, and tasks), methods (e.g., muscle synergy models and synergy extraction methods, signal processing methods), and the main findings of eligible studies were reported and discussed. RESULTS 383 articles were screened and 51 were selected, which involved a total of 13 diseases and 748 patients and 1155 participants. Each study investigated on average 15 ± 10 patients. Four to forty-one muscles were included in the muscle synergy analysis. Point-to-point reaching was the most used task. The preprocessing of EMG signals and algorithms for synergy extraction varied among studies, and non-negative matrix factorization was the most used method. Five EMG normalization methods and five methods for identifying the optimal number of synergies were used in the selected papers. Most of the studies report that analyses on synergy number, structure, and activations provide novel insights on the physiopathology of motor control that cannot be gained with standard clinical assessments, and suggest that muscle synergies may be useful to personalize therapies and to develop new therapeutic strategies. However, in the selected studies synergies were used only for assessment; different testing procedures were used and, in general, study-specific modifications of muscle synergies were observed; single session or longitudinal studies mainly aimed at assessing stroke (71% of the studies), even though other pathologies were also investigated. Synergy modifications were either study-specific or were not observed, with few analyses available for temporal coefficients. Thus, several barriers prevent wider adoption of muscle synergy analysis including a lack of standardized experimental protocols, signal processing procedures, and synergy extraction methods. A compromise in the design of the studies must be found to combine the systematicity of motor control studies and the feasibility of clinical studies. There are however several potential developments that might promote the use of muscle synergy analysis in clinical practice, including refined assessments based on synergistic approaches not allowed by other methods and the availability of novel models. Finally, neural substrates of muscle synergies are discussed, and possible future research directions are proposed. CONCLUSIONS This review provides new perspectives about the challenges and open issues that need to be addressed in future work to achieve a better understanding of motor impairments and rehabilitative therapy using muscle synergies. These include the application of the methods on wider scales, standardization of procedures, inclusion of synergies in the clinical decisional process, assessment of temporal coefficients and temporal-based models, extensive work on the algorithms and understanding of the physio-pathological mechanisms of pathology, as well as the application and adaptation of synergy-based approaches to various rehabilitative scenarios for increasing the available evidence.
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Affiliation(s)
- Kunkun Zhao
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Zhisheng Zhang
- School of Mechanical Engineering, Southeast University, Nanjing, China
| | - Haiying Wen
- School of Mechanical Engineering, Southeast University, Nanjing, China
| | - Bin Liu
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Jianqing Li
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Andrea d’Avella
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Italy
| | - Alessandro Scano
- Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy (CNR), Milan, Italy
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