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Pregnolato G, Rimini D, Baldan F, Maistrello L, Salvalaggio S, Celadon N, Ariano P, Pirri CF, Turolla A. Clinical Features to Predict the Use of a sEMG Wearable Device (REMO ®) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:5082. [PMID: 36981992 PMCID: PMC10049214 DOI: 10.3390/ijerph20065082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 03/04/2023] [Accepted: 03/09/2023] [Indexed: 06/18/2023]
Abstract
After stroke, upper limb motor impairment is one of the most common consequences that compromises the level of the autonomy of patients. In a neurorehabilitation setting, the implementation of wearable sensors provides new possibilities for enhancing hand motor recovery. In our study, we tested an innovative wearable (REMO®) that detected the residual surface-electromyography of forearm muscles to control a rehabilitative PC interface. The aim of this study was to define the clinical features of stroke survivors able to perform ten, five, or no hand movements for rehabilitation training. 117 stroke patients were tested: 65% of patients were able to control ten movements, 19% of patients could control nine to one movement, and 16% could control no movements. Results indicated that mild upper limb motor impairment (Fugl-Meyer Upper Extremity ≥ 18 points) predicted the control of ten movements and no flexor carpi muscle spasticity predicted the control of five movements. Finally, severe impairment of upper limb motor function (Fugl-Meyer Upper Extremity > 10 points) combined with no pain and no restrictions of upper limb joints predicted the control of at least one movement. In conclusion, the residual motor function, pain and joints restriction, and spasticity at the upper limb are the most important clinical features to use for a wearable REMO® for hand rehabilitation training.
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Affiliation(s)
- Giorgia Pregnolato
- Laboratory of Healthcare Innovation Technology, IRCCS San Camillo Hospital, Via Alberoni 70, 30126 Venice, Italy; (L.M.); (S.S.)
| | - Daniele Rimini
- Medical Physics Department, Salford Care Organisation, Northern Care Alliance, Salford M6 8HD, UK;
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University Of Manchester, Manchester M13 9PL, UK
| | | | - Lorenza Maistrello
- Laboratory of Healthcare Innovation Technology, IRCCS San Camillo Hospital, Via Alberoni 70, 30126 Venice, Italy; (L.M.); (S.S.)
| | - Silvia Salvalaggio
- Laboratory of Healthcare Innovation Technology, IRCCS San Camillo Hospital, Via Alberoni 70, 30126 Venice, Italy; (L.M.); (S.S.)
- Padova Neuroscience Center, Università degli Studi di Padova, Via Orus 2/B, 35131 Padova, Italy
| | - Nicolò Celadon
- Morecognition s.r.l., 10129 Turin, Italy; (N.C.); (P.A.)
| | - Paolo Ariano
- Morecognition s.r.l., 10129 Turin, Italy; (N.C.); (P.A.)
- Artificial Physiology Group, Center for Sustainable Future Technologies, Istituto Italiano di Tecnologia, Via Livorno 60, 10144 Torino, Italy;
| | - Candido Fabrizio Pirri
- Artificial Physiology Group, Center for Sustainable Future Technologies, Istituto Italiano di Tecnologia, Via Livorno 60, 10144 Torino, Italy;
- Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy
| | - Andrea Turolla
- Department of Biomedical and Neuromotor Sciences—DIBINEM, Alma Mater Studiorum Università di Bologna, Via Massarenti, 9, 40138 Bologna, Italy;
- Unit of Occupational Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Pelagio Palagi, 9, 40138 Bologna, Italy
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Marcos-Antón S, Gor-García-Fogeda MD, Cano-de-la-Cuerda R. An sEMG-Controlled Forearm Bracelet for Assessing and Training Manual Dexterity in Rehabilitation: A Systematic Review. J Clin Med 2022; 11:jcm11113119. [PMID: 35683503 PMCID: PMC9181798 DOI: 10.3390/jcm11113119] [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: 03/11/2022] [Revised: 05/24/2022] [Accepted: 05/27/2022] [Indexed: 01/27/2023] Open
Abstract
Background: The ability to perform activities of daily living (ADL) is essential to preserving functional independence and quality of life. In recent years, rehabilitation strategies based on new technologies, such as MYO Armband®, have been implemented to improve dexterity in people with upper limb impairment. Over the last few years, many studies have been published focusing on the accuracy of the MYO Armband® to capture electromyographic and inertial data, as well as the clinical effects of using it as a rehabilitation tool in people with loss of upper limb function. Nevertheless, to our knowledge, there has been no systematic review of this subject. Methods: A systematically comprehensive literature search was conducted in order to identify original studies that answered the PICO question (patient/population, intervention, comparison, and outcome): What is the accuracy level and the clinical effects of the MYO Armband® in people with motor impairment of the upper limb compared with other assessment techniques or interventions or no intervention whatsoever? The following data sources were used: Pubmed, Scopus, Web of Science, ScienceDirect, Physiotherapy Evidence Database, and the Cochrane Library. After identifying the eligible articles, a cross-search of their references was also completed for additional studies. The following data were extracted from the papers: study design, disease or condition, intervention, sample, dosage, outcome measures or data collection procedure and data analysis and results. The authors independently collected these data following the CONSORT 2010 statement when possible, and eventually reached a consensus on the extracted data, resolving disagreements through discussion. To assess the methodological quality of papers included, the tool for the critical appraisal of epidemiological cross-sectional studies was used, since only case series studies were identified after the search. Additionally, the articles were classified according to the levels of evidence and grades of recommendation for diagnosis studies established by the Oxford Center for Evidence-Based Medicine. Also, The Cochrane Handbook for Systematic Reviews of Interventions was used by two independent reviewers to assess risk of bias, assessing the six different domains. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was followed to carry out this review. Results: 10 articles with a total 180 participants were included in the review. The characteristics of included studies, sample and intervention characteristics, outcome measures, the accuracy of the system and effects of the interventions and the assessment of methodological quality of the studies and risk of bias are shown. Conclusions: Therapy with the MYO Armband® has shown clinical changes in range of motion, dexterity, performance, functionality and satisfaction. It has also proven to be an accurate system to capture signals from the forearm muscles in people with motor impairment of the upper limb. However, further research should be conducted using bigger samples, well-defined protocols, comparing with control groups or comparing with other assessment or therapeutic tools, since the studies published so far present a high risk of bias and low level of evidence and grade of recommendation.
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Affiliation(s)
- Selena Marcos-Antón
- International Doctorate School, Rey Juan Carlos University, 28008 Madrid, Spain;
| | - María Dolores Gor-García-Fogeda
- Department of Physical Therapy, Occupational Therapy, Rehabilitation and Physical Medicine, Rey Juan Carlos University, 28922 Alcorcon, Spain;
| | - Roberto Cano-de-la-Cuerda
- Department of Physical Therapy, Occupational Therapy, Rehabilitation and Physical Medicine, Rey Juan Carlos University, 28922 Alcorcon, Spain;
- Correspondence: ; Tel.: +34-914-888-674
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Effects of EMG-Controlled Video Games on the Upper Limb Functionality in Patients with Multiple Sclerosis: A Feasibility Study and Development Description. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:3735979. [PMID: 35449748 PMCID: PMC9017529 DOI: 10.1155/2022/3735979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/27/2022] [Accepted: 02/09/2022] [Indexed: 11/17/2022]
Abstract
Multiple sclerosis (MS) is the most common inflammatory neurological disease in young adults, with a high prevalence worldwide (2.8 million people). To aid in the MS treatment, using VR tools in cognitive and motor rehabilitation of such disease has been growing progressively in the last years. However, the role of VR as a rehabilitative tool in MS treatment is still under debate. This paper explores the effects of VR training using EMG activation in upper limb functionality. An experimental training protocol using video games controlled using an MYO armband sensor was conducted in a sample of patients with MS. Results support the use of EMG-commanded video games as a rehabilitative tool in patients with MS, obtaining favorable outcomes related to upper limb functionality and satisfaction.
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Lambelet C, Temiraliuly D, Siegenthaler M, Wirth M, Woolley DG, Lambercy O, Gassert R, Wenderoth N. Characterization and wearability evaluation of a fully portable wrist exoskeleton for unsupervised training after stroke. J Neuroeng Rehabil 2020; 17:132. [PMID: 33028354 PMCID: PMC7541267 DOI: 10.1186/s12984-020-00749-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 08/24/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Chronic hand and wrist impairment are frequently present following stroke and severely limit independence in everyday life. The wrist orientates and stabilizes the hand before and during grasping, and is therefore of critical importance in activities of daily living (ADL). To improve rehabilitation outcomes, classical therapy could be supplemented by novel therapies that can be applied in unsupervised settings. This would enable more distributed practice and could potentially increase overall training dose. Robotic technology offers new possibilities to address this challenge, but it is critical that devices for independent training are easy and appealing to use. Here, we present the development, characterization and wearability evaluation of a fully portable exoskeleton for active wrist extension/flexion support in stroke rehabilitation. METHODS First we defined the requirements, and based on these, constructed the exoskeleton. We then characterized the device with standardized haptic and human-robot interaction metrics. The exoskeleton is composed of two modules placed on the forearm/hand and the upper arm. These modules weigh 238 g and 224 g, respectively. The forearm module actively supports wrist extension and flexion with a torque up to 3.7 Nm and an angular velocity up to 530 deg/s over a range of 154∘. The upper arm module includes the control electronics and battery, which can power the device for about 125 min in normal use. Special emphasis was put on independent donning and doffing of the device, which was tested via a wearability evaluation in 15 healthy participants and 2 stroke survivors using both qualitative and quantitative methods. RESULTS All participants were able to independently don and doff the device after only 4 practice trials. For healthy participants the donning and doffing process took 61 ±15 s and 24 ±6 s, respectively. The two stroke survivors donned and doffed the exoskeleton in 54 s/22 s and 113 s/32 s, respectively. Usability questionnaires revealed that despite minor difficulties, all participants were positive regarding the device. CONCLUSIONS This study describes an actuated wrist exoskeleton which weighs less than 500 g, and which is easy and fast to don and doff with one hand. Our design has put special emphasis on the donning aspect of robotic devices which constitutes the first barrier a user will face in unsupervised settings. The proposed device is a first and intermediate step towards wearable rehabilitation technologies that can be used independently by the patient and in unsupervised settings.
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Affiliation(s)
- Charles Lambelet
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Damir Temiraliuly
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Marc Siegenthaler
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Marc Wirth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Daniel G. Woolley
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Olivier Lambercy
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Roger Gassert
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
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Comparison of Particle Filter to Established Filtering Methods in Electromyography Biofeedback. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2020.101949] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Lyu M, Chen WH, Ding X, Wang J, Pei Z, Zhang B. Development of an EMG-Controlled Knee Exoskeleton to Assist Home Rehabilitation in a Game Context. Front Neurorobot 2019; 13:67. [PMID: 31507400 PMCID: PMC6718718 DOI: 10.3389/fnbot.2019.00067] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 08/06/2019] [Indexed: 12/13/2022] Open
Abstract
As a leading cause of loss of functional movement, stroke often makes it difficult for patients to walk. Interventions to aid motor recovery in stroke patients should be carried out as a matter of urgency. However, muscle activity in the knee is usually too weak to generate overt movements, which poses a challenge for early post-stroke rehabilitation training. Although electromyography (EMG)-controlled exoskeletons have the potential to solve this problem, most existing robotic devices in rehabilitation centers are expensive, technologically complex, and allow only low training intensity. To address these problems, we have developed an EMG-controlled knee exoskeleton for use at home to assist stroke patients in their rehabilitation. EMG signals of the subject are acquired by an easy-to-don EMG sensor and then processed by a Kalman filter to control the exoskeleton autonomously. A newly-designed game is introduced to improve rehabilitation by encouraging patients' involvement in the training process. Six healthy subjects took part in an initial test of this new training tool. The test showed that subjects could use their EMG signals to control the exoskeleton to assist them in playing the game. Subjects found the rehabilitation process interesting, and they improved their control performance through 20-block training, with game scores increasing from 41.3 ± 15.19 to 78.5 ± 25.2. The setup process was simplified compared to traditional studies and took only 72 s according to test on one healthy subject. The time lag of EMG signal processing, which is an important aspect for real-time control, was significantly reduced to about 64 ms by employing a Kalman filter, while the delay caused by the exoskeleton was about 110 ms. This easy-to-use rehabilitation tool has a greatly simplified training process and allows patients to undergo rehabilitation in a home environment without the need for a therapist to be present. It has the potential to improve the intensity of rehabilitation and the outcomes for stroke patients in the initial phase of rehabilitation.
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Affiliation(s)
- Mingxing Lyu
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Wei-Hai Chen
- College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China
| | - Xilun Ding
- School of Mechanical Engineering and Automation, Beihang University, Beijing, China
| | - Jianhua Wang
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
| | - Zhongcai Pei
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
| | - Baochang Zhang
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
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