Literature DB >> 17413538

Electromyography-controlled exoskeletal upper-limb-powered orthosis for exercise training after stroke.

Joel Stein1, Kailas Narendran, John McBean, Kathryn Krebs, Richard Hughes.   

Abstract

OBJECTIVE: Robot-assisted exercise shows promise as a means of providing exercise therapy for weakness that results from stroke or other neurological conditions. Exoskeletal or "wearable" robots can, in principle, provide therapeutic exercise and/or function as powered orthoses to help compensate for chronic weakness. We describe a novel electromyography (EMG)-controlled exoskeletal robotic brace for the elbow (the active joint brace) and the results of a pilot study conducted using this brace for exercise training in individuals with chronic hemiparesis after stroke.
DESIGN: Eight stroke survivors with severe chronic hemiparesis were enrolled in this pilot study. One subject withdrew from the study because of scheduling conflicts. A second subject was unable to participate in the training protocol because of insufficient surface EMG activity to control the active joint brace. The six remaining subjects each underwent 18 hrs of exercise training using the device for a period of 6 wks. Outcome measures included the upper-extremity component of the Fugl-Meyer scale and the modified Ashworth scale of muscle hypertonicity.
RESULTS: Analysis revealed that the mean upper-extremity component of the Fugl-Meyer scale increased from 15.5 (SD 3.88) to 19 (SD 3.95) (P = 0.04) at the conclusion of training for the six subjects who completed training. Combined (summated) modified Ashworth scale for the elbow flexors and extensors improved from 4.67 (+/-1.2 SD) to 2.33 (+/-0.653 SD) (P = 0.009) and improved for the entire upper limb as well. All subjects tolerated the device, and no complications occurred.
CONCLUSION: EMG-controlled powered elbow orthoses can be successfully controlled by severely impaired hemiparetic stroke survivors. This technique shows promise as a new modality for assisted exercise training after stroke.

Entities:  

Mesh:

Year:  2007        PMID: 17413538     DOI: 10.1097/PHM.0b013e3180383cc5

Source DB:  PubMed          Journal:  Am J Phys Med Rehabil        ISSN: 0894-9115            Impact factor:   2.159


  29 in total

1.  Subject-specific myoelectric pattern classification of functional hand movements for stroke survivors.

Authors:  Sang Wook Lee; Kristin M Wilson; Blair A Lock; Derek G Kamper
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-09-27       Impact factor: 3.802

2.  Self-powered robots to reduce motor slacking during upper-extremity rehabilitation: a proof of concept study.

Authors:  Edward P Washabaugh; Emma Treadway; R Brent Gillespie; C David Remy; Chandramouli Krishnan
Journal:  Restor Neurol Neurosci       Date:  2018       Impact factor: 2.406

3.  Current Trends in Robot-Assisted Upper-Limb Stroke Rehabilitation: Promoting Patient Engagement in Therapy.

Authors:  Amy A Blank; James A French; Ali Utku Pehlivan; Marcia K O'Malley
Journal:  Curr Phys Med Rehabil Rep       Date:  2014-09

4.  Portable Myoelectric Brace Use Increases Upper Extremity Recovery and Participation But Does Not Impact Kinematics in Chronic, Poststroke Hemiparesis.

Authors:  Nienke W Willigenburg; Michael P McNally; Timothy E Hewett; Stephen J Page
Journal:  J Mot Behav       Date:  2016-10-17       Impact factor: 1.328

5.  Study of stability of time-domain features for electromyographic pattern recognition.

Authors:  Dennis Tkach; He Huang; Todd A Kuiken
Journal:  J Neuroeng Rehabil       Date:  2010-05-21       Impact factor: 4.262

6.  Surface EMG pattern recognition for real-time control of a wrist exoskeleton.

Authors:  Zeeshan O Khokhar; Zhen G Xiao; Carlo Menon
Journal:  Biomed Eng Online       Date:  2010-08-26       Impact factor: 2.819

Review 7.  Rehabilitation robotics.

Authors:  H I Krebs; B T Volpe
Journal:  Handb Clin Neurol       Date:  2013

8.  The effect of involuntary motor activity on myoelectric pattern recognition: a case study with chronic stroke patients.

Authors:  Xu Zhang; Yun Li; Xiang Chen; Guanglin Li; William Zev Rymer; Ping Zhou
Journal:  J Neural Eng       Date:  2013-07-17       Impact factor: 5.379

Review 9.  Technology-assisted training of arm-hand skills in stroke: concepts on reacquisition of motor control and therapist guidelines for rehabilitation technology design.

Authors:  Annick A A Timmermans; Henk A M Seelen; Richard D Willmann; Herman Kingma
Journal:  J Neuroeng Rehabil       Date:  2009-01-20       Impact factor: 4.262

Review 10.  Review of control strategies for robotic movement training after neurologic injury.

Authors:  Laura Marchal-Crespo; David J Reinkensmeyer
Journal:  J Neuroeng Rehabil       Date:  2009-06-16       Impact factor: 4.262

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.