Literature DB >> 9473993

Electromyographic biofeedback to improve lower extremity function after stroke: a meta-analysis.

J D Moreland1, M A Thomson, A R Fuoco.   

Abstract

OBJECTIVE: To examine the efficacy of electromyographic (EMG) biofeedback compared with conventional physiotherapy for improving lower extremity function in stroke patients. DATA SOURCES: A literature search covering the years 1976 to 1995 in MEDLINE, CINAHL, and EXCERPTA MEDICA. STUDY SELECTION: Studies of adults after stroke, in which the treatment group received biofeedback alone or with conventional physical therapy and the control group received conventional physical therapy. Outcomes included functional measures related to the lower extremity. The study design criterion was that all must be randomized controlled trials. DATA EXTRACTION: Study quality was assessed independently by two observers-using eight criteria. Data for analysis were extracted by two observers to ensure accuracy. DATA SYNTHESIS: For outcomes that were analyzed in more than one study, meta-analyses were done. Seventy-nine studies were identified as potentially relevant and eight studies met the selection criteria. The mean effect sizes were: for ankle dorsiflexion muscle strength, 1.17 (95% CI, .50-1.85; p = .0006); for gait quality, .48 (95% CI, -.06-1.01; p = .08); for ankle range of motion, .07 (95% CI, -.42-0.57; p = .78); for ankle angle during gait, .52 (95% CI, -.18-1.21; p = .14); for stride length, .09 (95% CI, -.56-.73; p = .80); and for gait speed, .31 (95% CI, -.16-.78; p = .20).
CONCLUSIONS: The results indicate that EMG biofeedback is superior to conventional therapy alone for improving ankle dorsiflexion muscle strength.

Entities:  

Mesh:

Year:  1998        PMID: 9473993     DOI: 10.1016/s0003-9993(98)90289-1

Source DB:  PubMed          Journal:  Arch Phys Med Rehabil        ISSN: 0003-9993            Impact factor:   3.966


  10 in total

1.  The influence of different intermittent myofeedback training schedules on learning relaxation of the trapezius muscle while performing a gross-motor task.

Authors:  G E Voerman; L Sandsjö; M M R Vollenbroek-Hutten; C G M Groothuis-Oudshoorn; H J Hermens
Journal:  Eur J Appl Physiol       Date:  2004-07-01       Impact factor: 3.078

2.  Recent developments in biofeedback for neuromotor rehabilitation.

Authors:  He Huang; Steven L Wolf; Jiping He
Journal:  J Neuroeng Rehabil       Date:  2006-06-21       Impact factor: 4.262

3.  Movement retraining using real-time feedback of performance.

Authors:  Michael Anthony Hunt
Journal:  J Vis Exp       Date:  2013-01-17       Impact factor: 1.355

Review 4.  Interventions for improving upper limb function after stroke.

Authors:  Alex Pollock; Sybil E Farmer; Marian C Brady; Peter Langhorne; Gillian E Mead; Jan Mehrholz; Frederike van Wijck
Journal:  Cochrane Database Syst Rev       Date:  2014-11-12

5.  Biofeedback for robotic gait rehabilitation.

Authors:  Lars Lünenburger; Gery Colombo; Robert Riener
Journal:  J Neuroeng Rehabil       Date:  2007-01-23       Impact factor: 4.262

Review 6.  What is the evidence for physical therapy poststroke? A systematic review and meta-analysis.

Authors:  Janne Marieke Veerbeek; Erwin van Wegen; Roland van Peppen; Philip Jan van der Wees; Erik Hendriks; Marc Rietberg; Gert Kwakkel
Journal:  PLoS One       Date:  2014-02-04       Impact factor: 3.240

7.  The effect of surface electromyography biofeedback on the activity of extensor and dorsiflexor muscles in elderly adults: a randomized trial.

Authors:  Ana Belén Gámez; Juan José Hernandez Morante; José Luis Martínez Gil; Francisco Esparza; Carlos Manuel Martínez
Journal:  Sci Rep       Date:  2019-09-11       Impact factor: 4.379

Review 8.  EMG biofeedback for the recovery of motor function after stroke.

Authors:  H Woodford; C Price
Journal:  Cochrane Database Syst Rev       Date:  2007-04-18

9.  Practice Variability Combined with Task-Oriented Electromyographic Biofeedback Enhances Strength and Balance in People with Chronic Stroke.

Authors:  Peih-Ling Tsaih; Ming-Jang Chiu; Jer-Junn Luh; Yea-Ru Yang; Jiu-Jenq Lin; Ming-Hsia Hu
Journal:  Behav Neurol       Date:  2018-11-26       Impact factor: 3.342

10.  Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment.

Authors:  Philipp Müller; Antonio J Del Ama; Juan C Moreno; Thomas Schauer
Journal:  J Neuroeng Rehabil       Date:  2020-02-28       Impact factor: 4.262

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.