Literature DB >> 20558567

Real-time kinematic, temporospatial, and kinetic biofeedback during gait retraining in patients: a systematic review.

Jeremiah J Tate1, Clare E Milner.   

Abstract

BACKGROUND: Biofeedback has been used in rehabilitation settings for gait retraining.
PURPOSE: The purpose of this review was to summarize and synthesize the findings of studies involving real-time kinematic, temporospatial, and kinetic biofeedback. The goal was to provide a general overview of the effectiveness of these forms of biofeedback in treating gait abnormalities. DATA SOURCES: Articles were identified through searches of the following databases: MEDLINE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and Cochrane Central Register for Controlled Trials. All searches were limited to the English language and encompassed the period from 1965 to November 2007. STUDY SELECTION: Titles and abstracts were screened to identify studies that met the following requirements: the study included the use of kinematic, temporospatial, or kinetic biofeedback during gait training, and the population of interest showed abnormal movement patterns as a result of a pathology or injury. DATA EXTRACTION: All articles that met the inclusion criteria were assessed by use of the Methodological Index for Nonrandomized Studies. DATA SYNTHESIS: Seven articles met the inclusion criteria and were included in the review. Effect sizes were calculated for the primary outcome variables for all studies that provided enough data. Effect sizes generally suggested moderate to large treatment effects for all methods of biofeedback during practice. LIMITATIONS: Several of the studies lacked adequate randomization; therefore, readers should exercise caution when interpreting authors' conclusions.
CONCLUSIONS: Each biofeedback method appeared to result in moderate to large treatment effects immediately after treatment. However, it is unknown whether the effects were maintained. Future studies should ensure adequate randomization of participants and implementation of motor learning concepts and should include retention testing to assess the long-term success of biofeedback and outcome measures capable of demonstrating coordinative changes in gait and improvement in function.

Entities:  

Mesh:

Year:  2010        PMID: 20558567     DOI: 10.2522/ptj.20080281

Source DB:  PubMed          Journal:  Phys Ther        ISSN: 0031-9023


  32 in total

1.  Characterization of unexpected postural changes during robot-assisted gait training in paraplegic patients.

Authors:  S Koyama; S Tanabe; E Saitoh; S Hirano; Y Shimizu; M Katoh; A Uno; T Takemitsu
Journal:  Spinal Cord       Date:  2015-08-11       Impact factor: 2.772

Review 2.  How New Technology Is Improving Physical Therapy.

Authors:  Johnny G Owens; Michelle R Rauzi; Andrew Kittelson; Jeremy Graber; Michael J Bade; Julia Johnson; Dustin Nabhan
Journal:  Curr Rev Musculoskelet Med       Date:  2020-04

3.  Role of body-worn movement monitor technology for balance and gait rehabilitation.

Authors:  Fay Horak; Laurie King; Martina Mancini
Journal:  Phys Ther       Date:  2014-12-11

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

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

5.  Gait modification to treat knee osteoarthritis.

Authors:  Benjamin J Fregly
Journal:  HSS J       Date:  2011-12-28

6.  A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli.

Authors:  Matthew J Leineweber; Sam Shi; Jan Andrysek
Journal:  J Vis Exp       Date:  2016-08-02       Impact factor: 1.355

7.  Use of visual and proprioceptive feedback to improve gait speed and spatiotemporal symmetry following chronic stroke: a case series.

Authors:  Michael D Lewek; Jeff Feasel; Erin Wentz; Frederick P Brooks; Mary C Whitton
Journal:  Phys Ther       Date:  2012-01-06

8.  Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback.

Authors:  Federica Tamburella; Juan C Moreno; Diana Sofía Herrera Valenzuela; Iolanda Pisotta; Marco Iosa; Febo Cincotti; Donatella Mattia; José L Pons; Marco Molinari
Journal:  J Neuroeng Rehabil       Date:  2019-07-23       Impact factor: 4.262

9.  Movement pattern biofeedback training after total knee arthroplasty: Randomized clinical trial protocol.

Authors:  Michael J Bade; Jesse C Christensen; Joseph A Zeni; Cory L Christiansen; Michael R Dayton; Jeri E Forster; Victor A Cheuy; Jennifer E Stevens-Lapsley
Journal:  Contemp Clin Trials       Date:  2020-03-12       Impact factor: 2.226

10.  A Dual-Learning Paradigm Simultaneously Improves Multiple Features of Gait Post-Stroke.

Authors:  Kendra M Cherry-Allen; Matthew A Statton; Pablo A Celnik; Amy J Bastian
Journal:  Neurorehabil Neural Repair       Date:  2018-08-07       Impact factor: 3.919

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