Literature DB >> 29078743

Biofeedback vs. game scores for reducing trunk compensation after stroke: a randomized crossover trial.

Bulmaro A Valdés1, H F Machiel Van der Loos1.   

Abstract

Background Compensatory movements are commonly employed by stroke survivors, and their use can have negative effects on motor recovery. Current practices to reduce them rely on strapping a person to a chair. The use of technology to substitute or supplement this methodology has not being thoroughly investigated. Objective To compare the use of Scores + Visual + Force and Visual + Force feedback for reducing trunk compensation. Methods Fourteen hemiparetic stroke survivors performed bimanual reaching movements while receiving feedback on trunk compensation. Participants held onto two robotic arms and performed movements in the anterior/posterior direction toward a target displayed on a monitor. A motion-tracking camera tracked trunk compensation; the robots provided force feedback; the monitor displayed the visual feedback and scores. Kinematic variables, a post-test questionnaire, and system usability were analyzed. Results Both conditions reduced trunk compensation from baseline: Scores + Visual + Force: 51.7% (40.8), p = 0.000; Visual + Force: 55.2% (40.9), p = 0.000. No statistically significant difference was found between modalities. Secondary outcome measures were not improved. Most participants would like to receive game scores to reduce trunk compensation, and the usability of the system was rated "Good." Conclusions Multimodal feedback about stroke survivors' trunk compensation levels resulted in reduced trunk displacement. No difference between feedback modalities was obtained. The positive effects of including game scores might not have been observed in a short-term intervention. Longer studies should investigate if the use of game scores could result in trunk compensation improvements when compared to trunk restraint strategies. Clinical Trial Registration Clinicaltrials.gov, NCT02912923, https://clinicaltrials.gov/ct2/show/NCT02912923?term=reaching+in+stroke&rank=2 .

Entities:  

Keywords:  Feedback; hemiplegia; robotics; stroke rehabilitation; trunk compensation; upper extremity; virtual rehabilitation

Mesh:

Year:  2017        PMID: 29078743     DOI: 10.1080/10749357.2017.1394633

Source DB:  PubMed          Journal:  Top Stroke Rehabil        ISSN: 1074-9357            Impact factor:   2.119


  11 in total

Review 1.  Effectiveness of modified constraint-induced movement therapy for upper limb function intervention following stroke: A brief review.

Authors:  Manting Cao; Xia Li
Journal:  Sports Med Health Sci       Date:  2021-08-10

Review 2.  Technology-Based Compensation Assessment and Detection of Upper Extremity Activities of Stroke Survivors: Systematic Review.

Authors:  Xiaoyi Wang; Yan Fu; Bing Ye; Jessica Babineau; Yong Ding; Alex Mihailidis
Journal:  J Med Internet Res       Date:  2022-06-13       Impact factor: 7.076

3.  Robotics-assisted visual-motor training influences arm position sense in three-dimensional space.

Authors:  Bulmaro A Valdés; Mahta Khoshnam; Jason L Neva; Carlo Menon
Journal:  J Neuroeng Rehabil       Date:  2020-07-14       Impact factor: 4.262

4.  Investigating the feasibility and acceptability of real-time visual feedback in reducing compensatory motions during self-administered stroke rehabilitation exercises: A pilot study with chronic stroke survivors.

Authors:  Shayne Lin; Jotvarinder Mann; Avril Mansfield; Rosalie H Wang; Jocelyn E Harris; Babak Taati
Journal:  J Rehabil Assist Technol Eng       Date:  2019-03-18

5.  The Effect of Animal-Assisted Therapy on the State of Patients' Health After a Stroke: A Pilot Study.

Authors:  Kristýna Machová; Radka Procházková; Michal Říha; Ivona Svobodová
Journal:  Int J Environ Res Public Health       Date:  2019-09-06       Impact factor: 3.390

6.  Detecting compensatory movements of stroke survivors using pressure distribution data and machine learning algorithms.

Authors:  Siqi Cai; Guofeng Li; Xiaoya Zhang; Shuangyuan Huang; Haiqing Zheng; Ke Ma; Longhan Xie
Journal:  J Neuroeng Rehabil       Date:  2019-11-04       Impact factor: 4.262

7.  Online compensation detecting for real-time reduction of compensatory motions during reaching: a pilot study with stroke survivors.

Authors:  Siqi Cai; Xuyang Wei; Enze Su; Weifeng Wu; Haiqing Zheng; Longhan Xie
Journal:  J Neuroeng Rehabil       Date:  2020-04-28       Impact factor: 4.262

8.  Inertial-Robotic Motion Tracking in End-Effector-Based Rehabilitation Robots.

Authors:  Arne Passon; Thomas Schauer; Thomas Seel
Journal:  Front Robot AI       Date:  2020-11-27

9.  A Wearable System Composed of FBG-Based Soft Sensors for Trunk Compensatory Movements Detection in Post-Stroke Hemiplegic Patients.

Authors:  Daniela Lo Presti; Martina Zaltieri; Marco Bravi; Michelangelo Morrone; Michele Arturo Caponero; Emiliano Schena; Silvia Sterzi; Carlo Massaroni
Journal:  Sensors (Basel)       Date:  2022-02-11       Impact factor: 3.576

10.  Effects of Noisy Galvanic Vestibular Stimulation During a Bimanual Tracking Robotic Task.

Authors:  Bulmaro A Valdés; Carlo Menon
Journal:  Front Neurosci       Date:  2019-10-25       Impact factor: 4.677

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