Literature DB >> 29099724

Identifying compensatory movement patterns in the upper extremity using a wearable sensor system.

Rajiv Ranganathan1, Rui Wang, Bo Dong, Subir Biswas.   

Abstract

OBJECTIVE: Movement impairments such as those due to stroke often result in the nervous system adopting atypical movements to compensate for movement deficits. Monitoring these compensatory patterns is critical for improving functional outcomes during rehabilitation. The purpose of this study was to test the feasibility and validity of a wearable sensor system for detecting compensatory trunk kinematics during activities of daily living. APPROACH: Participants with no history of neurological impairments performed reaching and manipulation tasks with their upper extremity, and their movements were recorded by a wearable sensor system and validated using a motion capture system. Compensatory movements of the trunk were induced using a brace that limited range of motion at the elbow. MAIN
RESULTS: Our results showed that the elbow brace elicited compensatory movements of the trunk during reaching tasks but not manipulation tasks, and that a wearable sensor system with two sensors could reliably classify compensatory movements (~90% accuracy). SIGNIFICANCE: These results show the potential of the wearable system to assess and monitor compensatory movements outside of a lab setting.

Entities:  

Mesh:

Year:  2017        PMID: 29099724     DOI: 10.1088/1361-6579/aa9835

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  5 in total

Review 1.  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

2.  Detection of Typical Compensatory Movements during Autonomously Performed Exercises Preventing Low Back Pain (LBP).

Authors:  Asaad Sellmann; Désirée Wagner; Lucas Holtz; Jörg Eschweiler; Christian Diers; Sybele Williams; Catherine Disselhorst-Klug
Journal:  Sensors (Basel)       Date:  2021-12-24       Impact factor: 3.576

3.  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

4.  NE-Motion: Visual Analysis of Stroke Patients Using Motion Sensor Networks.

Authors:  Rodrigo Colnago Contreras; Avinash Parnandi; Bruno Gomes Coelho; Claudio Silva; Heidi Schambra; Luis Gustavo Nonato
Journal:  Sensors (Basel)       Date:  2021-06-30       Impact factor: 3.576

5.  Movement Analysis with Inertial Measurement Unit Sensor After Surgical Treatment for Distal Radius Fractures.

Authors:  Benedetta Zucchi; Massimiliano Mangone; Francesco Agostini; Marco Paoloni; Luisa Petriello; Andrea Bernetti; Valter Santilli; Ciro Villani
Journal:  Biores Open Access       Date:  2020-05-21
  5 in total

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