Literature DB >> 25570613

The use of inertial sensors for the classification of rehabilitation exercises.

Oonagh Giggins, Kevin T Sweeney, Brian Caulfield.   

Abstract

The benefits of exercise in rehabilitation after orthopaedic surgery or following a musculoskeletal injury has been widely established. Within a hospital or clinical environment, adherence levels to rehabilitation exercise programs are high due to the supervision of the patient during the rehabilitation process. However, adherence levels drop significantly when patients are asked to perform the program at home. This paper describes the use of simple inertial sensors for the purpose of developing a biofeedback system to monitor adherence to rehabilitation programs. The results show that a single sensor can accurately distinguish between seven commonly prescribed rehabilitation exercises with accuracies between 93% and 95%. Results also show that the use of multiple sensor units does not significantly improve results therefore suggesting that a single sensor unit can be used as an input to an exercise biofeedback system.

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Year:  2014        PMID: 25570613     DOI: 10.1109/EMBC.2014.6944245

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  7 in total

1.  Reliability, Validity and Utility of Inertial Sensor Systems for Postural Control Assessment in Sport Science and Medicine Applications: A Systematic Review.

Authors:  William Johnston; Martin O'Reilly; Rob Argent; Brian Caulfield
Journal:  Sports Med       Date:  2019-05       Impact factor: 11.136

Review 2.  Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review.

Authors:  Martin O'Reilly; Brian Caulfield; Tomas Ward; William Johnston; Cailbhe Doherty
Journal:  Sports Med       Date:  2018-05       Impact factor: 11.136

3.  Continuous Monitoring of Patient Mobility for 18 Months Using Inertial Sensors following Traumatic Knee Injury: A Case Study.

Authors:  Arne Mueller; Holger Hoefling; Timur Nuritdinow; Nicholas Holway; Matthias Schieker; Martin Daumer; Ieuan Clay
Journal:  Digit Biomark       Date:  2018-08-02

Review 4.  A review of computational approaches for evaluation of rehabilitation exercises.

Authors:  Yalin Liao; Aleksandar Vakanski; Min Xian; David Paul; Russell Baker
Journal:  Comput Biol Med       Date:  2020-03-04       Impact factor: 4.589

5.  Patient Involvement With Home-Based Exercise Programs: Can Connected Health Interventions Influence Adherence?

Authors:  Rob Argent; Ailish Daly; Brian Caulfield
Journal:  JMIR Mhealth Uhealth       Date:  2018-03-01       Impact factor: 4.773

6.  Detection of Low Back Physiotherapy Exercises With Inertial Sensors and Machine Learning: Algorithm Development and Validation.

Authors:  Abdalrahman Alfakir; Colin Arrowsmith; David Burns; Helen Razmjou; Michael Hardisty; Cari Whyne
Journal:  JMIR Rehabil Assist Technol       Date:  2022-08-23

Review 7.  Feedback Design in Targeted Exercise Digital Biofeedback Systems for Home Rehabilitation: A Scoping Review.

Authors:  Louise Brennan; Enrique Dorronzoro Zubiete; Brian Caulfield
Journal:  Sensors (Basel)       Date:  2019-12-28       Impact factor: 3.576

  7 in total

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