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Wearable inertial sensor systems for lower limb exercise detection and evaluation: a systematic review

O'Reilly, Martin orcid logoORCID: 0000-0003-2425-5393, Caulfield, Brian orcid logoORCID: 0000-0003-0290-9587, Ward, Tomás E. orcid logoORCID: 0000-0002-6173-6607, Johnson, William orcid logoORCID: 0000-0003-0525-6577 and Doherty, Cailbhe orcid logoORCID: 0000-0002-5284-856X (2018) Wearable inertial sensor systems for lower limb exercise detection and evaluation: a systematic review. Sports Medicine, 48 (5). pp. 1221-1246. ISSN 0112-1642

Background. Analysis of lower limb exercises is traditionally completed with four distinct methods (i) 3D motion capture; (ii) depth-camera based systems (iii) visual analysis from a qualified exercise professional; (iv) self-assessment. Each method is associated with a number of limitations. Objective. The aim of this systematic review is to synthesize and evaluate studies which have investigated the capacity for inertial measurement unit (IMU) technologies to assess movement quality in lower limb exercises. Data Sources A systematic review of PubMed, ScienceDirect and Scopus was conducted. Study Eligibility Criteria. Articles written in English and published in the last 10 years which contained an IMU system for the analysis of repetition-based targeted lower limb exercises were included. Study Appraisal and Synthesis Methods. The quality of included studies was measured using an adapted version of the STROBE assessment criteria for cross-sectional studies. The studies were categorised in to three groupings: exercise detection, movement classification or measurement validation. Each study was then qualitatively summarised. Results. From the 2452 articles that were identified with the search strategies, 47 papers are included in this review. Conclusions. Wearable inertial sensor systems for analysing lower limb exercises are a rapidly growing technology. Research over the past ten years has predominantly focused on validating measurements that the systems produce and classifying users’ exercise quality. There have been very few user evaluation studies and no clinical trials in this field to date.
Item Type:Article (Published)
Subjects:Engineering > Biomedical engineering
DCU Faculties and Centres:Research Institutes and Centres > INSIGHT Centre for Data Analytics
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Official URL:https://doi.org/10.1007/s40279-018-0878-4
Copyright Information:© 2018 Springer. The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Irish Research Council as part of a Postgraduate Enterprise Partnership Scheme with Shimmer (EPSPG/2013/574), Science Foundation Ireland under their grant for the Insight Centre for Data Analytics (SFI/12/RC/2289)
ID Code:22415
Deposited On:02 Jul 2018 11:11 by Tomas Ward . Last Modified 24 Jan 2019 16:06

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