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Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review
Martin O'Reilly1,2, Brian Caulfield3,4, Tomas Ward5,6
1School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland. martin.oreilly@insight-centre.org.
Background:
Analysis of lower limb exercises is traditionally completed with four distinct methods: (1) 3D motion capture; (2) depth-camera-based systems; (3) visual analysis from a qualified exercise professional; and (4) self-assessment. Each method is associated with a number of limitations.
Objective:
The aim of this systematic review is to synthesise 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 studies identified through the databases of PubMed, ScienceDirect and Scopus was conducted.
Study Eligibility Criteria:
Articles written in English and published in the last 10 years which investigated 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 into 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. Twenty-six of the 47 included studies were deemed as being of high quality.
Conclusions:
Wearable inertial sensor systems for analysing lower limb exercises is a rapidly growing field of research. Research over the past 10 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.
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