Journal article
Comparison of tri-axial accelerometers step-count accuracy in slow walking conditions
Gait & posture, v 53, pp 11-16
01 Mar 2017
PMID: 28064084
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Accelerometers have shown great promise and popularity for monitoring gait. However, the accuracy of accelerometers for gait analysis in slow walking conditions is largely unknown. In this study, we compared the accuracy of three accelerometers recommended for gait analysis - Axivity AX3, APDM Opal, and the Actigraph wGT3X-BT, by holding the step-count algorithm constant. We evaluated device accuracy in four minutes of treadmill walking at the speeds of 0.9m/s, 1.1m/s, and 1.3m/s. We constructed a symbolization of the gait data to count the steps using Piecewise Aggregate Approximation and compared the estimated step counts with observer counted steps from video recordings. Our results highlight the variation between the performance of devices - the Axivity AX3 provides more accurate step counts than the other two devices. In this, we provide evidence for future scientific teams to make decisions on selecting accelerometers which can more accurately measure steps taken at slower walking speeds, and suggest ways to improve the design of algorithms and accelerometers.
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Details
- Title
- Comparison of tri-axial accelerometers step-count accuracy in slow walking conditions
- Creators
- Yuanyuan Feng - University of Maryland, Baltimore CountyChristopher K Wong - University of Maryland, Baltimore CountyVandana Janeja - University of Maryland, Baltimore CountyRavi Kuber - University of Maryland, Baltimore CountyHelena M Mentis - University of Maryland, Baltimore County
- Publication Details
- Gait & posture, v 53, pp 11-16
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Web of Science ID
- WOS:000397688600003
- Scopus ID
- 2-s2.0-85008352578
- Other Identifier
- 991021916914904721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Neurosciences
- Orthopedics
- Sport Sciences