The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review
Abstract
After decades of evolution, measuring instruments for quantitative gait analysis have become an important clinical tool for assessing pathologies manifested by gait abnormalities. However, such instruments tend to be expensive and require expert operation and maintenance besides their high cost, thus limiting them to only a small number of specialized centers. Consequently, gait analysis in most clinics today still relies on observation-based assessment. Recent advances in wearable sensors, especially inertial body sensors, have opened up a promising future for gait analysis. Not only can these sensors be more easily adopted in clinical diagnosis and treatment procedures than their current counterparts, but they can also monitor gait continuously outside clinics - hence providing seamless patient analysis from clinics to free-living environments. The purpose of this paper is to provide a systematic review of current techniques for quantitative gait analysis and to propose key metrics for evaluating both existing and emerging methods for qualifying the gait features extracted from wearable sensors. It aims to highlight key advances in this rapidly evolving research field and outline potential future directions for both research and clinical applications.
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Cites
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Cited by
Wade, L., Needham, L., McGuigan, P., & Bilzon, J. (2022) · PeerJ · doi:10.7717/peerj.12995 · Cited by 384
Wearable sensor-based real-time gait detection: A systematic review
Prasanth, H., Caban, M., Keller, U., Courtine, G., Ijspeert, A., Vallery, H., & von Zitzewitz, J. (2021) · Sensors · doi:10.3390/s21082727 · Cited by 348
Internet of things (IoT) applications for elderly care: a reflective review
Tun, S. Y. Y., Madanian, S., & Mirza, F. (2021) · Aging Clinical and Experimental Research · doi:10.1007/s40520-020-01545-9 · Cited by 266
IMU-Based Monitoring for Assistive Diagnosis and Management of IoHT: A Review
Bo, F., Yerebakan, M., Dai, Y., Wang, W., Li, J., Hu, B., & Gao, S. (2022) · Healthcare · doi:10.3390/healthcare10071210 · Cited by 35
Microphone Mechanomyography Sensors for Movement Analysis and Identification
Paszkiewicz, F. P., Wilson, S., Oddsson, M., McGregor, A. H., Alexandersson, A., Huo, W., & Vaidyanathan, R. (2022) · 2022 International Conference on Advanced Robotics and Mechatronics (ICARM) · doi:10.1109/icarm54641.2022.9959672 · Cited by 3
Metadata
- Authors
- Chen, S., Lach, J., Lo, B., & Yang, G.-Z.
- Venue
- IEEE Journal of Biomedical and Health Informatics
- Published
- 2016-11
- Volume
- 20
- Issue
- 6
- Pages
- 1521-1537
- ISSN
- 2168-2194 (ISSN-L)
- 2168-2208
- OpenAlex
- W2560253279
- Cited by
- 443
- References
- 5
- FWCI
- 2.21
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chen, S., Lach, J., Lo, B., & Yang, G.-Z. (2016). Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review. IEEE Journal of Biomedical and Health Informatics. https://doi.org/10.1109/jbhi.2016.2608720
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