Botros, Angela; Gyger, Nathan; Schütz, Narayan; Single, Michael; Nef, Tobias; Gerber, Stephan M. (2021). Contactless Gait Assessment in Home-like Environments. Sensors, 21(18) MDPI 10.3390/s21186205
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Botros__2021__Contactless_Gait_Assessment_in_Home-like_Environments.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (3MB) | Preview |
Gait analysis is an important part of assessments for a variety of health conditions, specifically neurodegenerative diseases. Currently, most methods for gait assessment are based on manual scoring of certain tasks or restrictive technologies. We present an unobtrusive sensor system based on light detection and ranging sensor technology for use in home-like environments. In our evaluation, we compared six different gait parameters, based on recordings from 25 different people performing eight different walks each, resulting in 200 unique measurements. We compared the proposed sensor system against two state-of-the art technologies, a pressure mat and a set of inertial measurement unit sensors. In addition to test usability and long-term measurement, multi-hour recordings were conducted. Our evaluation showed very high correlation (r>0.95) with the gold standards across all assessed gait parameters except for cycle time (r=0.91). Similarly, the coefficient of determination was high (R2>0.9) for all gait parameters except cycle time. The highest correlation was achieved for stride length and velocity (r≥0.98,R2≥0.95). Furthermore, the multi-hour recordings did not show the systematic drift of measurements over time. Overall, the unobtrusive gait measurement system allows for contactless, highly accurate long- and short-term assessments of gait in home-like environments.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology 10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research 10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Gerontechnology and Rehabilitation |
Graduate School: |
Graduate School for Cellular and Biomedical Sciences (GCB) |
UniBE Contributor: |
Botros, Angela Amira, Gyger, Nathan Thibault, Schütz, Narayan, Single, Michael Andreas, Nef, Tobias, Gerber, Stephan Moreno |
Subjects: |
500 Science > 570 Life sciences; biology 600 Technology > 610 Medicine & health 600 Technology > 620 Engineering |
ISSN: |
1424-8220 |
Publisher: |
MDPI |
Language: |
English |
Submitter: |
Aileen Charlotte Naef |
Date Deposited: |
15 Oct 2021 10:45 |
Last Modified: |
07 Aug 2024 15:45 |
Publisher DOI: |
10.3390/s21186205 |
PubMed ID: |
34577412 |
BORIS DOI: |
10.48350/159764 |
URI: |
https://boris.unibe.ch/id/eprint/159764 |
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