The development of a gait speed detection system for older adults using video-based processing

© 2019 Association for Computing Machinery. This study aimed to develop the gait speed detection system for measuring the instantaneous walking speed of older adults. The proposed system employed a standard camera 60 Hz and fixed on a tripod with 3-way head to collect the body motion. Besides, the p...

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Main Authors: Teerawat Kamnardsiri, Pattaraporn Khuwuthyakorn, Sirinun Boripuntakul
Format: Conference Proceeding
Published: 2020
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078509077&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/67707
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-677072020-04-02T15:01:45Z The development of a gait speed detection system for older adults using video-based processing Teerawat Kamnardsiri Pattaraporn Khuwuthyakorn Sirinun Boripuntakul Computer Science © 2019 Association for Computing Machinery. This study aimed to develop the gait speed detection system for measuring the instantaneous walking speed of older adults. The proposed system employed a standard camera 60 Hz and fixed on a tripod with 3-way head to collect the body motion. Besides, the proposed system was to assess the validity of instantaneous horizontal speed with the three-dimension motion analysis system. The cross-sectional study was used to design in this study. The proposed system consists of ten steps, which are: (1) Input video, (2) Extraction frames, (3) Calibration of a camera and the capture volume, (4) Colour detection and filling into the body, (5) The human body region detection, (6) Filtering of the foreground regions from image difference, (7) Centroid of the human body detection, (8) Identification of the human body position, (9) Feature tracking of the human speed and (10) Estimation of the human speed. The proposed system employed MATLAB (2015a) with the Computer Vision Toolbox and the Image Processing Toolbox for developing and testing. The fifteen older adults with mean age 67 (SD = 4.19) years performed three walking conditions that comprises: 1) walking at a slow speed, 2) walking at usual speed, and 3) walking at a fast speed. Besides, participants walked along a 10-metre walkway in the motion capture laboratory room. The results demonstrate that the proposed system measures have an excellent correlation with the motion analysis system measures, with correlation coefficients between 0.936 and 0.987. Hence, the proposed system is to be one of the useful tools for assessing instantaneous walking speed among older adults in both clinical and community settings. 2020-04-02T15:01:45Z 2020-04-02T15:01:45Z 2019-09-16 Conference Proceeding 2-s2.0-85078509077 10.1145/3366174.3366190 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078509077&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/67707
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
spellingShingle Computer Science
Teerawat Kamnardsiri
Pattaraporn Khuwuthyakorn
Sirinun Boripuntakul
The development of a gait speed detection system for older adults using video-based processing
description © 2019 Association for Computing Machinery. This study aimed to develop the gait speed detection system for measuring the instantaneous walking speed of older adults. The proposed system employed a standard camera 60 Hz and fixed on a tripod with 3-way head to collect the body motion. Besides, the proposed system was to assess the validity of instantaneous horizontal speed with the three-dimension motion analysis system. The cross-sectional study was used to design in this study. The proposed system consists of ten steps, which are: (1) Input video, (2) Extraction frames, (3) Calibration of a camera and the capture volume, (4) Colour detection and filling into the body, (5) The human body region detection, (6) Filtering of the foreground regions from image difference, (7) Centroid of the human body detection, (8) Identification of the human body position, (9) Feature tracking of the human speed and (10) Estimation of the human speed. The proposed system employed MATLAB (2015a) with the Computer Vision Toolbox and the Image Processing Toolbox for developing and testing. The fifteen older adults with mean age 67 (SD = 4.19) years performed three walking conditions that comprises: 1) walking at a slow speed, 2) walking at usual speed, and 3) walking at a fast speed. Besides, participants walked along a 10-metre walkway in the motion capture laboratory room. The results demonstrate that the proposed system measures have an excellent correlation with the motion analysis system measures, with correlation coefficients between 0.936 and 0.987. Hence, the proposed system is to be one of the useful tools for assessing instantaneous walking speed among older adults in both clinical and community settings.
format Conference Proceeding
author Teerawat Kamnardsiri
Pattaraporn Khuwuthyakorn
Sirinun Boripuntakul
author_facet Teerawat Kamnardsiri
Pattaraporn Khuwuthyakorn
Sirinun Boripuntakul
author_sort Teerawat Kamnardsiri
title The development of a gait speed detection system for older adults using video-based processing
title_short The development of a gait speed detection system for older adults using video-based processing
title_full The development of a gait speed detection system for older adults using video-based processing
title_fullStr The development of a gait speed detection system for older adults using video-based processing
title_full_unstemmed The development of a gait speed detection system for older adults using video-based processing
title_sort development of a gait speed detection system for older adults using video-based processing
publishDate 2020
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078509077&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/67707
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