%0 Conference Paper %1 zhu2016computer %A Zhu, Wei %A Anderson, Boyd %A Zhu, Shenggao %A Wang, Ye %B Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility %C New York, NY, USA %D 2016 %I Association for Computing Machinery (ACM) %K computer-vision gait-analysis mobile-camera movement-disorder parkinson-disease real video-analysis %P 121-130 %R 10.1145/2982142.2982156 %T A Computer Vision-Based System for Stride Length Estimation Using a Mobile Phone Camera %U https://doi.org/10.1145/2982142.2982156 %X Conditions such as Parkinson's disease (PD), a chronic neurodegenerative disorder which severely affects the motor system, will be an increasingly common problem for our growing and aging population. Gait analysis is widely used as a noninvasive method for PD diagnosis and assessment. However, current clinical systems for gait analysis usually require highly specialized cameras and lab settings, which are expensive and not scalable. This paper presents a computer vision-based gait analysis system using a camera on a common mobile phone. A simple PVC mat was designed with markers printed on it, on which a subject can walk whilst being recorded by a mobile phone camera. A set of video analysis methods were developed to segment the walking video, detect the mat and feet locations, and calculate gait parameters such as stride length. Experiments showed that stride length measurement has a mean absolute error of 0.62 cm, which is comparable with the "gold standard" walking mat system GAITRite. We also tested our system on Parkinson's disease patients in a real clinical environment. Our system is affordable, portable, and scalable, indicating a potential clinical gait measurement tool for use in both hospitals and the homes of patients. %@ 9781450341240

@inproceedings{zhu2016computer, abstract = {Conditions such as Parkinson's disease (PD), a chronic neurodegenerative disorder which severely affects the motor system, will be an increasingly common problem for our growing and aging population. Gait analysis is widely used as a noninvasive method for PD diagnosis and assessment. However, current clinical systems for gait analysis usually require highly specialized cameras and lab settings, which are expensive and not scalable. This paper presents a computer vision-based gait analysis system using a camera on a common mobile phone. A simple PVC mat was designed with markers printed on it, on which a subject can walk whilst being recorded by a mobile phone camera. A set of video analysis methods were developed to segment the walking video, detect the mat and feet locations, and calculate gait parameters such as stride length. Experiments showed that stride length measurement has a mean absolute error of 0.62 cm, which is comparable with the "gold standard" walking mat system GAITRite. We also tested our system on Parkinson's disease patients in a real clinical environment. Our system is affordable, portable, and scalable, indicating a potential clinical gait measurement tool for use in both hospitals and the homes of patients.}, added-at = {2019-11-14T07:15:17.000+0100}, address = {New York, NY, USA}, author = {Zhu, Wei and Anderson, Boyd and Zhu, Shenggao and Wang, Ye}, biburl = {https://www.bibsonomy.org/bibtex/25442b4d317244220fa5d7943ae787eed/jpmor}, booktitle = {Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility}, doi = {10.1145/2982142.2982156}, institution = {National University of Singapore (NUS)}, interhash = {0d821d500573e0a51eef383c608ac9ea}, intrahash = {5442b4d317244220fa5d7943ae787eed}, isbn = {9781450341240}, keywords = {computer-vision gait-analysis mobile-camera movement-disorder parkinson-disease real video-analysis}, location = {Reno, Nevada, USA}, numpages = {10}, pages = {121-130}, publisher = {Association for Computing Machinery (ACM)}, series = {ASSETS ’16}, timestamp = {2020-10-07T13:36:50.000+0200}, title = {A Computer Vision-Based System for Stride Length Estimation Using a Mobile Phone Camera}, url = {https://doi.org/10.1145/2982142.2982156}, year = 2016 }