DocumentCode
140192
Title
Classification of gait quality for biofeedback to improve heel-to-toe gait
Author
Vadnerkar, Abhishek ; Figueiredo, Sabrina ; Mayo, Nancy E. ; Kearney, Robert E.
Author_Institution
Biomed. Eng. Dept., McGill Univ., Montreal, QC, Canada
fYear
2014
fDate
26-30 Aug. 2014
Firstpage
3626
Lastpage
3629
Abstract
A feature of healthy gait is a clearly defined heel strike upon initial contact of the foot with the ground. However, a common consequence of ageing is deterioration of the heel first nature of gait towards a shuffling gait (flat foot at contact). Physiotherapy can be effective in correcting this but is costly and labour intensive. Gait rehabilitation could be accelerated with home exercise, guided by a biofeedback device that distinguishes between heel first and shuffling gait. This paper describes an algorithm that distinguishes between heel-to-toe gait and shuffling gait on the basis of angular velocity of the foot, using an inertial measurement unit. Measurements were made of normal and abnormal gait and used to develop an algorithm that distinguishes between good and bad steps. Results demonstrate very good algorithm performance, with a classification accuracy at the accuracy-optimal threshold of 92.7% when compared with physiotherapist labels. The sensitivity and specificity at this threshold are 84.4% and 97.5% respectively. These performance metrics suggest that this algorithm is usable in a biofeedback device.
Keywords
gait analysis; patient rehabilitation; accuracy optimal threshold; ageing; biofeedback; foot angular velocity; gait quality; gait rehabilitation; heel strike; heel-to-toe gait; inertial measurement unit; physiotherapy; Accelerometers; Accuracy; Angular velocity; Foot; Integrated circuits; Legged locomotion; Sensitivity;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location
Chicago, IL
ISSN
1557-170X
Type
conf
DOI
10.1109/EMBC.2014.6944408
Filename
6944408
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