Title :
Enhanced Classification of Abnormal Gait Using BSN and Depth
Author :
Wong, Charence ; McKeague, Stephen ; Correa, Javier ; Liu, Jindong ; Yang, Guang-Zhong
Author_Institution :
Hamlyn Centre, Imperial Coll. London, London, UK
Abstract :
Changes in gait can be caused by a wide range of health complications. As deviations in gait may be an indicator of deteriorating health, abnormalities can be used as a surrogate measure for detecting the onset of certain symptoms. Previous studies have demonstrated the value of wearable sensing for gait analysis. This paper demonstrates the added value of using a depth vision sensor combined with wearable sensors for gait analysis. It also presents a method for extracting a robust set of depth features. The preliminary results from a simulated homecare environment using a three-layer artificial neural network classifier demonstrate the advantages of using a depth sensor for gait analysis.
Keywords :
biomedical equipment; body sensor networks; gait analysis; image sensors; medical disorders; abnormal gait; body sensor networks; depth vision sensor; enhanced classification; gait analysis; simulated homecare environment; three-layer artificial neural network classifier; wearable sensors; Biomedical monitoring; Cameras; Feature extraction; Legged locomotion; Robot vision systems; Vectors; Body Sensor Networks; depth camera; gait analysis;
Conference_Titel :
Wearable and Implantable Body Sensor Networks (BSN), 2012 Ninth International Conference on
Conference_Location :
London
Print_ISBN :
978-1-4673-1393-3
DOI :
10.1109/BSN.2012.26
