Title :
Bayesian Analysis of Sub-plantar Ground Reaction Force with BSN
Author :
Lo, Benny ; Pansiot, Julien ; Yang, Guang-Zhong
Author_Institution :
Dept. of Comput., Imperial Coll. London, London, UK
Abstract :
The assessment of Ground Reaction Forces (GRF) is important for gait analysis for sports, pathological gaits and rehabilitation. To capture GRF, force plates and foot pressure insoles are commonly used. Due to cost and portability issues, such systems are mostly limited to lab-based studies. Long-term, continuous and pervasive measurement of GRF is not feasible. This paper presents a novel concept of using an ear-worn sensor for pervasive gait analysis. By emulating the human vestibular system, the bio-inspired design sensor effectively captures the shock wave generated by the GRF. A hierarchical Bayesian network is developed to estimate the plantar force distribution from the ear sensor signals. The accuracy of the ear sensor for detecting GRF is demonstrated by comparing the results with a high-accuracy commercial foot pressure insole system.
Keywords :
belief networks; biomedical measurement; gait analysis; patient rehabilitation; Bayesian network; gait analysis; human vestibular system; pathological gaits; rehabilitation; sports; subplantar ground reaction force; Bayesian methods; Biosensors; Costs; Ear; Foot; Force sensors; Humans; Pathology; Sensor systems; Shock waves; Bayesian Network; Biomechanics; Gait Analysis; Ground Reaction Force;
Conference_Titel :
Wearable and Implantable Body Sensor Networks, 2009. BSN 2009. Sixth International Workshop on
Conference_Location :
Berkeley, CA
Print_ISBN :
978-0-7695-3644-6
DOI :
10.1109/BSN.2009.38
