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

fYear

2009

fDate

3-5 June 2009

Firstpage

133

Lastpage

137

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/BSN.2009.38

Filename

5226902