{"title":"基于BSN的地底反力贝叶斯分析","authors":"Benny P. L. Lo, J. Pansiot, Guang-Zhong Yang","doi":"10.1109/BSN.2009.38","DOIUrl":null,"url":null,"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.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"Bayesian Analysis of Sub-plantar Ground Reaction Force with BSN\",\"authors\":\"Benny P. L. Lo, J. Pansiot, Guang-Zhong Yang\",\"doi\":\"10.1109/BSN.2009.38\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":269861,\"journal\":{\"name\":\"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BSN.2009.38\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BSN.2009.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bayesian Analysis of Sub-plantar Ground Reaction Force with BSN
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.
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