Characterizing Dynamic Walking Patterns and Detecting Falls with Wearable Sensors Using Gaussian Process Methods.

Kim, Taehwan; Park, Jeongho; Heo, Seongman; Sung, Keehoon; Park, Jooyoung

Kim, Taehwan; Park, Jeongho; Heo, Seongman; Sung, Keehoon; Park, Jooyoung.

Afiliación

Kim T; Department of Control and Instrumentation Engineering, Korea University, Sejong-Ro 2511, Sejong-City 30016, Korea. kteaw0110@korea.ac.kr.
Park J; Department of Control and Instrumentation Engineering, Korea University, Sejong-Ro 2511, Sejong-City 30016, Korea. seanpark0107@korea.ac.kr.
Heo S; Department of Control and Instrumentation Engineering, Korea University, Sejong-Ro 2511, Sejong-City 30016, Korea. smheo@vadas.co.kr.
Sung K; Research Institute of Korean Air Lines Co., Ltd., Daejeon-City 34054, Korea. skhz89@naver.com.
Park J; Department of Control and Instrumentation Engineering, Korea University, Sejong-Ro 2511, Sejong-City 30016, Korea. parkj@korea.ac.kr.

Sensors (Basel) ; 17(5)2017 May 20.

Article en En | MEDLINE | ID: mdl-28531125

Palabras clave

Gaussian process; dimensionality reduction; dynamic model; fall detection; latent feature space; novelty detection; walking; wearable sensors

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2017 Tipo del documento: Article Pais de publicación: Suiza

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