DC Field | Value | Language |
---|---|---|
dc.contributor.author | 백종훈 | - |
dc.contributor.author | 이기혁 | - |
dc.date.accessioned | 2013-03-18T20:29:37Z | - |
dc.date.available | 2013-03-18T20:29:37Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2003-08-01 | - |
dc.identifier.citation | 대한전자공학회 2003년도 하계종합학술대회, v., no., pp. - | - |
dc.identifier.uri | http://hdl.handle.net/10203/152180 | - |
dc.description.abstract | Estimation of human motion states is important enabling technologies for realizing a pervasive computing environment. In this paper, an improved method fur estimating human motion state from accelerometer data is introduced. Our method fur estimating human motion state utilizes various statistics of accelerometer data, such as mean, standard variation, skewness, kurtosis, eccentricity, as features for classification, and therefore is expected to be more robust than other existing methods that rely on only a few simple statistics. A series of experiments fur testing the effectiveness of the proposed method has been performed, and its result is presented. | - |
dc.language | KOR | - |
dc.title | 사용자 운동 상태 추정을 위한 가속도센서 신호처리 기술 | - |
dc.title.alternative | Accelerometer Signal Processing for User Activity Detection | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 대한전자공학회 2003년도 하계종합학술대회 | - |
dc.identifier.conferencecountry | South Korea | - |
dc.identifier.conferencecountry | South Korea | - |
dc.contributor.localauthor | 이기혁 | - |
dc.contributor.nonIdAuthor | 백종훈 | - |
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