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dc.contributor.authorChenen_US
dc.contributor.authorChun-Weien_US
dc.contributor.authorSongen_US
dc.contributor.authorKai-Taien_US
dc.date.accessioned2014-12-16T06:14:24Z-
dc.date.available2014-12-16T06:14:24Z-
dc.date.issued2010-06-22en_US
dc.identifier.govdocG08B021/00zh_TW
dc.identifier.govdocG01C017/38zh_TW
dc.identifier.govdocG01P021/00zh_TW
dc.identifier.govdocG01R013/00zh_TW
dc.identifier.govdocG06F019/00zh_TW
dc.identifier.govdocG08B023/00zh_TW
dc.identifier.govdocG01N037/00zh_TW
dc.identifier.govdocG01C009/00zh_TW
dc.identifier.govdocG01C017/00zh_TW
dc.identifier.govdocG01C019/00zh_TW
dc.identifier.govdocG06F015/00zh_TW
dc.identifier.urihttp://hdl.handle.net/11536/104712-
dc.description.abstractIn the present invention, a multi-person pose recognition system has been developed. This system includes a body pose detection module, a CC2420DBK board and a multi-person pose monitoring software module. The body pose detection module includes a triaxial accelerometer, a Zigbee chip and an 8-bit microcontroller. Several body pose detection modules and the CC2420DBK board form a Zigbee wireless sensor network (WSN). The CC2420DBK board functions as the receiver of the Zigbee WSN and communicates with a robot onboard computer or a host computer through a RS-232 port. The multi-person pose monitoring software monitors and records activities of multiple users simultaneously. The present invention provides a pose recognition algorithm by combining time-domain analysis and wavelet transform analysis. This algorithm has been implemented in the microcontroller of a body pose estimation module. Through the algorithm, the system can recognize seven body poses: falling, standing, sitting, lying, walking, going upstairs and going downstairs.zh_TW
dc.language.isozh_TWen_US
dc.titleMulti-person pose recognition system using a zigbee wireless sensor networkzh_TW
dc.typePatentsen_US
dc.citation.patentcountryUSAzh_TW
dc.citation.patentnumber07742894zh_TW
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