Cong-Cong Zhou, C. Tu, Yun Gao, Fei-Xiang Wang, Hong-Wei Gong, Ping Lian, Cheng He, Xuesong Ye
{"title":"一种低功耗,无线,手腕佩戴设备,用于长时间心率监测和跌倒检测","authors":"Cong-Cong Zhou, C. Tu, Yun Gao, Fei-Xiang Wang, Hong-Wei Gong, Ping Lian, Cheng He, Xuesong Ye","doi":"10.1109/ICOT.2014.6954670","DOIUrl":null,"url":null,"abstract":"A new low-power wrist-worn miniature device used for real-time wireless heart rate (HR) monitoring and fall detection is presented here. This device consists of sensors, signal condition circuits, microcontroller, and system communication module. Power management and algorithms are applied to achieve low power function. Using PASW Statistics 18.0(SPSS Statistics) software to analyze the 54 HR date gotten from Six subjects, we find that the average and standard deviation of the proposed device are 60.83 and 9.705 while they are 61.96 and 9.317 by using POLAR RS100(Polar Electro). The Pearson correlation coefficient is 0.975(p<;0.01). Results show that proposed device has good consistency as compared to the POLAR RS100. A low-power, low-cost MEMS accelerometer is used to detect the fall. Results show that we can detect the occurrence of a fall according to the threshold which is significant different from stationary, walking and standing up from sitting situations. When people worn the device fall down, an interrupt will be generated and sent to the microcontroller for further process immediately. 245 samples are tested, and the fall forwards detection accuracy is 93.75%. The device is useful to detect heartbeat problems in long-term vital sign monitoring such as combat medics, mountain climbers, etc. And also it is useful to detect health condition of elderly people.","PeriodicalId":343641,"journal":{"name":"2014 International Conference on Orange Technologies","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"A low-power, wireless, wrist-worn device for long time heart rate monitoring and fall detection\",\"authors\":\"Cong-Cong Zhou, C. Tu, Yun Gao, Fei-Xiang Wang, Hong-Wei Gong, Ping Lian, Cheng He, Xuesong Ye\",\"doi\":\"10.1109/ICOT.2014.6954670\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new low-power wrist-worn miniature device used for real-time wireless heart rate (HR) monitoring and fall detection is presented here. This device consists of sensors, signal condition circuits, microcontroller, and system communication module. Power management and algorithms are applied to achieve low power function. Using PASW Statistics 18.0(SPSS Statistics) software to analyze the 54 HR date gotten from Six subjects, we find that the average and standard deviation of the proposed device are 60.83 and 9.705 while they are 61.96 and 9.317 by using POLAR RS100(Polar Electro). The Pearson correlation coefficient is 0.975(p<;0.01). Results show that proposed device has good consistency as compared to the POLAR RS100. A low-power, low-cost MEMS accelerometer is used to detect the fall. Results show that we can detect the occurrence of a fall according to the threshold which is significant different from stationary, walking and standing up from sitting situations. When people worn the device fall down, an interrupt will be generated and sent to the microcontroller for further process immediately. 245 samples are tested, and the fall forwards detection accuracy is 93.75%. The device is useful to detect heartbeat problems in long-term vital sign monitoring such as combat medics, mountain climbers, etc. And also it is useful to detect health condition of elderly people.\",\"PeriodicalId\":343641,\"journal\":{\"name\":\"2014 International Conference on Orange Technologies\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Orange Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOT.2014.6954670\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Orange Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOT.2014.6954670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A low-power, wireless, wrist-worn device for long time heart rate monitoring and fall detection
A new low-power wrist-worn miniature device used for real-time wireless heart rate (HR) monitoring and fall detection is presented here. This device consists of sensors, signal condition circuits, microcontroller, and system communication module. Power management and algorithms are applied to achieve low power function. Using PASW Statistics 18.0(SPSS Statistics) software to analyze the 54 HR date gotten from Six subjects, we find that the average and standard deviation of the proposed device are 60.83 and 9.705 while they are 61.96 and 9.317 by using POLAR RS100(Polar Electro). The Pearson correlation coefficient is 0.975(p<;0.01). Results show that proposed device has good consistency as compared to the POLAR RS100. A low-power, low-cost MEMS accelerometer is used to detect the fall. Results show that we can detect the occurrence of a fall according to the threshold which is significant different from stationary, walking and standing up from sitting situations. When people worn the device fall down, an interrupt will be generated and sent to the microcontroller for further process immediately. 245 samples are tested, and the fall forwards detection accuracy is 93.75%. The device is useful to detect heartbeat problems in long-term vital sign monitoring such as combat medics, mountain climbers, etc. And also it is useful to detect health condition of elderly people.