Full model for sensors placement and activities recognition

Yu-Tai Ching, Guan Wei He, Chang-Chieh Cheng, Yu Jin Yang

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

We implemented a wired sensors system that supports activities identification. The system consists of Raspberry Pi, MPU6050 (accelerometers and gyrometers), and TCA9548 (1 to 8 multiplexer). Our experimental results show that when 6 MPU6050 attached to the right arm, right wrist, chest, waist, right thigh, and right ankle, the activities of standing, sitting, lying, walking, running, going upstairs, going downstairs, drinking water, and dumbbells activities could be identified with high accuracy. The system can connect up to 128 sensors, but under a practical sampling rate, the number of sensors should not be greater than 15. The system shall be used for finding the optimal locations for a multi-sensor wearable system (for examples, clothes or shoes).

原文English
主出版物標題UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
發行者Association for Computing Machinery, Inc
頁面17-20
頁數4
ISBN(電子)9781450351904
DOIs
出版狀態Published - 11 9月 2017
事件2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017 - Maui, United States
持續時間: 11 9月 201715 9月 2017

出版系列

名字UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

Conference

Conference2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017
國家/地區United States
城市Maui
期間11/09/1715/09/17

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