Title: | Full Model for Sensors Placement and Activities Recognition |
Authors: | Ching, Yu-Tai He, Guan-Wei Cheng, Chang-Chieh Yang, Yu-Jin 資訊工程學系 Department of Computer Science |
Keywords: | Human Activity Recognition;Wearable sensors;physical activities |
Issue Date: | 1-Jan-2017 |
Abstract: | 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). |
URI: | http://dx.doi.org/10.1145/3123024.3123096 http://hdl.handle.net/11536/147051 |
DOI: | 10.1145/3123024.3123096 |
Journal: | PROCEEDINGS OF THE 2017 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2017 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC '17 ADJUNCT) |
Begin Page: | 17 |
End Page: | 20 |
Appears in Collections: | Conferences Paper |