Body inertial-sensing network platform for wearable 3D gesture analysis

Author

Guo, Yan-Wei ; Wang, Wei-Zhong ; Liu, Guan-Zheng ; Zhao, Guo-Ru ; Huang, Bang-Yu ; Mei, Zhan-Yong ; Wang, Lei

Author_Institution

Key Lab. of Biomed. Inf. & Health Eng., Shenzhen Inst. of Adv. Technol., Shenzhen, China

fYear

2011

fDate

3-5 Nov. 2011

Firstpage

259

Lastpage

262

Abstract

Gesture analysis was widely used in many applications such as healthcare, robotics and human-computer interactions. This paper presented a low-cost body inertial-sensing network platform developed by us. The platform contains the base station, the BSN inertial measurement nodes and the wireless communication protocol. The sensing nodes contain one 3-axis accelerometer, one 3-axis magnetometer, and one 3-axis gyroscope. Wearable gesture analysis was achieved using this platform. Then Kalman filter was designed to get optimal gesture estimation from the BSN inertial measurement nodes. Preliminary results showed that the averaged estimating errors of the roll angle, the yaw angle and the pitch angle were 3.5°, 3.2°, 2.1°, respectively.

Keywords

Kalman filters; accelerometers; biomedical measurement; biosensors; body sensor networks; error analysis; gyroscopes; human computer interaction; magnetometers; wearable computers; 3-axis accelerometer; 3-axis gyroscope; 3-axis magnetometer; Kalman filter; body inertial-sensing network platform; error estimation; health care; human-computer interactions; optimal gesture estimation; pitch angle; robotics; roll angle; wearable 3D gesture analysis; wireless communication protocol; yaw angle; Accelerometers; Gyroscopes; Humans; Kalman filters; Magnetometers; Quaternions; Sensors; Kalman filter; inertial sensors; non video-based motion capture;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioelectronics and Bioinformatics (ISBB), 2011 International Symposium on

Conference_Location

Suzhou

Print_ISBN

978-1-4577-0076-7

Type

conf

DOI

10.1109/ISBB.2011.6107696

Filename

6107696