Please use this identifier to cite or link to this item: https://doi.org/10.1109/ROBOT.2008.4543338
Title: A wearable, self-calibrating, wireless sensor network for body motion processing
Authors: Kwang, Y.L.
Goh, F.Y.K.
Dong, W.
Kim, D.N.
Chen, I.-M.
Song, H.Y.
Duh, H.B.L. 
Chung, G.K.
Issue Date: 2008
Source: Kwang, Y.L., Goh, F.Y.K., Dong, W., Kim, D.N., Chen, I.-M., Song, H.Y., Duh, H.B.L., Chung, G.K. (2008). A wearable, self-calibrating, wireless sensor network for body motion processing. Proceedings - IEEE International Conference on Robotics and Automation : 1017-1022. ScholarBank@NUS Repository. https://doi.org/10.1109/ROBOT.2008.4543338
Abstract: A novel self-calibrating sensing technology using miniature linear encoders and Inertial/magnetic Measurement Unit (IMU) provides the accuracy, fast response and robustness required by many body motion processing applications. Our sensor unit consists of an accelerometer, a 3-axis magnetic sensor, 2 gyroscopes and a miniature linear encoder. The fusion of data from the sensors is accomplished by extracting the gravity related term from the accelerometer and consistently calibrating the gyroscopes and linear encoder when the sensor unit is under static conditions. Using the fused sensors, we developed a complete motion processing system that consists of a gateway where the human kinematics modeling is embedded. A time divided multiple access wireless architecture is adopted to synchronize the sensor network at 100Hz. Experimental results show that the combination of the IMU and linear encoder produces a low RMS error of 3.5° and correlation coefficient of 99.01%. A video showing the capture a performer's upper body motion is also realized. ©2008 IEEE.
Source Title: Proceedings - IEEE International Conference on Robotics and Automation
URI: http://scholarbank.nus.edu.sg/handle/10635/69125
ISBN: 9781424416479
ISSN: 10504729
DOI: 10.1109/ROBOT.2008.4543338
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