DocumentCode :
720213
Title :
Kalman filtering for wearable fitness monitoring
Author :
Tran, K.H. ; Chew, M.T.
Author_Institution :
Centre of Technol., RMIT Int. Univ. Vietnam, Ho Chi Minh City, Vietnam
fYear :
2015
fDate :
11-14 May 2015
Firstpage :
2020
Lastpage :
2025
Abstract :
This paper presents a low-cost wearable fitness monitoring device utilizing a 6-axis Inertial Measurement Unit (IMU) embedding 3-axis gyroscope and 3-axis accelerometer. The objective is to measure the angular value form by the feet with respect to the gravitational vector while walking in order to estimate the stride length. Kalman filter is employed for the sensor fusion technique and data conditioning.
Keywords :
Kalman filters; accelerometers; angular measurement; body sensor networks; gait analysis; gyroscopes; patient monitoring; sensor fusion; Kalman filtering; angle measurement; data conditioning; gravitational vector; sensor fusion technique; six-axis inertial measurement unit; stride length estimation; three-axis accelerometer; three-axis gyroscope; walking; wearable fitness monitoring device; Acceleration; Accelerometers; Foot; Gyroscopes; Kalman filters; Noise; Noise measurement; Kalman filtering; accelerometer; angle measurement; fusion; gyroscope; pedometer; sensors; stride length estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference (I2MTC), 2015 IEEE International
Conference_Location :
Pisa
Type :
conf
DOI :
10.1109/I2MTC.2015.7151593
Filename :
7151593
Link To Document :
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