Kalman filtering for wearable fitness monitoring

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.