Quantifying the Spatial Position Representation of Gait Through Sensor Fusion

Abstract

Wearable and wireless systems equipped with the ability to mutually record the accelerometer and gyroscope signal can be applied to sensor fusion. Sensor fusion can provide the location of the inertial sensor with trajectory information, such as displacement, velocity, and acceleration as a function of time. In order to achieve the results of sensor fusion multiple subjects must be applied, such as the use of quaternion mathematics and orientation filtering. A traditional orientation filter is the Kalman filter; however, the gradient descent orientation filter offers a more computationally robust alternative that is suitable for wearable and wireless systems. The result information provided by sensor fusion is particularly useful for the assessment of gait trajectory. Sensor fusion is anticipated to enhance Network Centric Therapy with improved visualization of patient status.