Frequency analysis of inertial sensor data for measuring toe clearance

Abstract

The use of sensors in studies of human movement and gait is now fast gaining attention as a promising alternative to video capture systems in gait laboratories. Inertial sensors such as accelerometers and gyroscopes have been deployed to detect acceleration and angular velocities of body landmarks, from which secondary quantities such as velocity, displacement and joint angles could be inferred. The major challenge with secondary quantity derivation has been the cumulative errors arising from the integration used. While this has often been attributed to sensor measurement errors, quantification of these errors have so far been limited. In this paper, we performed frequency analysis of accelerometer and gyroscope signals to investigate the effect of sensor errors on the frequency components in motion measurements. We employ the Fast Fourier Transform (FFT) to obtain the Fourier frequency spectra of the inertial sensor signals. Comparisons were made against the frequency spectra of the same signals obtained from the Optotrak video capture system. Our analysis revealed that sensor signals contained a large DC signal which could be filtered out using a bandpass Butterworth filter with a 1-20Hz passband. This allowed us to obtain better estimates of toe displacement data without the use of strapdown integration techniques. It was also discovered that inertial sensors possessed low frequency errors which co-existed in the frequency band of gait motion making them difficult to remove with static filters. Future work will focus on adaptive filtering methods to detect and remove these sensor errors in an effort to improve displacement measurements.