Abstract
Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.
Highlights
The quantitative observation of how humans move provides information concerning both the functions of the locomotor sub-systems and the overall strategy with which a motor activity is executed
A number of critical aspects related to the accurate estimation of 3D orientation from magnetic and inertial measurement units (MIMUs) data in typical human movement analysis scenarios have been discussed and a set of structured guidelines have been provided as a useful outcome and code of practice for the scientific community working in the field
The sensor fusion approach has proven effective in compensating the limitations associated with the use of the gyroscopes alone, when the measurement conditions do not challenge the main limitations of the aiding sensors
Summary
The quantitative observation of how humans move provides information concerning both the functions of the locomotor sub-systems and the overall strategy with which a motor activity is executed. An understanding of these functions and strategies can be gained from measurements provided by motion capture techniques, associated with mathematical models of the anatomy and physiology of the organs and systems involved. Body segment orientation is crucial when monitoring activities of daily living in elderly people for walking instability evaluation and fall risk assessment [5,6]. Rehabilitation using virtual/augmented reality requires accurate information about body segment orientation in real time [7]
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