Magnetic-free Extended Kalman Filter for upper limb kinematic assessment in Yoga

Abstract

Human motion analysis is gaining increased importance in several fields, from movement assessment in rehabilitation to recreational applications such as virtual coaching. Among all the technologies involved in motion capture, Magneto-Inertial Measurements Units (MIMUs) is one of the most promising due to their small dimensions and low costs. Nevertheless, their usage is strongly limited by different error sources, among which magnetic disturbances, which are particularly problematic in indoor environments. Inertial Measurement Units (IMUs) could, thus, be considered as alternative solution. Indeed, relying exclusively on accelerometers and gyroscopes, they are insensitive to magnetic disturbances. Even if the literature has started to propose few algorithms that do not take into account magnetometer input, their application is limited to robotics and aviation. The aim of the present work is to introduce a magnetic-free quaternion based Extended Kalman filter for upper limb kinematic assessment in human motion (i.e., yoga). The algorithm was tested on five expert yoga trainers during the execution of the sun salutation sequence. Joint angle estimations were compared with the ones obtained from an optoelectronic reference system by evaluating the Mean Absolute Errors (MAEs) and Pearson’s correlation coefficients. The achieved worst-case was 6.17°, while the best one was 2.65° for MAEs mean values. The accuracy of the algorithm was further confirmed by the high values of the Pearson’s correlation coefficients (lowest mean value of 0.86).Clinical Relevance— The proposed work validated a magnetic free algorithm for kinematic reconstruction with inertial units. It could be used as a wearable solution to track human movements in indoor environments being insensitive to magnetic disturbances, and thus could be potentially used also for rehabilitation purposes.