ITERATOR: A 3D Gait Identification from IR-UWB Technology

A more locally cared for and self-managing aging population along with better attention to self health-care, has resulted in increasing need for non-intrusive monitoring. Wearable, wireless physiological sensors, and cameras can pose user privacy, security and discomfort issues which may have a negative impact on consumer confidence and uptake. Thus, for the first time a non-contact, non-intrusive 3D human motion model is proposed for gait disorder identification from impulse radio ultra-wide band (ITERATOR) with the understanding of spherical trigonometry and vector field. Simultaneously, the Kinect Xbox One is used to compare the outcomes of the proposed IR-UWB model. The experiment comprises twenty-four human participants, where twenty people have normal walking pattern and four persons have spasticity. The height of different body sections from the ground have been recorded for each individual and employed later to distinguish lower and upper human body from the outcomes. The proposed work has transformed the radars backscattered responses through trigonometry and vector algebra where, only vector algebra has been implemented to transform the skeletal data obtained from Kinect. Angles between two thighs have been determined from the proposed UWB algorithm and validated against angles obtained from the Kinect skeletal data using root mean square error (RMSE), where less than 0.5 RMSE has been found.