Non-Contact Human Gait Identification through IR-UWB Edge Based Monitoring Sensor

Non-contact sensors are negating the use of wearables or cameras and providing a rewarding and accepting environment to assist in biomedical applications such as, physiological examinations, physiotherapy, home assistance, rehabilitation success determination, compliance and health diagnostics. In this study, physiological parameter identification of human gait has been demonstrated through an edge based sensor and heuristic approach. Impulse radio ultra-wide band (IR-UWB) pulsed Doppler radar has been employed with a focus on human walking patterns. This work extracts an individual’s gait trait from associated biomechanical activity and differentiates the lower limb movement patterns from other body areas via a radar transceiver. It is observed that Doppler shifts alone are not reliable to detect human gait because of frequency shifts occurring across the entire body (including, breathing, heartbeat, and arm movements) where movement occurs. Thus, a heuristic spherical trigonometrical approach has been proposed to augment radar principles and short term fourier transformation (STFT) to identify the gait trait precisely. The experiment presented includes data gathering from a number of male and female participants in both ideal and real environments. Subsequently, the proposed gait identification and parameter characterization has been analysed, tested and validated against popularly accepted smartphone applications where the errors are less than 5%. © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.