2020/05/11 by Ann-Kathrin Seifert, Seifert, Ann-Kathrin, Martin Grimmer +3
Engineering · Medicine · #Diabetic Foot Ulcer Assessment and Management #FOS: Electrical engineering #Muscle activation and electromyography studies #Non-Invasive Vital Sign Monitoring #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2005.05280
openalex publication_date 2020/05/11 · openalex created_date 2022/09/27 · openalex updated_date 2026/07/28
The applicability of Doppler radar for gait analysis is investigated by\nquantitatively comparing the measured biomechanical parameters to those\nobtained using motion capturing and ground reaction forces. Nineteen\nindividuals walked on a treadmill at two different speeds, where a radar system\nwas positioned in front of or behind the subject. The right knee angle was\nconfined by an adjustable orthosis in five different degrees. Eleven gait\nparameters are extracted from radar micro-Doppler signatures. Here, new methods\nfor obtaining the velocities of individual lower limb joints are proposed.\nFurther, a new method to extract individual leg flight times from radar data is\nintroduced. Based on radar data, five spatiotemporal parameters related to\nrhythm and pace could reliably be extracted. Further, for most of the\nconsidered conditions, three kinematic parameters could accurately be measured.\nThe radar-based stance and flight time measurements rely on the correct\ndetection of the time instant of maximal knee velocity during the gait cycle.\nThis time instant is reliably detected when the radar has a back view, but is\nunderestimated when the radar is positioned in front of the subject. The\nresults validate the applicability of Doppler radar to accurately measure a\nvariety of medically relevant gait parameters. Radar has the potential to\nunobtrusively diagnose changes in gait, e.g., to design training in prevention\nand rehabilitation. As contact-less and privacy-preserving sensor, radar\npresents a viable technology to supplement existing gait analysis tools for\nlong-term in-home examinations.\n