Gait Speed Estimation from Millimeter-Wave Wireless Sensing

Gait speed is an important indicator of human health. Monitoring patients' gait speed can help doctors assess the recovery process, but traditional clinician observation fails to track in home scenarios. Compared to vision-based and wearable approaches, radio frequency signals offer an easily deployable and light free solution protecting user privacy in home scenarios. Therefore, we proposed a millimeter-wave (mmWave) system to accurately extract walking periods from collected trials and calculate gait speeds. To evaluate the robustness and reliability of our system and determine the optimal mounting position, we collected data from 5 volunteers with normal walking speeds and imitated various abnormal gait patterns and walking speeds. The results show that the mmWave device mounted near the ground outperforms across all volunteers than the one mounted near the ceiling, achieving an average estimation error of 0.02 m/s in abnormal gait evaluations.