Non-Imaging Fall Detection Based on Spectral Signatures Obtained Using a Micro-Doppler Millimeter-Wave Radar

Falls are the leading cause of accidents among the elderly population. In recent years, radar has been employed in fall detection due to its superior sensing capabilities, small dimensions, low cost and primarily non-intrusive sensing capabilities in addition to its robustness under a range of heat and lighting conditions. In this paper, we present a technique for identifying when a person is falling using a low-power millimeter-wave radar operating in the W-band. This detection, conducted in real time, is based on the transmission of a continuous wave and heterodyning of the received signal reflected from the person to obtain micro-Doppler shifts associated with the person's motion. These results make it possible to obtain a high-quality time-frequency distribution and spectrogram, from which the person's unique fall movement characteristics can be determined. In this paper, we present experimental results based on 94 GHz real radar data obtained from a falling person. This carrier frequency is higher than that of current systems, allowing higher frequency resolution and more accurate results. Compared to other tracking systems, this sensor does not simulate or violate privacy. However, the high-frequency system enables high-resolution realizations with high reliability.

Automated summary

Falls are the leading cause of accidents among the elderly population. In recent years, radar has been widely employed in fall detection, providing superior sensing capabilities, small dimensions, low cost, non-intrusive sensing, and robustness. This paper presents a technique using low-power millimeter-wave radar to identify when a person is falling in real time, based on micro-Doppler shifts associated with the person's motion. Experimental results show high-resolution and accurate results using 94 GHz real radar data.