Micro-Doppler based in-home aided and un-aided walking recognition with multiple radar and sonar systems

The potential for using micro-Doppler signatures as a basis for distinguishing between aided and unaided gaits is considered in this paper for the purpose of characterizing normal elderly gait and assessment of patient recovery. In particular, five different classes of mobility are considered: normal unaided walking, walking with a limp, walking using a cane or tripod, walking with a walker, and using a wheelchair. This presents a challenging classification problem as the differences in micro-Doppler for these activities can be quite slight. Within this context, the performance of four different radar and sonar systems - a 40 kHz sonar, a 5.8 GHz wireless pulsed Doppler radar mote, a 10 GHz X-band CW radar, and a 24 GHz CW radar - is evaluated using a broad range of features. Performance improvements using feature selection is addressed as well as the impact on performance of sensor placement and potential occlusion due to household objects. Results show that nearly 80% correct classification can be achieved with 10 second observations from the 24 GHz CW radar, while 86% performance can be achieved with 5 second observations of sonar