Personalized fall detection and classification through walls and in heavy indoor clutter

摘要

Recent research and developments for in home radar monitoring have shown real promise of the technology in detecting normal and abnormal gross-motor activities of humans inside their residences and at private homes. Attention is now paid to challenges in system integration, operations, and installations. One important question touches on the required number of radar units for a given residence and whether eventually one radar unit per room would become the nominal approach. Towards addressing this question and assessing the effectiveness of radar unit to sense adjacent rooms and hallways of the same residence, this paper examines through-wall radar monitoring where the radar signal faces both wall attenuation and dispersion. We show that typical interior walls do not significantly alter the radar time-frequency (TF) signature of a fall, and the radar signal return is slightly weakened by wall penetration. Additionally, we show that there is a wide variation of the TF feature values associated with fall motions which confuse a classifier, trained with generic subjects, and cause it to falsely declare a different motion.