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

Moeness Amin; Fauzia Ahmad; Branka Jokanovic

doi:10.1117/12.2177600

21 May 2015 Personalized fall detection and classification through walls and in heavy indoor clutter

Moeness Amin, Fauzia Ahmad, Branka Jokanovic

Proceedings Volume 9461, Radar Sensor Technology XIX; and Active and Passive Signatures VI; 94610H (2015) https://doi.org/10.1117/12.2177600
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

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.

Citation Download Citation

Moeness Amin, Fauzia Ahmad, and Branka Jokanovic "Personalized fall detection and classification through walls and in heavy indoor clutter", Proc. SPIE 9461, Radar Sensor Technology XIX; and Active and Passive Signatures VI, 94610H (21 May 2015); https://doi.org/10.1117/12.2177600

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