A linear discriminative analysis based fall motion detector using radar

Sivan Zlotnikov; Patrick Somaru; Panos P. Markopoulos; Fauzia Ahmad

doi:10.1117/12.2311574

14 May 2018 A linear discriminative analysis based fall motion detector using radar

Sivan Zlotnikov, Patrick Somaru, Panos P. Markopoulos, Fauzia Ahmad

Proceedings Volume 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics; 106580D (2018) https://doi.org/10.1117/12.2311574
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

Remote activity monitoring can support aging-in-place for the elderly, providing crucial capabilities such as fall detection. Falls are the leading cause of accidental death in people aged 65 and over in the United States. The chances of survival are high with low impact on quality of life when prompt assistance is provided after a fall. Radar is at the forefront of research on non-wearable technologies for fall detection and monitoring of activities of daily living for eldercare. Various features extracted from Doppler motion signatures have been proposed in the literature for radar-based fall detection. However, none of these features were specifically designed to provide the most discrimination between the fall and non-fall motion classes. In this paper, we perform linear discriminant analysis (LDA) of Doppler signatures as a first step towards identification of the most discriminative features. LDA performance is evaluated using real data measurements of various indoor human activities and compared with that of existing radar-based fall detection schemes.

Citation Download Citation

Sivan Zlotnikov, Patrick Somaru, Panos P. Markopoulos, and Fauzia Ahmad "A linear discriminative analysis based fall motion detector using radar", Proc. SPIE 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics, 106580D (14 May 2018); https://doi.org/10.1117/12.2311574

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