Poster: Foot-Floor Friction Based Walking Surface Detection for Fall Prevention Using Wearable Motion Sensors

Abstract

Automatic walking surface detection helps people adapt their gait to different surfaces and reduce fall risk. Walking on different surfaces causes different foot-floor friction patterns. We proposed to deploy motion sensors near the ankle to sense foot-floor friction and recognize walking surfaces. There are two contributions in this proposed research work. First, we demonstrated that the proposed method is capable of distinguishing five most-common walking surfaces in daily living. Second, we compare the detection accuracy between walking normally and dragging feet while walking. Experimental results show the proposed method obtains higher accuracy for dragging feet while walking, which reaches 90.6% using only five seconds of data.