Body movement analysis during sleep based on video motion estimation

To assess sleep in the home situation, wrist actigraphy is often used. However, it requires an on-body sensor which may disturb sleep and primarily collects data on the movement of one wrist only. Video actigraphy, by estimating motion from captured infrared images, overcome these issues. In this paper, we compare activity levels from wrist and full body video actigraphy in a home setting. Video actigraphy correctly found 19 % more small and medium movements that were missed by the wrist sensor. We further show that similar values of sleep efficiency (SE, %) are obtained from simultaneous recordings of video and wrist actigraphy, and we compared both to reference SE values provided by a full polysomnography (PSG). The proposed video actigraphy proved convenient and easy to use in real home situations. It successfully found movements originating from under the blanket, and turned out robust to various sleeping positions, different illumination conditions, viewing angles, beds and blankets. Our results suggest that on-body actigraph sensors can be successfully replaced with the proposed video-based solution for the application of unobtrusive sleep monitoring and analysis.