Operations Research, Systems Engineering and Industrial Engineering Commons^™

Classification Of Rest And Active Periods In Actigraphy Data Using Pca, Isaac W. Muns, Yogesh Lad, Ivan G. Guardiola, Matthew S. Thimgan

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper we highlight a clustering algorithm for the purpose of identifying sleep and wake periods directly from actigraphy signals. The paper makes use of statistical Principal Component Analysis to identify periods of rest and activity. The aim of the proposed methodology is to develop a quick and efficient method to determine the sleep duration of an individual. In addition, a robust method that can identify sleep periods in the accelerometer data when duration, time of day varies by individual. A selected group of 10 individual's sensor data consisting of actigraphy from an accelerometer (3-axis), near body temperature, and …