Accelerometer-Based Person-in-Bed Detection Challenge

Abstract

In-bed, non-contact vital signs monitoring enables patient monitoring without the use of intrusive sensors that interfere with patients’ sleep. Accelerometers incorporated into mattresses can be used to estimate insights related to vitals and sleep quality when someone lays on the mattress. A necessary first step to this is detecting whether someone is lying on the bed. In this signal processing grand challenge, we consider the problem of person-in-bed detection using only 3-axis accelerometer data obtained using the ADXL355 sensor. In particular, we focus on low-cost, low-latency detection algorithms through two challenge tracks, the first focused on detection over limited windows and the second on state tracking aimed to detect changes quickly.