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Sleep is the primary mean of recovery from accumulated fatigue and thus playsa crucial role in fostering people's mental and physical well-being. Sleepquality monitoring systems are often implemented using wearables that leveragetheir sensing capabilities to provide sleep behaviour insights andrecommendations to users. Building models to estimate sleep quality from sensordata is a challenging task, due to the variability of both physiological data,perception of sleep quality, and the daily routine across users. This challengegauges the need for a comprehensive dataset that includes information about thedaily behaviour of users, physiological signals as well as the perceived sleepquality. In this paper, we try to narrow this gap by proposing Bilateral Heartrate from multiple devices and body positions for Sleep measurement (BiHeartS)dataset. The dataset is collected in the wild from 10 participants for 30consecutive nights. Both research-grade and commercial wearable devices areincluded in the data collection campaign. Also, comprehensive self-reports arecollected about the sleep quality and the daily routine.

BiHeartS: Bilateral Heart Rate from multiple devices and body positions for Sleep measurement Dataset