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

TL;DR

This paper introduces the BiHeartS dataset, capturing bilateral heart rate data from multiple devices and body positions over 30 nights to improve sleep quality assessment using wearable sensors.

Contribution

The paper presents a new comprehensive dataset combining physiological, behavioral, and subjective sleep data from multiple devices and positions in real-world conditions.

Findings

Dataset includes data from 10 participants over 30 nights.

Combines research-grade and commercial wearable devices.

Includes detailed self-reports on sleep quality and routines.

Abstract

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