Motion and heart rate from a wrist-worn wearable and labeled sleep from polysomnography

This project contains acceleration (in units of g) and heart rate (bpm, measured from photoplethysmography) recorded from the Apple Watch, as well as labeled sleep scored from gold-standard polysomnography. Data were collected at the University of Michigan from June 2017 to March 2019, and there are 31 subjects in total. Code to read and process these files is available on GitHub. The paper corresponding to the work is Walch et al., "Sleep stage prediction with raw acceleration and photoplethysmography heart rate data derived from a consumer wearable device", SLEEP (2019).本数据集包含由Apple Watch采集的加速度数据（单位：g）与心率数据（单位：次/分钟，bpm，通过光电容积描记法（photoplethysmography）测得），同时包含经金标准多导睡眠图（polysomnography）评分并标注的睡眠分期数据。该数据集于2017年6月至2019年3月在美国密歇根大学采集完成，共纳入31名受试者。用于读取和处理该数据集文件的代码已开源至GitHub平台。本研究对应的学术论文为Walch等人发表于期刊《SLEEP》2019年的《基于消费级可穿戴设备原始加速度与光电容积描记法心率数据的睡眠分期预测》。

搜集汇总

背景与挑战

背景概述

该数据集包含来自Apple Watch的加速度和心率数据，以及来自多导睡眠图的标记睡眠数据，旨在研究运动和心率数据在睡眠阶段预测中的应用。数据收集于2017年6月至2019年3月，共有31名受试者参与。