智能手表
加速度计
计算机科学
生物信号
人工智能
标杆管理
机器学习
可穿戴计算机
移动设备
数据挖掘
计步器
人机交互
心音图
医学
数据科学
体力活动
像素
惊喜
地理定位
计算机视觉
可穿戴技术
心血管健康
物联网
作者
Jathushan Kaetheeswaran,Boyi Ma,Ali Abedi,Shehroz S. Khan,Milad Lankarany
出处
期刊:PLOS digital health
[Public Library of Science]
日期:2026-08-25
卷期号:5 (8): e0001647-e0001647
被引量:1
标识
DOI:10.1371/journal.pdig.0001647
摘要
Consumer-grade smartwatches offer a new option for personalized health monitoring for general consumers, as cardiovascular diseases continue to prevail as the leading cause of global mortality. The development and validation of reliable cardiovascular monitoring algorithms for these consumer-grade devices requires realistic biosignal data from diverse sets of participants. However, the availability of public consumer-grade smartwatch datasets with synchronized cardiovascular biosignals remains limited, and existing datasets often lack rich demographic diversity in their participant cohorts, potentially leading to biased algorithm development. This paper presents HEART-Watch, a multimodal physiological dataset of synchronized wrist-worn Google Pixel Watch electrocardiogram (ECG), photoplethysmography, and accelerometer signals from a diverse cohort of 40 healthy adults across three physical states - sitting, standing and walking - alongside reference chest ECG. Intermittent upper arm blood pressure measurements and concurrent biosignals were collected as an additional biomarker for future research. The motivation, methodology, and initial analyses of results are presented. HEART-Watch is intended to support the development and benchmarking of robust cardiovascular algorithms on consumer-grade smartwatches across diverse populations.
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