HEART-Watch: A multimodal physiological dataset from a Google Pixel Watch across different physical states
Provides a public dataset with demographic diversity for developing and validating cardiovascular monitoring algorithms on consumer smartwatches, addressing a gap in available resources.
The paper introduces HEART-Watch, a multimodal physiological dataset from a Google Pixel Watch with synchronized ECG, PPG, and accelerometer signals from 40 diverse adults across sitting, standing, and walking states, alongside reference chest ECG and blood pressure measurements. The dataset aims to support development and benchmarking of cardiovascular algorithms for consumer smartwatches.
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.