A Comprehensive PPG-based Dataset for HR/HRV Studies

TL;DR

This paper introduces UTSA-PPG, a comprehensive, multimodal, long-term PPG dataset designed to facilitate HR and HRV research across various scenarios, addressing limitations of existing datasets.

Contribution

The study presents a new all-in-one PPG dataset with diverse modalities and long-term data, filling a significant gap in HR/HRV research resources.

Findings

UTSA-PPG dataset offers extensive multimodal data for HR/HRV analysis.

Compared to existing datasets, UTSA-PPG provides longer recordings and more diverse conditions.

The dataset proves useful for developing generalized HR/HRV models.

Abstract

Heart rate (HR) and heart rate variability (HRV) are important vital signs for human physical and mental health. Recent research has demonstrated that photoplethysmography (PPG) sensors can infer HR and HRV. However, it is difficult to find a comprehensive PPG-based dataset for HR/HRV studies, especially for various study needs: multiple scenes, long-term monitoring, and multimodality (multiple PPG channels and extra acceleration data). In this study, we collected a comprehensive multimodal long-term dataset to address the gap of missing an all-in-one HR/HRV dataset (denoted as UTSA-PPG). We began by reviewing state-of-the-art datasets, emphasizing their strengths and limitations. Following this, we developed a custom data acquisition system and then collected the UTSA-PPG dataset and compared its key features with those of existing datasets. Additionally, five case studies were conducted, including comparisons with state-of-the-art datasets. The outcomes highlight the value of our dataset, demonstrating its utility for HR/HRV estimation exploration and its potential to aid researchers in creating generalized models for targeted research challenges.