Introduction of Integrated Image Deep Learning Solution and how it brought laboratorial level heart rate and blood oxygen results to everyone

TL;DR

This paper presents a contact-less deep learning-based solution, HealthyPai, that accurately measures heart rate and blood oxygen levels, achieving results comparable to FDA-approved devices and surpassing consumer-grade wearables.

Contribution

The introduction of the Integrated Image Deep Learning Solution (IIDLS) enables accurate, contact-less measurement of HR and SpO2, bringing laboratory-level results to general users.

Findings

HealthyPai's HR MAE in lab: 1.48 bpm

HealthyPai's SpO2 MAE: 1.04%

Performance surpasses consumer-grade wearables

Abstract

The general public and medical professionals recognized the importance of accurately measuring and storing blood oxygen levels and heart rate during the COVID-19 pandemic. The demand for accurate contact-less devices was motivated by the need for cross-infection reduction and the shortage of conventional oximeters, partially due to the global supply chain issue. This paper evaluated a contact-less mini-program HealthyPai's heart rate (HR) and oxygen saturation (SpO2) measurements compared with other wearable devices. In the HR study of 185 samples (81 in the laboratory environment, 104 in the real-life environment), the mean absolute error (MAE) $\pm$ standard deviation was $1.4827 \pm 1.7452$ in the lab, $6.9231 \pm 5.6426$ in the real-life setting. In the SpO2 study of 24 samples, the mean absolute error (MAE) $\pm$ standard deviation of the measurement was $1.0375 \pm 0.7745$. Our results validated that HealthyPai utilizing the Integrated Image Deep Learning Solution (IIDLS) framework can accurately measure HR and SpO2, providing the test quality at least comparable to other FDA-approved wearable devices in the market and surpassing the consumer-grade and research-grade wearable standards.