# A Cost-Effective Method for the Spectral Calibration of Photoplethysmography Pulses: The Optimal Wavelengths for Heart Rate Monitoring

## TL;DR

This paper introduces a cost-effective method to determine optimal wavelengths for heart rate monitoring using PPG sensors.

## Contribution

The study proposes a novel spectral calibration method using an optical phantom and simulations to identify optimal PPG wavelengths.

## Key findings

- Green light (523 nm) improves PPG sensitivity compared to NIR (945 nm) in a controlled optical phantom model.
- Monte Carlo simulations reveal how epithelial thickness and source–detector distance affect PPG signal characteristics.
- The study provides insights into spectral behavior of PPG signals across 500–900 nm wavelengths.

## Abstract

A photoplethysmography (PPG) pulse in reflection mode represents the change in diffuse reflectance at the skin surface during a cardiac cycle and is commonly used in wearable devices to monitor heart rate. Commercial PPG sensors often rely on the reflectance signal from light sources at two different wavelength regions, green, such as λ = 523 nm, and near infrared (NIR), such as λ = 945 nm. Early in vivo studies of wearable sensors showed that green light is more beneficial than NIR light in optimizing PPG sensitivity. This contradicts the common trends in the standard near infrared spectroscopy techniques, which rely on the long optical pathlengths at NIR wavelengths to achieve optimal depth sensitivity. To quantitatively analyze the spectral characteristics of PPG across the wavelength region of 500–900 nm in a controlled environment, this study performs the spectral measurement of PPG signals using a simple and cost-effective optical phantom model with two distinct layers and a customized diffuse reflectance spectroscopy system. In addition, Monte Carlo simulations are used to elaborate the underlying phenomena at the green and NIR wavelengths when considering different epithelial thicknesses and source–detector distances (SDD).