# DistancePPG: Robust non-contact vital signs monitoring using a camera

arXiv: https://arxiv.org/abs/1502.08040 · HTML: https://mlsanity.com/paper/1502.08040/

## Key facts

- Cited by 16 papers in the map (data through 7 Oct 2026).
- First posted on arXiv 27 Feb 2015.

## Built on by (most cited first, 16 of 16)

- [Contrast-Phys: Unsupervised Video-based Remote Physiological Measurement via Spatiotemporal Contrast](https://mlsanity.com/paper/2208.04378/) (2022)
- [Contrast-Phys+: Unsupervised and Weakly-supervised Video-based Remote Physiological Measurement via Spatiotemporal Contrast](https://mlsanity.com/paper/2309.06924/) (2023)
- [PhysMLE: Generalizable and Priors-Inclusive Multi-task Remote Physiological Measurement](https://mlsanity.com/paper/2405.06201/) (2024)
- [Non-contact PPG Signal and Heart Rate Estimation with Multi-hierarchical Convolutional Network](https://mlsanity.com/paper/2104.02260/) (2021)
- [Noncontact Respiratory Anomaly Detection Using Infrared Light-Wave Sensing](https://mlsanity.com/paper/2301.03713/) (2023)
- [Evaluation of Video-Based rPPG in Challenging Environments: Artifact Mitigation and Network Resilience](https://mlsanity.com/paper/2405.01230/) (2024)
- [UbiHR: Resource-efficient Long-range Heart Rate Sensing on Ubiquitous Devices](https://mlsanity.com/paper/2410.19279/) (2024)
- [ReViSe: Remote Vital Signs Measurement Using Smartphone Camera](https://mlsanity.com/paper/2206.08748/) (2022)
- [MHAD: Multimodal Home Activity Dataset with Multi-Angle Videos and Synchronized Physiological Signals](https://mlsanity.com/paper/2409.09366/) (2024)
- [PulseFi: A Low Cost Robust Machine Learning System for Accurate Cardiopulmonary and Apnea Monitoring Using Channel State Information](https://mlsanity.com/paper/2510.24744/) (2025)
- [A Supervised Learning Approach for Robust Health Monitoring using Face Videos](https://mlsanity.com/paper/2102.00322/) (2021)
- [A Web Application for Experimenting and Validating Remote Measurement of Vital Signs](https://mlsanity.com/paper/2208.09916/) (2022)
- [Respiratory Anomaly Detection using Reflected Infrared Light-wave Signals](https://mlsanity.com/paper/2311.01367/) (2023)
- [Internship Report: Benchmark of Deep Learning-based Imaging PPG in Automotive Domain](https://mlsanity.com/paper/2411.00919/) (2024)
- [Time-Series U-Net with Recurrence for Noise-Robust Imaging Photoplethysmography](https://mlsanity.com/paper/2503.17351/) (2025)
- [Time-varying rPPG signal separation via block-sparse signal model](https://mlsanity.com/paper/2605.22425/) (2026)

## Abstract (arXiv)

Vital signs such as pulse rate and breathing rate are currently measured using contact probes. But, non-contact methods for measuring vital signs are desirable both in hospital settings (e.g. in NICU) and for ubiquitous in-situ health tracking (e.g. on mobile phone and computers with webcams). Recently, camera-based non-contact vital sign monitoring have been shown to be feasible. However, camera-based vital sign monitoring is challenging for people with darker skin tone, under low lighting conditions, and/or during movement of an individual in front of the camera. In this paper, we propose distancePPG, a new camera-based vital sign estimation algorithm which addresses these challenges. DistancePPG proposes a new method of combining skin-color change signals from different tracked regions of the face using a weighted average, where the weights depend on the blood perfusion and incident light intensity in the region, to improve the signal-to-noise ratio (SNR) of camera-based estimate. One of our key contributions is a new automatic method for determining the weights based only on the video recording of the subject. The gains in SNR of camera-based PPG estimated using distancePPG translate into reduction of the error in vital sign estimation, and thus expand the scope of camera-based vital sign monitoring to potentially challenging scenarios. Further, a dataset will be released, comprising of synchronized video recordings of face and pulse oximeter based ground truth recordings from the earlobe for people with different skin tones, under different lighting conditions and for various motion scenarios.