ArticleFrontiers in bioengineering and biotechnology2018
A Comparative Survey of Methods for Remote Heart Rate Detection From Frontal Face Videos.
Article in Frontiers in bioengineering and biotechnology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Continuous Monitoring of Vital Signs Using Cameras: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Evaluation and analysis of image compression effect on neural network-based heart rate classification.Scientific reports · 2025Article
- Deep learning and remote photoplethysmography powered advancements in contactless physiological measurement.Frontiers in bioengineering and biotechnology · 2024Review
- A novel approach for contactless heart rate monitoring from pet facial videos.Frontiers in veterinary science · 2024Article
- PhysioKit: An Open-Source, Low-Cost Physiological Computing Toolkit for Single- and Multi-User Studies.Sensors (Basel, Switzerland) · 2023Article
- Towards a Machine Learning-Based Digital Twin for Non-Invasive Human Bio-Signal Fusion.Sensors (Basel, Switzerland) · 2022Article
- Remote Heart Rate Prediction in Virtual Reality Head-Mounted Displays Using Machine Learning Techniques.Sensors (Basel, Switzerland) · 2022Article
- Using a graph-based image segmentation algorithm for remote vital sign estimation and monitoring.Scientific reports · 2022Article
- Cryptography-Based Medical Signal Securing Using Improved Variation Mode Decomposition with Machine Learning Techniques.Computational intelligence and neuroscience · 2022Article
- Contactless Vital Signs Monitoring From Videos Recorded With Digital Cameras: An Overview.Frontiers in physiology · 2022Review
- Contact-Free Pulse Signal Extraction from Human Face Videos: A Review and New Optimized Filtering Approach.Advances in experimental medicine and biology · 2021Review
- Detail-preserving pulse wave extraction from facial videos using consumer-level camera.Biomedical optics express · 2020Article
- Non-Contact Vital Signs Monitoring of Dog and Cat Using a UWB Radar.Animals : an open access journal from MDPI · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Remotely measuring physiological activity can provide substantial benefits for both the medical and the affective computing applications. Recent research has proposed different methodologies for the unobtrusive detection of heart rate (HR) using human face recordings. These methods are based on subtle color changes or motions of the face due to cardiovascular activities, which are invisible to human eyes but can be captured by digital cameras. Several approaches have been proposed such as signal processing and machine learning. However, these methods are compared with different datasets, and there is consequently no consensus on method performance. In this article, we describe and evaluate several methods defined in literature, from 2008 until present day, for the remote detection of HR using human face recordings. The general HR processing pipeline is divided into three stages: face video processing, face blood volume pulse (BVP) signal extraction, and HR computation. Approaches presented in the paper are classified and grouped according to each stage. At each stage, algorithms are analyzed and compared based on their performance using the public database MAHNOB-HCI. Results found in this article are limited on MAHNOB-HCI dataset. Results show that extracted face skin area contains more BVP information. Blind source separation and peak detection methods are more robust with head motions for estimating HR.
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