{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/robust-pulse-rate-from-chrominance-based-rppg","title":"Robust Pulse Rate From Chrominance-Based rPPG","arxiv_id":null,"date":"2013-06-04","proceeding":"IEEE Transactions on Biomedical Engineering 2013 6","authors":["Gerard de Haan","Vincent Jeanne"],"abstract":"Remote photoplethysmography (rPPG) enables contactless monitoring of the blood volume pulse using a regular camera. Recent research focused on improved motion robustness, but the proposed blind source separation techniques (BSS) in RGB color space show limited success. We present an analysis of the motion problem, from which far superior chrominance-based methods emerge. For a population of 117 stationary subjects, we show our methods to perform in 92% good agreement (±1.96σ) with contact PPG, with RMSE and standard deviation both a factor of 2 better than BSS-based methods. In a fitness setting using a simple spectral peak detector, the obtained pulse-rate for modest motion (bike) improves from 79% to 98% correct, and for vigorous motion (stepping) from less than 11% to more than 48% correct. We expect the greatly improved robustness to considerably widen the application scope of the technology.","url_abs":"https://ieeexplore.ieee.org/document/6523142","url_pdf":"https://www.es.ele.tue.nl/~dehaan/pdf/169_ChrominanceBasedPPG.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"photoplethysmography-ppg-heart-rate","task_name":"Photoplethysmography (PPG) heart rate estimation"},{"task_slug":"blind-source-separation","task_name":"blind source separation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/photoplethysmography-ppg-heart-rate-2","task":"Photoplethysmography (PPG) heart rate estimation","dataset":"MMSE-HR","model":"CHROM","rank_in_archive_order":5,"of":6,"metrics":{"MAE":"3.61","MAPE (%)":"4.50%","Pearson Correlation":" 0.85","RMSE":" 7.43"},"uses_additional_data":false},{"leaderboard":"/sota/photoplethysmography-ppg-heart-rate-1","task":"Photoplethysmography (PPG) heart rate estimation","dataset":"UBFC-rPPG","model":"CHROM","rank_in_archive_order":6,"of":8,"metrics":{"MAE":"3.10","MAPE (%)":"3.83%","Pearson Correlation":"0.93","RMSE":"6.84"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}