{"url":"/task/heart-rate-estimation","name":"Heart rate estimation","slug":"heart-rate-estimation","description_markdown":"RR interval detection and R peak detection from QRS complex","categories":[{"name":"Medical","url":"/area/medical"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":85,"papers_with_code":28,"benchmarks":6,"benchmark_tables_in_archive":6,"benchmark_tables_shown":6,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":8,"subtasks":0,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/heart-rate-estimation-on-ppg-dalia","slug":"heart-rate-estimation-on-ppg-dalia","dataset":"PPG-DaLiA","dataset_url":null,"rows_in_archive":6,"metrics":["MAE [bpm, session-wise]"],"first_row_in_archive_order":{"model":"KID-PPG","paper_title":"KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch","paper_url":"/paper/kid-ppg-knowledge-informed-deep-learning-for","paper_date":"2024-05-02","arxiv_id":"2405.09559","code_links":[{"title":"esl-epfl/KID-PPG","url":"https://github.com/esl-epfl/KID-PPG"},{"title":"esl-epfl/kid-ppg-paper","url":"https://github.com/esl-epfl/kid-ppg-paper"}],"syntology":null}},{"leaderboard":"/sota/heart-rate-estimation-on-wesad","slug":"heart-rate-estimation-on-wesad","dataset":"WESAD","dataset_url":null,"rows_in_archive":5,"metrics":["MAE [bpm, session-wise]"],"first_row_in_archive_order":{"model":"CNN ensemble","paper_title":"Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks","paper_url":"/paper/deep-ppg-large-scale-heart-rate-estimation","paper_date":"2019-07-12","arxiv_id":null,"code_links":[],"syntology":null}},{"leaderboard":"/sota/heart-rate-estimation-on-bidmc","slug":"heart-rate-estimation-on-bidmc","dataset":"BIDMC","dataset_url":null,"rows_in_archive":2,"metrics":["MAE [bpm, session-wise]"],"first_row_in_archive_order":{"model":"Liquid-S4","paper_title":"Liquid Structural State-Space Models","paper_url":"/paper/liquid-structural-state-space-models","paper_date":"2022-09-26","arxiv_id":"2209.12951","code_links":[{"title":"raminmh/liquid-s4","url":"https://github.com/raminmh/liquid-s4"}],"syntology":null}},{"leaderboard":"/sota/heart-rate-estimation-on-mths","slug":"heart-rate-estimation-on-mths","dataset":"MTHS","dataset_url":"/dataset/mths","rows_in_archive":1,"metrics":["MAE [bpm, session-wise]"],"first_row_in_archive_order":{"model":"Residual FCN","paper_title":"Efficient Deep Learning-based Estimation of the Vital Signs on Smartphones","paper_url":"/paper/efficient-deep-learning-based-estimation-of","paper_date":"2022-04-13","arxiv_id":"2204.08989","code_links":[{"title":"mahdifarvardin/medvse","url":"https://github.com/mahdifarvardin/medvse"},{"title":"mahdifarvardin/mtvital","url":"https://github.com/mahdifarvardin/mtvital"}],"syntology":null}},{"leaderboard":"/sota/heart-rate-estimation-on-vipl-hr","slug":"heart-rate-estimation-on-vipl-hr","dataset":"VIPL-HR","dataset_url":"/dataset/vipl-hr","rows_in_archive":1,"metrics":["RMSE","MAE"],"first_row_in_archive_order":{"model":"DRNet","paper_title":"DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement","paper_url":"/paper/drnet-decomposition-and-reconstruction","paper_date":"2022-06-12","arxiv_id":"2206.05687","code_links":[{"title":"yuhang1070/rPPG_Strong_Baseline","url":"https://github.com/yuhang1070/rPPG_Strong_Baseline"},{"title":"MindSpore-paper-code-3/code8","url":"https://github.com/MindSpore-paper-code-3/code8/tree/main/DRNet"},{"title":"2023-MindSpore-4/Code3","url":"https://github.com/2023-MindSpore-4/Code3/tree/main/DRNet"}],"syntology":null}},{"leaderboard":"/sota/heart-rate-estimation-on-wildppg","slug":"heart-rate-estimation-on-wildppg","dataset":"WildPPG","dataset_url":"/dataset/wildppg","rows_in_archive":1,"metrics":["\t MAE [bpm, session-wise]"],"first_row_in_archive_order":{"model":"Temp-ResNet","paper_title":"WildPPG: A Real-World PPG Dataset of Long Continuous Recordings","paper_url":"/paper/wildppg-a-real-world-ppg-dataset-of-long","paper_date":"2024-12-23","arxiv_id":"2412.17540","code_links":[{"title":"eth-siplab/WildPPG","url":"https://github.com/eth-siplab/WildPPG"}],"syntology":null}}],"datasets":[{"url":"/dataset/ubfc-rppg","name":"UBFC-rPPG","full_name":"Univ. Bourgogne Franche-Comté Remote PhotoPlethysmoGraphy","num_papers_in_archive":69},{"url":"/dataset/mmse-hr","name":"MMSE-HR","full_name":"Multimodal Spontaneous Expression-Heart Rate dataset","num_papers_in_archive":24},{"url":"/dataset/vipl-hr","name":"VIPL-HR","full_name":"","num_papers_in_archive":17},{"url":"/dataset/mmpd","name":"MMPD","full_name":"Multi-Domain Mobile Video Physiology Dataset","num_papers_in_archive":14},{"url":"/dataset/v4v","name":"V4V","full_name":"Vision for Vitals","num_papers_in_archive":11},{"url":"/dataset/buaa-mihr-dataset","name":"BUAA-MIHR dataset","full_name":"Large-scale-Multi-illumination-HR-Database","num_papers_in_archive":3},{"url":"/dataset/mths","name":"MTHS","full_name":"","num_papers_in_archive":2},{"url":"/dataset/wildppg","name":"WildPPG","full_name":"WildPPG: A Real-World PPG Dataset of Long Continuous Recordings","num_papers_in_archive":2}],"subtasks":[],"parent_tasks":[{"url":"/task/photoplethysmography-ppg","name":"Photoplethysmography (PPG)"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":28,"of":28,"tagged_in_all":85,"items":[{"url":"/paper/drnet-decomposition-and-reconstruction","title":"DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement","date":"2022-06-12","arxiv_id":"2206.05687","repositories_listed":3,"syntology":null},{"url":"/paper/kid-ppg-knowledge-informed-deep-learning-for","title":"KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch","date":"2024-05-02","arxiv_id":"2405.09559","repositories_listed":2,"syntology":null},{"url":"/paper/gpt-as-psychologist-preliminary-evaluations","title":"GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing","date":"2024-03-09","arxiv_id":"2403.05916","repositories_listed":2,"syntology":null},{"url":"/paper/efficient-deep-learning-based-estimation-of","title":"Efficient Deep Learning-based Estimation of the Vital Signs on Smartphones","date":"2022-04-13","arxiv_id":"2204.08989","repositories_listed":2,"syntology":null},{"url":"/paper/remote-heart-rate-measurement-from-highly","title":"Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement","date":"2019-07-27","arxiv_id":"1907.11921","repositories_listed":2,"syntology":null},{"url":"/paper/non-contact-health-monitoring-during-daily","title":"Non-Contact Health Monitoring During Daily Personal Care Routines","date":"2025-06-11","arxiv_id":"2506.09718","repositories_listed":1,"syntology":null},{"url":"/paper/wildppg-a-real-world-ppg-dataset-of-long","title":"WildPPG: A Real-World PPG Dataset of Long Continuous Recordings","date":"2024-12-23","arxiv_id":"2412.17540","repositories_listed":1,"syntology":null},{"url":"/paper/nightbeat-heart-rate-estimation-from-a-wrist","title":"Nightbeat: Heart Rate Estimation From a Wrist-Worn Accelerometer During Sleep","date":"2024-11-01","arxiv_id":"2411.00731","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}},{"url":"/paper/alpha-anomalous-physiological-health","title":"ALPHA: AnomaLous Physiological Health Assessment Using Large Language Models","date":"2023-11-21","arxiv_id":"2311.12524","repositories_listed":1,"syntology":null},{"url":"/paper/finding-order-in-chaos-a-novel-data-1","title":"Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning","date":"2023-09-23","arxiv_id":"2309.13439","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_unverified":2,"n_pointer_only":5}},{"url":"/paper/beliefppg-uncertainty-aware-heart-rate","title":"BeliefPPG: Uncertainty-aware Heart Rate Estimation from PPG signals via Belief Propagation","date":"2023-06-13","arxiv_id":"2306.07730","repositories_listed":1,"syntology":{"n":9,"n_ran":0,"n_unverified":9,"n_pointer_only":0}},{"url":"/paper/image-enhancement-for-remote","title":"Image Enhancement for Remote Photoplethysmography in a Low-Light Environment","date":"2023-03-16","arxiv_id":"2303.09336","repositories_listed":1,"syntology":null},{"url":"/paper/edbb-demo-biometrics-and-behavior-analysis","title":"edBB-Demo: Biometrics and Behavior Analysis for Online Educational Platforms","date":"2022-11-16","arxiv_id":"2211.09210","repositories_listed":1,"syntology":null},{"url":"/paper/liquid-structural-state-space-models","title":"Liquid Structural State-Space Models","date":"2022-09-26","arxiv_id":"2209.12951","repositories_listed":1,"syntology":null},{"url":"/paper/tiny-hr-towards-an-interpretable-machine","title":"Tiny-HR: Towards an interpretable machine learning pipeline for heart rate estimation on edge devices","date":"2022-08-16","arxiv_id":"2208.07981","repositories_listed":1,"syntology":null},{"url":"/paper/demo-rhythmedge-enabling-contactless-heart","title":"Demo: RhythmEdge: Enabling Contactless Heart Rate Estimation on the Edge","date":"2022-08-13","arxiv_id":"2208.06572","repositories_listed":1,"syntology":null},{"url":"/paper/heart-rate-estimation-in-intense-exercise","title":"Heart rate estimation in intense exercise videos","date":"2022-08-04","arxiv_id":"2208.02509","repositories_listed":1,"syntology":null},{"url":"/paper/pyvhr-a-python-framework-for-remote","title":"pyVHR: a Python framework for remote photoplethysmography","date":"2022-04-15","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/instantaneous-physiological-estimation-using","title":"Instantaneous Physiological Estimation using Video Transformers","date":"2022-02-24","arxiv_id":"2202.12368","repositories_listed":1,"syntology":null},{"url":"/paper/skin-feature-point-tracking-using-deep","title":"Skin feature point tracking using deep feature encodings","date":"2021-12-28","arxiv_id":"2112.14159","repositories_listed":1,"syntology":null},{"url":"/paper/self-supervised-learning-framework-for-remote","title":"Self-supervised Representation Learning Framework for Remote Physiological Measurement Using Spatiotemporal Augmentation Loss","date":"2021-07-16","arxiv_id":"2107.07695","repositories_listed":1,"syntology":{"n":6,"n_ran":2,"n_unverified":4,"n_pointer_only":0}},{"url":"/paper/an-open-framework-for-remote-ppg-methods-and","title":"An Open Framework for Remote-PPG Methods and their Assessment","date":"2020-11-26","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/deepfakeson-phys-deepfakes-detection-based-on","title":"DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimation","date":"2020-10-01","arxiv_id":"2010.00400","repositories_listed":1,"syntology":null},{"url":"/paper/meta-rppg-remote-heart-rate-estimation-using","title":"Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner","date":"2020-07-14","arxiv_id":"2007.06786","repositories_listed":1,"syntology":null},{"url":"/paper/heart-rate-estimation-from-face-videos-for","title":"Heart Rate Estimation from Face Videos for Student Assessment: Experiments on edBB","date":"2020-06-01","arxiv_id":"2006.00825","repositories_listed":1,"syntology":null},{"url":"/paper/non-contact-photoplethysmogram-and","title":"Non-contact photoplethysmogram and instantaneous heart rate estimation from infrared face video","date":"2019-02-14","arxiv_id":"1902.05194","repositories_listed":1,"syntology":null},{"url":"/paper/specmar-fast-heart-rate-estimation-from-ppg","title":"SPECMAR: Fast Heart Rate Estimation from PPG Signal using a Modified Spectral Subtraction Scheme with Composite Motion Artifacts Reference Generation","date":"2018-10-15","arxiv_id":"1810.06196","repositories_listed":1,"syntology":null},{"url":"/paper/heart-rate-estimation-from","title":"Heart Rate Estimation from Ballistocardiography Based on Hilbert Transform and Phase Vocoder","date":"2018-09-10","arxiv_id":"1809.03174","repositories_listed":1,"syntology":null}],"syntology_records":4,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}