{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:01:15Z","timestamp":1792785675944,"version":"4.5.0"},"reference-count":41,"publisher":"IOP Publishing","issue":"10","license":[{"start":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T00:00:00Z","timestamp":1791244800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T00:00:00Z","timestamp":1791244800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62266025"],"award-info":[{"award-number":["62266025"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Physiol. Meas."],"published-print":{"date-parts":[[2026,10,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    Remote photoplethysmography (rPPG) enables contactless heart rate (HR) estimation from facial video. Unsupervised methods still face two coupled limitations: fixed backbones lack progressive hierarchical feature refinement, and contrastive objectives mainly regulate inter-sample spectral relations rather than the single-waveform morphology used for bandpass filtering and dominant-peak HR readout at test time.\n                    <jats:italic>Approach.<\/jats:italic>\n                    We propose progressive hierarchical attention (PHA) and a frequency-domain decoupled physiological (FDP) loss on a single-branch three-dimensional CNN trained with Contrast-Phys-style power-spectral-density contrastive learning. PHA cascades spatial, temporal, and channel attention with learnable stage-wise fusion, as a physiologically motivated design. FDP anchors each waveform at a dynamic fundamental frequency and applies out-of-band suppression with confidence-gated harmonic constraints.\n                    <jats:italic>Main results.<\/jats:italic>\n                    On UBFC-rPPG, PURE, and COHFACE under in-domain and cross-dataset protocols, PHA and FDP yield complementary gains and remain competitive with contrastive and structure-decoupling baselines, while retaining a single-branch inference pipeline without background region of interest.\n                    <jats:italic>Significance.<\/jats:italic>\n                    By coupling feature-level hierarchical refinement with loss-level spectral anchoring, the framework aligns unsupervised training with practical frequency-domain HR readout and offers an interpretable, deployment-friendly paradigm for video-based physiological measurement.\n                  <\/jats:p>","DOI":"10.1088\/1361-6579\/aeac9a","type":"journal-article","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T22:52:25Z","timestamp":1790376745000},"page":"105003","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Progressive hierarchical attention and frequency-domain decoupled physiological loss for unsupervised remote photoplethysmography"],"prefix":"10.1088","volume":"47","author":[{"given":"Dangguo","family":"Shao","sequence":"first","affiliation":[{"name":"Kunming University of Science and Technology"},{"name":"Kunming University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1642-682X","authenticated-orcid":true,"given":"Yiting","family":"Peng","sequence":"additional","affiliation":[{"name":"Kunming University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"data-curation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5570-4927","authenticated-orcid":true,"given":"Sanli","family":"Yi","sequence":"additional","affiliation":[{"name":"Kunming University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Hongbin","family":"Wang","sequence":"additional","affiliation":[{"name":"Kunming University of Science and Technology"},{"name":"Kunming University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Shengxiang","family":"Gao","sequence":"additional","affiliation":[{"name":"Kunming University of Science and Technology"},{"name":"Kunming University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Lei","family":"Ma","sequence":"additional","affiliation":[{"name":"Kunming University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"266","published-online":{"date-parts":[[2026,10,6]]},"reference":[{"key":"pmeaaeac9abib1","doi-asserted-by":"publisher","first-page":"R1","DOI":"10.1088\/0967-3334\/28\/3\/R01","type":"journal-article","article-title":"Photoplethysmography and its application in clinical physiological measurement","volume":"28","author":"Allen","year":"2007","journal-title":"Physiol. Meas."},{"key":"pmeaaeac9abib2","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.patrec.2017.10.017","type":"journal-article","article-title":"Unsupervised skin tissue segmentation for remote photoplethysmography","volume":"124","author":"Bobbia","year":"2019","journal-title":"Pattern Recognit. Lett."},{"key":"pmeaaeac9abib3","doi-asserted-by":"publisher","first-page":"pp 1242","DOI":"10.1109\/CVPRW50498.2020.00161)","type":"conference-proceedings","article-title":"Long short-term memory deep-filter in remote photoplethysmography","author":"Botina-Monsalve","year":"2020"},{"key":"pmeaaeac9abib4","doi-asserted-by":"publisher","first-page":"4613","DOI":"10.1109\/JBHI.2024.3400869","type":"journal-article","article-title":"ST-Phys: Unsupervised spatio-temporal contrastive remote physiological measurement","volume":"28","author":"Cao","year":"2024","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"pmeaaeac9abib5","first-page":"pp 349","type":"conference-proceedings","article-title":"DeepPhys: video-based physiological measurement using convolutional attention networks","author":"Chen","year":"2018"},{"key":"pmeaaeac9abib6","doi-asserted-by":"publisher","first-page":"4932","DOI":"10.1109\/JBHI.2025.3540134","type":"journal-article","article-title":"CodePhys: robust video-based remote physiological measurement through latent codebook querying","volume":"29","author":"Chu","year":"2025","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"pmeaaeac9abib7","first-page":"pp 807","type":"conference-proceedings","article-title":"Domain generalized RPPG network: disentangled feature learning with domain permutation and domain augmentation","author":"Chung","year":"2022"},{"key":"pmeaaeac9abib8","doi-asserted-by":"publisher","first-page":"pp 2856","DOI":"10.1109\/ICIP55913.2025.11084290)","type":"conference-proceedings","article-title":"rPPG-NDCL: unsupervised remote physiological measurement via noise-disentangled contrastive learning","author":"Dai","year":"2025"},{"key":"pmeaaeac9abib9","doi-asserted-by":"publisher","first-page":"2878","DOI":"10.1109\/TBME.2013.2266196","type":"journal-article","article-title":"Robust pulse rate from chrominance-based rPPG","volume":"60","author":"de Haan","year":"2013","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"pmeaaeac9abib10","doi-asserted-by":"publisher","first-page":"1913","DOI":"10.1088\/0967-3334\/35\/9\/1913","type":"journal-article","article-title":"Improved motion robustness of remote plethysmography by using the blood volume pulse signature","volume":"35","author":"de Haan","year":"2014","journal-title":"Physiol. Meas."},{"key":"pmeaaeac9abib11","first-page":"pp 3995","type":"conference-proceedings","article-title":"The way to my heart is through contrastive learning: remote photoplethysmography from unlabelled video","author":"Gideon","year":"2021"},{"key":"pmeaaeac9abib12","article-title":"A reproducible study on remote heart rate measurement","author":"Heusch","year":"2017","type":"preprint"},{"key":"pmeaaeac9abib13","first-page":"pp 372","type":"conference-proceedings","article-title":"Augmentation of rppg benchmark datasets: learning to remove and embed rPPG signals via double cycle consistent learning from unpaired facial videos","author":"Hsieh","year":"2022"},{"key":"pmeaaeac9abib14","first-page":"pp 7132","type":"conference-proceedings","article-title":"Squeeze-and-excitation networks","author":"Hu","year":"2018"},{"key":"pmeaaeac9abib15","doi-asserted-by":"publisher","first-page":"4956","DOI":"10.1109\/TIFS.2025.3565965","type":"journal-article","article-title":"DD-rPPGNet: De-interfering and descriptive feature learning for unsupervised rPPG estimation","volume":"20","author":"Huang","year":"2025","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"pmeaaeac9abib16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2025.107128","type":"journal-article","article-title":"Spiking-PhysFormer: camera-based remote photoplethysmography with parallel spike-driven transformer","volume":"185","author":"Liu","year":"2025","journal-title":"Neural Netw."},{"key":"pmeaaeac9abib17","first-page":"pp 19400","type":"conference-proceedings","article-title":"Multi-task temporal shift attention networks for on-device contactless vitals measurement","volume":"vol 33","author":"Liu","year":"2020"},{"key":"pmeaaeac9abib18","first-page":"pp 12404","type":"conference-proceedings","article-title":"Dual-GAN: joint BVP and noise modeling for remote physiological measurement","author":"Hao","year":"2021"},{"key":"pmeaaeac9abib19","doi-asserted-by":"publisher","first-page":"3589","DOI":"10.1109\/TITS.2020.3038317","type":"journal-article","article-title":"Near-infrared imaging photoplethysmography during driving","volume":"23","author":"Nowara","year":"2022","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"pmeaaeac9abib20","type":"conference-proceedings","article-title":"Hybrid approach to heart rate estimation: comparing Green, CHROM and POS methods in rPPG analysis","volume":"vol 13510","author":"Shahmirzadi","year":"2025"},{"key":"pmeaaeac9abib21","doi-asserted-by":"publisher","DOI":"10.1016\/j.array.2026.100969","type":"journal-article","article-title":"Remote photoplethysmography for camera-based vital sign estimation: a systematic literature review, challenges and deployment guidelines","volume":"31","author":"Shahmirzadi","year":"2026","journal-title":"Array"},{"key":"pmeaaeac9abib22","doi-asserted-by":"publisher","first-page":"pp 10858","DOI":"10.1109\/CVPR52734.2025.01014)","type":"conference-proceedings","article-title":"Remote photoplethysmography in real-world and extreme lighting scenarios","author":"Shao","year":"2025"},{"key":"pmeaaeac9abib23","doi-asserted-by":"publisher","first-page":"1373","DOI":"10.1109\/JBHI.2021.3051176","type":"journal-article","article-title":"PulseGAN: learning to generate realistic pulse waveforms in remote photoplethysmography","volume":"25","author":"Song","year":"2021","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"pmeaaeac9abib24","first-page":"pp 14464","type":"conference-proceedings","article-title":"Non-contrastive unsupervised learning of physiological signals from video","author":"Speth","year":"2023"},{"key":"pmeaaeac9abib25","doi-asserted-by":"publisher","first-page":"pp 1056","DOI":"10.1109\/ROMAN.2014.6926392)","type":"conference-proceedings","article-title":"Non-contact video-based pulse rate measurement on a mobile service robot","author":"Stricker","year":"2014"},{"key":"pmeaaeac9abib26","doi-asserted-by":"publisher","DOI":"10.1117\/1.3602852","type":"journal-article","article-title":"Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise","volume":"16","author":"Sun","year":"2011","journal-title":"J. Biomed. Opt."},{"key":"pmeaaeac9abib27","first-page":"pp 492","type":"conference-proceedings","article-title":"Contrast-Phys: unsupervised video-based remote physiological measurement via spatiotemporal contrast","author":"Sun","year":"2022"},{"key":"pmeaaeac9abib28","doi-asserted-by":"publisher","first-page":"5835","DOI":"10.1109\/TPAMI.2024.3367910","type":"journal-article","article-title":"Contrast-Phys+: unsupervised and weakly-supervised video-based remote physiological measurement via spatiotemporal contrast","volume":"46","author":"Sun","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"pmeaaeac9abib29","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1088\/0967-3334\/35\/5\/807","type":"journal-article","article-title":"Non-contact video-based vital sign monitoring using ambient light and auto-regressive models","volume":"35","author":"Tarassenko","year":"2014","journal-title":"Physiol. Meas."},{"key":"pmeaaeac9abib30","doi-asserted-by":"publisher","first-page":"21434","DOI":"10.1364\/OE.16.021434","type":"journal-article","article-title":"Remote plethysmographic imaging using ambient light","volume":"16","author":"Verkruysse","year":"2008","journal-title":"Opt. Express"},{"key":"pmeaaeac9abib31","doi-asserted-by":"publisher","first-page":"7090","DOI":"10.1109\/JBHI.2024.3433461","type":"journal-article","article-title":"ConDiff-rPPG: robust remote physiological measurement to heterogeneous occlusions","volume":"28","author":"Wang","year":"2024","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"pmeaaeac9abib32","doi-asserted-by":"publisher","first-page":"1479","DOI":"10.1109\/TBME.2016.2638020","type":"journal-article","article-title":"Algorithmic principles of remote PPG","volume":"64","author":"Wang","year":"2017","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"pmeaaeac9abib33","first-page":"3","type":"conference-proceedings","article-title":"CBAM: convolutional block attention module","author":"Woo","year":"2018"},{"key":"pmeaaeac9abib34","doi-asserted-by":"publisher","first-page":"3951","DOI":"10.1109\/TCSVT.2025.3613370","type":"journal-article","article-title":"UDA-rPPG: Unsupervised geometric-physiological domain anchoring for low-light rppg measurement","volume":"36","author":"Wu","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"pmeaaeac9abib35","first-page":"pp 4186","type":"conference-proceedings","article-title":"PhysFormer: Facial video-based physiological measurement with temporal difference transformer","author":"Yu","year":"2022"},{"key":"pmeaaeac9abib36","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1109\/LSP.2020.3007086","type":"journal-article","article-title":"AutoHR: a strong end-to-end baseline for remote heart rate measurement with neural searching","volume":"27","author":"Yu","year":"2020","journal-title":"IEEE Signal Process. Lett."},{"key":"pmeaaeac9abib37","article-title":"Remote photoplethysmograph signal measurement from facial videos using spatio-temporal networks","author":"Yu","year":"2019","type":"conference-proceedings"},{"key":"pmeaaeac9abib38","doi-asserted-by":"publisher","first-page":"13844","DOI":"10.1109\/TPAMI.2023.3298650","type":"journal-article","article-title":"Facial video-based remote physiological measurement via self-supervised learning","volume":"45","author":"Yue","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"pmeaaeac9abib39","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2026.109787","type":"journal-article","article-title":"CNN\u2013LSTM based deep learning approach for remote photoplethysmography and cardiac activity monitoring leveraging minimal data","volume":"119","author":"Zeb","year":"2026","journal-title":"Biomed. Signal Process. Control"},{"key":"pmeaaeac9abib40","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2025.113593","type":"journal-article","article-title":"UL-Phys: ultra-lightweight remote physiological measurement in facial videos based on unsupervised learning","volume":"182","author":"Zhang","year":"2025","journal-title":"Appl. Soft Comput."},{"key":"pmeaaeac9abib41","first-page":"pp 21198","type":"conference-proceedings","article-title":"PHASE-Net: Physics-grounded harmonic attention system for efficient remote photoplethysmography measurement","author":"Zhao","year":"2026"}],"container-title":["Physiological Measurement"],"original-title":[],"link":[{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6579\/aeac9a","content-type":"text\/html","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6579\/aeac9a\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6579\/aeac9a","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6579\/aeac9a\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6579\/aeac9a\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6579\/aeac9a\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6579\/aeac9a\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"similarity-checking"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6579\/aeac9a\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T07:17:59Z","timestamp":1791271079000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6579\/aeac9a"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,6]]},"references-count":41,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2026,10,6]]},"published-print":{"date-parts":[[2026,10,30]]}},"URL":"https:\/\/doi.org\/10.1088\/1361-6579\/aeac9a","relation":{},"ISSN":["0967-3334","1361-6579"],"issn-type":[{"value":"0967-3334","type":"print"},{"value":"1361-6579","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,6]]},"assertion":[{"value":"Progressive hierarchical attention and frequency-domain decoupled physiological loss for unsupervised remote photoplethysmography","name":"article_title","label":"Article Title"},{"value":"Physiological Measurement","name":"journal_title","label":"Journal Title"},{"value":"paper","name":"article_type","label":"Article Type"},{"value":"\u00a9 2026 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2026-07-14","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-09-22","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-10-06","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}