{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:02:33Z","timestamp":1760148153595,"version":"build-2065373602"},"reference-count":49,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,4,4]],"date-time":"2023-04-04T00:00:00Z","timestamp":1680566400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"PPRS SAS"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we propose a sparse decomposition of the heart rate during sleep with an application to apnoea\u2013RERA detection. We observed that the tachycardia following an apnoea event has a quasi-deterministic shape with a random amplitude. Accordingly, we model the apnoea-perturbed heart rate as a Bernoulli\u2013Gaussian (BG) process convolved with a deterministic reference signal that allows the identification of tachycardia and bradycardia events. The problem of determining the BG series indicating the presence or absence of an event and estimating its amplitude is a deconvolution problem for which sparsity is imposed. This allows an almost syntactic representation of the heart rate on which simple detection algorithms are applied.<\/jats:p>","DOI":"10.3390\/s23073743","type":"journal-article","created":{"date-parts":[[2023,4,5]],"date-time":"2023-04-05T02:11:41Z","timestamp":1680660701000},"page":"3743","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sparse Decomposition of Heart Rate Using a Bernoulli-Gaussian Model: Application to Sleep Apnoea Detection"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9163-4807","authenticated-orcid":false,"given":"Bruno H.","family":"Muller","sequence":"first","affiliation":[{"name":"Pharma Partnering in Research & Strategy (PPRS), 68000 Colmar, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3538-3799","authenticated-orcid":false,"given":"R\u00e9gis","family":"Lengell\u00e9","sequence":"additional","affiliation":[{"name":"LIST3N, Universit\u00e9 de Technologie de Troyes (UTT), 10004 Troyes, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,4]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Ramachadran, A., and Karappiah, A. 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