{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:48:10Z","timestamp":1787010490777,"version":"build-2736575974"},"reference-count":45,"publisher":"The Royal Society","issue":"1887","license":[{"start":{"date-parts":[[2008,10,30]],"date-time":"2008-10-30T00:00:00Z","timestamp":1225324800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/royalsociety.org\/journals\/ethics-policies\/data-sharing-mining\/"}],"content-domain":{"domain":["royalsocietypublishing.org"],"crossmark-restriction":true},"short-container-title":["Phil. Trans. R. Soc. A."],"published-print":{"date-parts":[[2009,1,28]]},"abstract":"<jats:p>A method for the detection of sleep apnoea, suitable for use in the home environment, is presented. The method automatically analyses night-time electrocardiogram (ECG) and oximetry recordings and identifies periods of normal and sleep-disordered breathing (SDB). The SDB is classified into one of six classes: obstructive, mixed and central apnoeas, and obstructive, mixed and central hypopnoeas. It also provides an estimated apnoea, hypopnoea and apnoea\u2013hypopnoea index. The basis of the method is a pattern recognition system that identifies episodes of apnoea by analysing the heart variability, an ECG-derived respiration signal and blood oximetry values. The method has been tested on 183 subjects with a range of apnoea severities who have undergone a full overnight polysomnogram study. The results show that the method separates control subjects from subjects with clinically significant sleep apnoea with a specificity of 83 per cent and sensitivity of 95 per cent. These results demonstrate that home-based screening for sleep apnoea is a viable alternative to hospital-based tests with the added benefit of low cost and minimal waiting times.<\/jats:p>","DOI":"10.1098\/rsta.2008.0156","type":"journal-article","created":{"date-parts":[[2008,10,30]],"date-time":"2008-10-30T21:16:27Z","timestamp":1225401387000},"page":"369-389","update-policy":"https:\/\/doi.org\/10.1098\/crossmark-policy","source":"Crossref","is-referenced-by-count":32,"title":["Multimodal detection of sleep apnoea using electrocardiogram and oximetry signals"],"prefix":"10.1098","volume":"367","author":[{"given":"Philip","family":"de Chazal","sequence":"first","affiliation":[{"name":"BiancaMed, NovaUCD, University College DublinBelfield, Dublin 4, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Conor","family":"Heneghan","sequence":"additional","affiliation":[{"name":"BiancaMed, NovaUCD, University College DublinBelfield, Dublin 4, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Walter T","family":"McNicholas","sequence":"additional","affiliation":[{"name":"Respiratory Sleep Disorders Unit, St Vincent's University HospitalDublin 4, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"175","published-online":{"date-parts":[[2008,10,30]]},"reference":[{"key":"e_1_3_1_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/sleep\/22.5.667"},{"key":"e_1_3_1_3_1","unstructured":"Armitage P Statistical methods in medical research. 2nd edn. 1987 Boston MA:Blackwell Scientific Publications."},{"key":"e_1_3_1_4_1","doi-asserted-by":"crossref","unstructured":"Bishop C.M Neural networks for pattern recognition. 1995 New York NY:Oxford University Press.","DOI":"10.1201\/9781420050646.ptb6"},{"key":"e_1_3_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/3468.477860"},{"key":"e_1_3_1_6_1","doi-asserted-by":"publisher","DOI":"10.1136\/thx.54.11.968"},{"key":"e_1_3_1_7_1","doi-asserted-by":"publisher","DOI":"10.1161\/01.HYP.0000107251.49515.c2"},{"key":"e_1_3_1_8_1","doi-asserted-by":"publisher","DOI":"10.1183\/09031936.03.00098002"},{"key":"e_1_3_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.1984.325351"},{"key":"e_1_3_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2003.812203"},{"key":"e_1_3_1_11_1","unstructured":"de Chazal P. 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