{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T08:37:30Z","timestamp":1775032650068,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,12]],"date-time":"2018-02-12T00:00:00Z","timestamp":1518393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Background: Fragmentation and delayed potentials in the QRS signal of patients have been postulated as risk markers for Sudden Cardiac Death (SCD). The analysis of the high-frequency spectral content may be useful for quantification. Methods: Forty-two consecutive patients with prior history of SCD or malignant arrhythmias (patients) where compared with 120 healthy individuals (controls). The QRS complexes were extracted with a modified Pan-Tompkins algorithm and processed with the Continuous Wavelet Transform to analyze the high-frequency content (85\u2013130 Hz). Results: Overall, the power of the high-frequency content was higher in patients compared with controls (170.9 vs. 47.3 103nV2Hz\u22121; p = 0.007), with a prolonged time to reach the maximal power (68.9 vs. 64.8 ms; p = 0.002). An analysis of the signal intensity (instantaneous average of cumulative power), revealed a distinct function between patients and controls. The total intensity was higher in patients compared with controls (137.1 vs. 39 103nV2Hz\u22121s\u22121; p = 0.001) and the time to reach the maximal intensity was also prolonged (88.7 vs. 82.1 ms; p &lt; 0.001). Discussion: The high-frequency content of the QRS complexes was distinct between patients at risk of SCD and healthy controls. The wavelet transform is an efficient tool for spectral analysis of the QRS complexes that may contribute to stratification of risk.<\/jats:p>","DOI":"10.3390\/s18020560","type":"journal-article","created":{"date-parts":[[2018,2,12]],"date-time":"2018-02-12T10:50:38Z","timestamp":1518432638000},"page":"560","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Analysis of the High-Frequency Content in Human QRS Complexes by the Continuous Wavelet Transform: An Automatized Analysis for the Prediction of Sudden Cardiac Death"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4747-2497","authenticated-orcid":false,"given":"Daniel","family":"Garc\u00eda Iglesias","sequence":"first","affiliation":[{"name":"Arrhythmia Unit, Hospital Universitario Central de Asturias, 33011 Oviedo, Spain"},{"name":"Instituto de Investigaci\u00f3n Sanitaria del Principado de Asturias, 33011 Oviedo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nieves","family":"Roque\u00f1i Guti\u00e9rrez","sequence":"additional","affiliation":[{"name":"Grupo para la Modelizaci\u00f3n Matem\u00e1tica Avanzada (MOMA), Universidad de Oviedo, 33004 Oviedo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francisco","family":"De Cos","sequence":"additional","affiliation":[{"name":"Grupo para la Modelizaci\u00f3n Matem\u00e1tica Avanzada (MOMA), Universidad de Oviedo, 33004 Oviedo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Calvo","sequence":"additional","affiliation":[{"name":"Arrhythmia Unit, Hospital Universitario Central de Asturias, 33011 Oviedo, Spain"},{"name":"Instituto de Investigaci\u00f3n Sanitaria del Principado de Asturias, 33011 Oviedo, Spain"},{"name":"Grupo para la Modelizaci\u00f3n Matem\u00e1tica Avanzada (MOMA), Universidad de Oviedo, 33004 Oviedo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2335","DOI":"10.1161\/CIRCULATIONAHA.110.976092","article-title":"Sudden Cardiac Death Prediction and Prevention","volume":"122","author":"From","year":"2010","journal-title":"Circulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.hrthm.2015.08.038","article-title":"Risk stratification in brugada syndrome: Clinical characteristics, electrocardiographic parameters and auxiliary testing","volume":"13","author":"Adler","year":"2016","journal-title":"Heart Rhythm"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1697","DOI":"10.1161\/CIRCULATIONAHA.108.770917","article-title":"Fragmented QRS as a marker of conduction abnormality and a predictor of prognosis of Brugada syndrome","volume":"118","author":"Morita","year":"2008","journal-title":"Circulation"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1161\/CIRCEP.107.763284","article-title":"Fragmented Wide QRS on a 12-Lead ECG. 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