{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T04:40:24Z","timestamp":1789015224353,"version":"build-2803163510"},"reference-count":66,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,18]],"date-time":"2020-09-18T00:00:00Z","timestamp":1600387200000},"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: Heartbeat detection is a crucial step in several clinical fields. Laser Doppler Vibrometer (LDV) is a promising non-contact measurement for heartbeat detection. The aim of this work is to assess whether machine learning can be used for detecting heartbeat from the carotid LDV signal. Methods: The performances of Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF) and K-Nearest Neighbor (KNN) were compared using the leave-one-subject-out cross-validation as the testing protocol in an LDV dataset collected from 28 subjects. The classification was conducted on LDV signal windows, which were labeled as beat, if containing a beat, or no-beat, otherwise. The labeling procedure was performed using electrocardiography as the gold standard. Results: For the beat class, the f1-score (f1) values were 0.93, 0.93, 0.95, 0.96 for RF, DT, KNN and SVM, respectively. No statistical differences were found between the classifiers. When testing the SVM on the full-length (10 min long) LDV signals, to simulate a real-world application, we achieved a median macro-f1 of 0.76. Conclusions: Using machine learning for heartbeat detection from carotid LDV signals showed encouraging results, representing a promising step in the field of contactless cardiovascular signal analysis.<\/jats:p>","DOI":"10.3390\/s20185362","type":"journal-article","created":{"date-parts":[[2020,9,18]],"date-time":"2020-09-18T10:22:23Z","timestamp":1600424543000},"page":"5362","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Heartbeat Detection by Laser Doppler Vibrometry and Machine Learning"],"prefix":"10.3390","volume":"20","author":[{"given":"Luca","family":"Antognoli","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering and Mathematical Sciences, Universit\u00e0 Politecnica delle Marche, 60121 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara","family":"Moccia","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, 60121 Ancona, Italy"},{"name":"Department of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genoa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucia","family":"Migliorelli","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, 60121 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9909-0816","authenticated-orcid":false,"given":"Sara","family":"Casaccia","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Mathematical Sciences, Universit\u00e0 Politecnica delle Marche, 60121 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4728-3736","authenticated-orcid":false,"given":"Lorenzo","family":"Scalise","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Mathematical Sciences, Universit\u00e0 Politecnica delle Marche, 60121 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8893-9244","authenticated-orcid":false,"given":"Emanuele","family":"Frontoni","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, 60121 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,18]]},"reference":[{"key":"ref_1","first-page":"354","article-title":"Heart rate variability: Standards of measurement, physiological interpretation, and clinical use","volume":"17","author":"Malik","year":"1996","journal-title":"Task Force Eur. 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