{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T05:02:59Z","timestamp":1768885379842,"version":"3.49.0"},"reference-count":66,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2021,7,28]],"date-time":"2021-07-28T00:00:00Z","timestamp":1627430400000},"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>Functional near infrared spectroscopy (fNIRS) is a neuroimaging technique that allows to monitor the functional hemoglobin oscillations related to cortical activity. One of the main issues related to fNIRS applications is the motion artefact removal, since a corrupted physiological signal is not correctly indicative of the underlying biological process. A novel procedure for motion artifact correction for fNIRS signals based on wavelet transform and video tracking developed for infrared thermography (IRT) is presented. In detail, fNIRS and IRT were concurrently recorded and the optodes\u2019 movement was estimated employing a video tracking procedure developed for IRT recordings. The wavelet transform of the fNIRS signal and of the optodes\u2019 movement, together with their wavelet coherence, were computed. Then, the inverse wavelet transform was evaluated for the fNIRS signal excluding the frequency content corresponding to the optdes\u2019 movement and to the coherence in the epochs where they were higher with respect to an established threshold. The method was tested using simulated functional hemodynamic responses added to real resting-state fNIRS recordings corrupted by movement artifacts. The results demonstrated the effectiveness of the procedure in eliminating noise, producing results with higher signal to noise ratio with respect to another validated method.<\/jats:p>","DOI":"10.3390\/s21155117","type":"journal-article","created":{"date-parts":[[2021,7,28]],"date-time":"2021-07-28T21:21:04Z","timestamp":1627507264000},"page":"5117","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["A Motion Artifact Correction Procedure for fNIRS Signals Based on Wavelet Transform and Infrared Thermography Video Tracking"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1903-0501","authenticated-orcid":false,"given":"David","family":"Perpetuini","sequence":"first","affiliation":[{"name":"Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1506-1995","authenticated-orcid":false,"given":"Daniela","family":"Cardone","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2282-3537","authenticated-orcid":false,"given":"Chiara","family":"Filippini","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5347-8417","authenticated-orcid":false,"given":"Antonio Maria","family":"Chiarelli","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"given":"Arcangelo","family":"Merla","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1111\/nyas.13948","article-title":"The Present and Future Use of Functional Near-infrared Spectroscopy (FNIRS) for Cognitive Neuroscience","volume":"1464","author":"Pinti","year":"2020","journal-title":"Ann. N.Y. Acad. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1016\/j.neuroimage.2012.03.049","article-title":"A Brief Review on the History of Human Functional Near-Infrared Spectroscopy (FNIRS) Development and Fields of Application","volume":"63","author":"Ferrari","year":"2012","journal-title":"Neuroimage"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Quaresima, V., and Ferrari, M. (2019). A Mini-Review on Functional Near-Infrared Spectroscopy (FNIRS): Where Do We Stand, and Where Should We Go?. 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