{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,29]],"date-time":"2026-03-29T00:00:03Z","timestamp":1774742403503,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T00:00:00Z","timestamp":1653436800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["PD\/BDE\/150304\/2019"],"award-info":[{"award-number":["PD\/BDE\/150304\/2019"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["2020.06024.BD"],"award-info":[{"award-number":["2020.06024.BD"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["PEest\/UID\/CEC\/04516\/2019"],"award-info":[{"award-number":["PEest\/UID\/CEC\/04516\/2019"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NOVA-LINCS","award":["PD\/BDE\/150304\/2019"],"award-info":[{"award-number":["PD\/BDE\/150304\/2019"]}]},{"name":"NOVA-LINCS","award":["2020.06024.BD"],"award-info":[{"award-number":["2020.06024.BD"]}]},{"name":"NOVA-LINCS","award":["PEest\/UID\/CEC\/04516\/2019"],"award-info":[{"award-number":["PEest\/UID\/CEC\/04516\/2019"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Wearable sensors have increasingly been applied in healthcare to generate data and monitor patients unobtrusively. Their application for Brain\u2013Computer Interfaces (BCI) allows for unobtrusively monitoring one\u2019s cognitive state over time. A particular state relevant in multiple domains is cognitive fatigue, which may impact performance and attention, among other capabilities. The monitoring of this state will be applied in real learning settings to detect and advise on effective break periods. In this study, two functional near-infrared spectroscopy (fNIRS) wearable devices were employed to build a BCI to automatically detect the state of cognitive fatigue using machine learning algorithms. An experimental procedure was developed to effectively induce cognitive fatigue that included a close-to-real digital lesson and two standard cognitive tasks: Corsi-Block task and a concentration task. Machine learning models were user-tuned to account for the individual dynamics of each participant, reaching classification accuracy scores of around 70.91 \u00b1 13.67 %. We concluded that, although effective for some subjects, the methodology needs to be individually validated before being applied. Moreover, time on task was not a particularly determining factor for classification, i.e., to induce cognitive fatigue. Further research will include other physiological signals and human\u2013computer interaction variables.<\/jats:p>","DOI":"10.3390\/s22114010","type":"journal-article","created":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T08:41:33Z","timestamp":1653468093000},"page":"4010","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Automatic Cognitive Fatigue Detection Using Wearable fNIRS and Machine Learning"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0237-3412","authenticated-orcid":false,"given":"Rui","family":"Varandas","sequence":"first","affiliation":[{"name":"LIBPhys (Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics), Faculdade de Ci\u00eancias e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal"},{"name":"PLUX Wireless Biosignals S.A., 1050-059 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4030-9526","authenticated-orcid":false,"given":"Rodrigo","family":"Lima","sequence":"additional","affiliation":[{"name":"Departamento de Engenharia Inform\u00e1tica, Universidade da Madeira & Madeira N-LINCS, 9020-105 Funchal, Portugal"},{"name":"NOVA Laboratory for Computer Science and Informatics, 2829-516 Caparica, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4452-0414","authenticated-orcid":false,"given":"Sergi","family":"Berm\u00fadez I Badia","sequence":"additional","affiliation":[{"name":"Departamento de Engenharia Inform\u00e1tica, Universidade da Madeira & Madeira N-LINCS, 9020-105 Funchal, Portugal"},{"name":"NOVA Laboratory for Computer Science and Informatics, 2829-516 Caparica, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6764-8432","authenticated-orcid":false,"given":"Hugo","family":"Silva","sequence":"additional","affiliation":[{"name":"PLUX Wireless Biosignals S.A., 1050-059 Lisboa, Portugal"},{"name":"Instituto de Telecomunica\u00e7\u00f5es (IT), 1049-001 Lisbon, Portugal"},{"name":"Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4022-7424","authenticated-orcid":false,"given":"Hugo","family":"Gamboa","sequence":"additional","affiliation":[{"name":"LIBPhys (Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics), Faculdade de Ci\u00eancias e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal"},{"name":"PLUX Wireless Biosignals S.A., 1050-059 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Henriksen, A., Haugen Mikalsen, M., Woldaregay, A.Z., Muzny, M., Hartvigsen, G., Hopstock, L.A., and Grimsgaard, S. 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