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When incorporating subjectively-derived HIFs into the QoE model, gains of up to 26.3\u00a0% could be found relative to utilizing only technological factors. When utilizing HIFs derived from an electroencephalography (EEG) based aBCI, in turn, gains of up to 14.5\u00a0% were observed. These findings show the importance of using aBCIs in QoE measurement and also highlight that further improvement may be warranted once improved affective state correlates are found from EEGs and\/or other neurophysiological modalities.<\/jats:p>","DOI":"10.1186\/s13673-016-0062-5","type":"journal-article","created":{"date-parts":[[2016,4,9]],"date-time":"2016-04-09T00:47:12Z","timestamp":1460162832000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Using affective brain-computer interfaces to characterize human influential factors for speech quality-of-experience perception modelling"],"prefix":"10.1186","volume":"6","author":[{"given":"Rishabh","family":"Gupta","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Khalil","family":"Laghari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hubert","family":"Banville","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tiago H.","family":"Falk","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,5,5]]},"reference":[{"key":"62_CR1","first-page":"37","volume":"2007","author":"R Leeb","year":"2012","unstructured":"Leeb R et al (2012) A tetraplegic patient controls a wheelchair in virtual reality. 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