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MMAI - Mobile Moods AI; Electroencephalography Artifact Detection; Towards Objective Assessment of Mental States

Stock, Simon; Mazura, Florian; De La Torre, Fernando Gomez; Gerdes, Marius; Schinle, Markus; Stork, Wilhelm

The inner workings of the human mind remain a mystery to this day. A core element of philosophy and science is to understand ourselves better. However, it is a tough challenge to perceive what is going on in someone's head. Questionnaires and interviews can provide some degree of insight into what a subject is thinking or feeling, but misinterpretations are a common problem. Therefore, we firmly believe that an ambulatory brain-computer interface system that can capture mental states will significantly impact our scientific understanding. This paper introduces Mobile Moods AI (MMAI), a software pipeline for AI evaluation of brain data. Still, the data we can extract from even modern Electroencephalography (EEG) devices are very susceptible to interferences. Hence, we introduce and evaluate an AI-based artifact detection approach. Furthermore, the overall concept of the MMAI system is outlined.

DOI: 10.1109/ICECCME52200.2021.9590972
Zugehörige Institution(en) am KIT Institut für Technik der Informationsverarbeitung (ITIV)
Karlsruhe School of Optics & Photonics (KSOP)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 10.2021
Sprache Englisch
Identifikator ISBN: 978-1-6654-1262-9
KITopen-ID: 1000139987
Erschienen in 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
Veranstaltung International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2021), Mauritius, 07.10.2021 – 08.10.2021
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 01–06
Nachgewiesen in Scopus
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