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Article Dans Une Revue Behavioural Brain Research Année : 2024

Evaluation of a headphones-fitted EEG system for the recording of auditory evoked potentials and mental workload assessment

Résumé

Advancements in portable neuroimaging technologies open up new opportunities to gain insight into the neural dynamics and cognitive processes underlying day-to-day behaviors. In this study, we evaluated the relevance of a headphone- mounted electroencephalogram (EEG) system for monitoring mental workload. The participants (N=12) were instructed to pay attention to auditory alarms presented sporadically while performing the Multi-Attribute Task Battery (MATB) whose difficulty was staged across three conditions to manipulate mental workload. The P300 Event-Related Potentials (ERP) elicited by the presentation of auditory alarms were used as probes of attentional resources available. The amplitude and latency of P300 ERPs were compared across experimental conditions. Our findings indicate that the P300 ERP component can be captured using a headphone-mounted EEG system. Moreover, neural responses to alarm could be used to classify mental workload with high accuracy (over 80%) at a single-trial level. Our analyses indicated that the signal-to-noise ratio acquired by the sponge-based sensors remained stable throughout the recordings. These results highlight the potential of portable neuroimaging technology for the development of neuroassistive applications while underscoring the current limitations and challenges associated with the integration of EEG sensors in everyday-life wearable technologies. Overall, our study contributes to the growing body of research exploring the feasibility and validity of wearable neuroimaging technologies for the study of human cognition and behavior in real-world settings.
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Dates et versions

hal-04369353 , version 1 (02-01-2024)

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Simon Ladouce, Max Pietzker, Dietrich Manzey, Frederic Dehais. Evaluation of a headphones-fitted EEG system for the recording of auditory evoked potentials and mental workload assessment. Behavioural Brain Research, 2024, 460, pp.114827. ⟨10.1016/j.bbr.2023.114827⟩. ⟨hal-04369353⟩
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