ArticleMedical & biological engineering & computing2026
Multisensory integration task-based age group classification in early-mid adulthood.
Article in Medical & biological engineering & computing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
This preliminary study investigates the temporal dynamics of multisensory integration in early to mid-adulthood. Five regions of interest (ROIs) were identified, and integration times from 0 to 500 ms were analyzed. The impact of temporal asynchrony on audio-visual integration was assessed through behavioral analysis. Brain topography-based age-related differences in multisensory processing, particularly in the middle-aged group, were observed. Early integration consistently occurs between 200 and 325 ms across age groups. Audio stimuli integrate slower than visual stimuli, with AV integration times falling in between. Delayed integration is observed in audio-leading conditions (A50V), while faster integration occurs in visual-leading conditions (V50A). ERP-based channel selection significantly enhances age group classification accuracy. The random forest classifier achieves 98.3% accuracy using a small set of 13 selected channels during the A50V task. This optimized channel selection improves the ergonomics of EEG-based age group classification and simplifies the clustering process. The study demonstrates the effectiveness of using minimal electrodes and straightforward features for multisensory integration tasks in early to mid-adulthood.
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