Evaluation method of Driver’s olfactory preferences: a machine learning model based on multimodal physiological signals

machine learning 0302 clinical medicine in-vehicle fragrance physiological signal 0202 electrical engineering, electronic engineering, information engineering Bioengineering and Biotechnology driving comfort TP248.13-248.65 olfactory preference Biotechnology
DOI: 10.3389/fbioe.2024.1433861 Publication Date: 2024-12-18T06:44:09Z
ABSTRACT
Assessing the olfactory preferences of drivers can help improve odor environment and enhance comfort during driving. However, current evaluation methods have limited availability, including subjective evaluation, electroencephalogram, behavioral action methods. Therefore, this study explores potential autonomic response signals for assessing preferences.
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