Affect Recognition in Muscular Response Signals
نویسندگان
چکیده
This study investigated the potential of recognising arousal in motor activity collected by wrist-worn accelerometers. We hypothesise that emotional emerges from generalised central nervous system which embeds affective states within activity. formulate detection as a statistical problem separating two sets - under and without arousal. propose novel test regime based on machine learning assuming can be distinguished if classifier separate better than random guessing. To increase power testing regime, performance classifiers is evaluated cross-validation framework, to perform guessing, repeated corrected t-test used. The were basis accuracy Matthew’s correlation coefficient. suggested procedures further compared against traditional multivariate paired Hotelling’s T-squared test. achieved an about 60%, according proposed significantly demonstrated higher test, we conclude distinguish between it.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2023
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2023.3279720