A New Hybrid Algorithm Proposed for the Analysis and Classification of Signals Obtained from Head Movements

In this paper, we present a new algorithm that combines Hu invariant moments, data preprocessing techniques, and fuzzy logic to analyze and classify signals obtained from the macro and micro head movements that a person makes. Firstly, we project different videos to elicit the disgust emotion in various participants. Following the stimulation, we recorded all the participants' reactions on video. The next step is to apply Hu moments to transform the different movements that the participant made to create a signal. This process yields polynomial regression and applies normalization methods to standardize the size and numerical scale of all signals. We implement a fuzzy inference system to classify the signals. The results presented by this algorithm show high performance in sorting movements to detect disgust emotion. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1120Dimensions.Open Alex.