An emotion classification method and device based on pulse wave time sequence analysis. The method comprises: acquiring pulse wave time sequences by means of photoplethysmography (S1); constructing characteristic representations of the pulse wave time sequences according to the pulse wave time sequences (S2); training a support vector machine according to the characteristic representations of the pulse wave time sequences and corresponding emotional tags (S3); and classifying emotions for the pulse wave time sequences by means of the support vector machine (S4). The method and device can accurately describe non-linear characteristics of pulse wave time sequences, and accurately recognize emotions according to these characteristics. Moreover, a user can accurately perform unperceivable emotion analysis on a test subject under in real time without being limited to the acquisition process of pulse wave time sequences, or places such as home and workplace.
EMOTION CLASSIFICATION METHOD AND DEVICE BASED ON PULSE WAVE TIME SEQUENCE ANALYSIS