The purpose of this disclosure is to provide a computer
system based on a quantitative pain model, comprising: a preprocessing module, a local temporal
feature extraction module, a cross-domain global
frequency domain feature extraction module, a cross-domain interactive fusion module, a
feature fusion module, and a classification output module. Through a dual-
parallel processing architecture of local temporal and cross-domain global pathways, multi-scale
convolution and sliding window temporal modeling are used to accurately capture transient and evolutionary temporal features related to pain. Then, through
wavelet transform and attention mechanisms,
frequency domain oscillation energy closely related to the physiological mechanisms of pain is explicitly extracted. Finally, a cross-domain interactive
encoder is used for deep fusion, achieving complementarity and enhancement of temporal and
frequency domain features. This disclosure effectively controls the computational scale while maintaining high-precision classification, making it easier to deploy lightweight and perform real-time
inference on embedded devices or mobile medical terminals, demonstrating significant practical value.