Classifying social and physical pain from multimodal physiological signals using machine learning.

ABSTRACT: Accurate pain assessment is essential for effective management; however, most studies have focused on differentiating pain from non-pain or estimating pain intensity rather than distinguishing between distinct pain types. We present a machine learning method for classifying physical and social pain using physiological signals. Seventy-three healthy adults participated in experiments involving baseline, neutral, and pain-inducing stimuli related to both types of pain. Physical pain was elicited by pressure cuff inflation, whereas social pain was induced by watching a video depicting a loved one's death. The electrocardiogram, electrodermal activity, photoplethysmogram, respiration, and finger temperature were recorded, and 12 physiological features were extracted. Three machine learning alg

SUBMITTER: Jang EH 

PROVIDER: S-EPMC12307811 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature