Key result
Random forest model using skin conductance and respiration classifies emotionally induced pain with 0.83 F1 score.
Why the study?
To explore the feasibility of classifying perceived pain intensity despite identical stimuli using multimodal physiological signals and self-reported emotional ratings.
Can multimodal physiological signals and subjective emotional ratings accurately classify perceived pain intensity in healthy participants exposed to an identical anger-inducing stimulus?
Observational (n=112)
Can multimodal physiological signals and subjective emotional ratings accurately classify perceived pain intensity in healthy participants exposed to an identical anger-inducing stimulus?
Effect estimate: F1 score 0.83
Multimodal physiological signals, particularly skin conductance, combined with subjective emotional ratings can effectively classify perceived pain intensity, supporting the development of personalized pain assessment systems.
We explore the feasibility of classifying perceived pain intensity—despite the stimulus being identical—using multimodal physiological signals and self-reported emotional ratings. A total of 112 healthy participants watched the same anger-inducing video, yet reported varying pain intensities (5, 6, or 7 on a 7-point scale). We recorded electrocardiogram, skin conductance (SC), respiration, photoplethysmogram results, and finger temperature, extracting 12 physiological features. Participants also rated their valence and arousal. Using a random forest model, we classified pain versus baseline and distinguished intensity levels. Compared to baseline, the painful stimulus altered heart rate variability, SC, respiration, and pulse transit time (PTT). Higher perceived pain correlated with more negative valence, higher arousal, and elevated SC, suggesting stronger sympathetic activation. The classification of baseline versus pain using SC and respiratory features reached an F1 score of 0.83. For intensity levels 6 versus 7, including PTT and skin conductance response along with valence achieved an F1 score of 0.73. These findings highlight distinct psychophysiological patterns that reflect perceived intensity under the same stimulus. SC features emerged as key biomarkers, while valence and arousal offered complementary insights, supporting the development of personalized, psychologically informed pain assessment systems.
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Jang et al. (2025) conducted an observational in Emotionally induced pain (n=112). Anger-inducing video vs. Baseline was evaluated on Classification of baseline versus pain using skin conductance and respiratory features (F1 score 0.83). A random forest model using skin conductance and respiratory features classified baseline versus emotionally induced pain with an F1 score of 0.83.
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