An AI recognition method for children's clinical operative pain by skin potential (SP) signal.

ABSTRACT:

Objective and rationale

Children's clinical pain phenotypes are complex, and there is a lack of objective biological diagnostic markers and cognitive patterns. Detecting physiological signals through wearable devices simplifies disease diagnosis and holds the potential for remote medical applications.

Method and results

This research established a pain recognition model based on AI skin potential (SP) signal analysis. A total of 237 subjects participated in this study, comprising 152 boys and 85 girls, ranging in age from 2 to 16 years old. Initially, we preprocessed SP signals and built datasets for pain and non-pain conditions, including 195 pain and 97 non-pain samples. Then, we applied wavelet transform (WT) to capture the time-frequency characteristics of the signals an

SUBMITTER: Huang M 

PROVIDER: S-EPMC11750553 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature