A Spatiotemporal Deep Learning Framework for Scalp EEG-Based Automated Pain Assessment in Children.

Journal: IEEE transactions on bio-medical engineering

PMID: 38231823

Abstract

OBJECTIVE: Common pain assessment approaches such as self-evaluation and observation scales are inappropriate for children as they require patients to have reasonable communication ability. Subjective, inconsistent, and discontinuous pain assessment in children may reduce therapeutic effectiveness and thus affect their later life.

Authors

Zanhao Fu
Huaiyu Zhu
Yi Zhang

Department of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Jilin University, Changchun, China.
Ruohong Huan
Shuohui Chen
Yun Pan

School of Computer and Cyberspace Security, Communication University of China, Beijing 100024, China.

Keywords

Adolescent Child Child, Preschool Deep Learning Electroencephalography Female Humans Male Pain Pain Measurement Scalp Signal Processing, Computer-Assisted

External Resources

View on PubMed Access via DOI PubMed (38231823)

A Spatiotemporal Deep Learning Framework for Scalp EEG-Based Automated Pain Assessment in Children.

Abstract

Authors

Keywords

External Resources

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