Toward Objectification of Subjective Chronic Pain based on Implicit Response in Biosignals.
IEEE Trans Biomed Eng
; PP2024 Sep 02.
Article
em En
| MEDLINE
| ID: mdl-39222459
ABSTRACT
OBJECTIVE:
Chronic pain necessitates early intervention and accurate evaluation. Current subjective questionnaire -based methods have limitations. This study aims to develop a chronic pain assessment method based on multi-modal biosignal and to validate its feasibility.METHODS:
We present a model utilizing electroencephalogram (EEG), photoplethysmogram (PPG), electrocardiogram (ECG), and facial temperature (FT) data from 59 subjects (26 chronic pain patients). A total of 112 features were derived from all signals, and 17 of them showed a significant difference between the chronic pains and the normal control.RESULTS:
By optimizing signal types and feature combinations, our pain classification model significantly enhanced chronic pain assessment (AUROC 0.802 to 0.864). Notable features included PPG systolic length (12.3%), EEG alpha band power (11.1%), and delta band power (9.4%).CONCLUSION:
This multi-modal biosignal approach holds promise for effective chronic pain quantification.
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Base de dados:
MEDLINE
Idioma:
En
Revista:
IEEE Trans Biomed Eng
Ano de publicação:
2024
Tipo de documento:
Article