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Toward Objectification of Subjective Chronic Pain Based on Implicit Response in Biosignals
IEEE Transactions on Bio-Medical Engineering
|September 2, 2024
Summary
This study introduces a new method for assessing chronic pain using multiple biosignals like EEG and PPG. The developed model accurately quantifies pain, offering a promising alternative to subjective assessments.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Physiology
Background:
- Chronic pain management requires accurate and early evaluation, but current subjective methods have limitations.
- Developing objective assessment tools is crucial for effective pain intervention.
Purpose of the Study:
- To develop and validate a novel chronic pain assessment method utilizing multi-modal biosignals.
- To enhance the accuracy of chronic pain evaluation beyond traditional subjective questionnaires.
Main Methods:
- A model was developed using electroencephalogram (EEG), photoplethysmogram (PPG), electrocardiogram (ECG), and facial temperature (FT) data from 59 subjects.
- 112 features were extracted from the biosignals, with 17 showing significant differences between chronic pain patients and controls.
Main Results:
- The multi-modal biosignal model significantly improved chronic pain classification accuracy (AUROC increased from 0.802 to 0.864).
- Key features identified included PPG systolic length, EEG alpha band power, and delta band power.
Conclusions:
- The developed multi-modal biosignal approach demonstrates significant potential for objective chronic pain quantification.
- This method offers a promising advancement for the clinical assessment and management of chronic pain.
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