ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2026
[Application of support vector machine in identifying neuromodulation states in patients with zoster-associated pain].
Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesSpinal cord stimulation (SCS) is a commonly used treatment for refractory zoster-associated pain (ZAP). The conventional open-loop regulation mode mainly relies on patients' subjective feedback for manual parameter adjustment, whereas the clinical application of closed-loop SCS regulation remains immature and requires further optimization. Previous studies have shown that SCS can influence electroencephalography (EEG) functional connectivity. This study aims to investigate whether a support vector machine (SVM) based on EEG functional connectivity features can effectively identify different neuromodulation states of SCS.
methodsA total of 21 patients with ZAP who underwent SCS treatment were retrospectively included. Visual Analogue Scale (VAS) scores were recorded before SCS implantation, at discharge, and at 1, 3, and 6 months postoperatively. EEG data lasting 5-10 minutes were collected under SCS-on and SCS-off conditions. The EEG data were randomly divided into a training set and a test set at a ratio of 7∶3. Pearson correlation coefficient (PCC) and coherence (COH) between EEG feature channels were extracted to construct an SVM-based classification model. Model performance in distinguishing SCS-on and SCS-off EEG states was evaluated using accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Shapley additive explanations (SHAP) were used to interpret the SVM model by analyzing the contribution and direction of each EEG feature to the model prediction.
resultsSCS effectively alleviated pain in patients with ZAP. Compared with baseline, VAS scores were significantly reduced at discharge and at 1, 3, and 6 months after SCS treatment (all
conclusionsThe SVM model based on EEG functional connectivity features can effectively identify different neuromodulation states of SCS in patients with ZAP. These findings suggest that SCS may induce alterations in brain functional connectivity and provide a basis for future studies on EEG-based closed-loop SCS regulation.
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