Entropy Analysis of Electroencephalography for Post-Stroke Dysphagia Assessment

Area of Science:

• Neuroscience
• Biomedical Engineering
• Clinical Neurology

Background:

• Dysphagia affects over 50% of stroke patients, posing diagnostic and management challenges.
• Dysphagia is linked to disrupted cortical and subcortical neural activity, observable in electroencephalography (EEG) patterns.
• Sample Entropy (SampEn) measures signal complexity and can potentially identify dysphagia-related abnormalities.

Purpose of the Study:

• To identify quantitative dysphagia biomarkers using SampEn from EEG recordings in post-stroke patients.
• To investigate alterations in neural activity associated with swallowing in individuals with and without dysphagia post-stroke.

Main Methods:

• Calculated SampEn in theta, alpha, and beta EEG frequency bands during a repetitive swallowing task.
• Analyzed data from three groups: healthy individuals, stroke patients without dysphagia, and stroke patients with dysphagia.
• Utilized EEG, a non-invasive and cost-efficient neuroimaging technique.

Main Results:

• Post-stroke patients (with and without dysphagia) showed significant SampEn differences compared to healthy subjects in alpha and theta bands, indicating widespread brain dynamic alterations.
• A significant cluster in the left parietal region (beta band) during swallowing exhibited higher SampEn in dysphagic patients versus healthy individuals and controls.
• These findings suggest impaired sensorimotor integration and disrupted cortical coordination in dysphagia.

Conclusions:

• SampEn analysis of EEG signals provides a robust and objective biomarker for neurogenic dysphagia.
• This method can aid in the diagnosis of dysphagia and monitor therapeutic interventions.
• EEG-based SampEn quantification offers a cost-efficient approach to understanding and managing post-stroke swallowing impairments.