September 10, 2025Computer Methods in Biomechanics & Biomedical Engineering

A robust deep learning-driven framework for detecting Parkinson’s disease using EEG

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Why the study?

Accurate and early diagnosis of Parkinson's disease is essential for enhancing well-being and ensuring effective treatment.

Does a deep learning-based approach using EEG signals accurately detect Parkinson's disease?

Population

PD-affected patients and healthy control subjects

Authors

PMPrithwijit MukherjeeUniversity of Calcutta ARAnisha Halder RoyUniversity of Calcutta

Discussion

Member takes

Implication

Hypothesis-generating for EEG-based PD detection; leaves open prospective validation before any clinical use.

Structured PICO

Does a deep learning-based approach using EEG signals accurately detect Parkinson's disease?

Population

Parkinson's disease (PD) patients and healthy control subjects (EEG data)

Intervention

Deep learning-based approach using EEG signals (channel attention module, wavelet scattering transform, GAN for augmentation, and CNN-Transformer-based model)

Outcome

Accuracy of Parkinson's disease detection

A novel deep learning framework utilizing EEG signals and GAN augmentation achieved high accuracy (99.52%) in detecting Parkinson's disease.

Cite This Study

Mukherjee et al. (2025) studied this question.

synapsesocial.com/papers/6a89cca00f137e402b3365fe https://doi.org/10.1080/10255842.2025.2556310

View Full Paper

Ask AI

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A robust deep learning-driven framework for detecting Parkinson’s disease using EEG

Discussion

Member takes

Implication

Structured PICO

Cite This Study

A robust deep learning-driven framework for detecting Parkinson’s disease using EEG

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Also Consider