EEG Mortality Dataset in Parkinson's Disease

Simin Jamshidi; Arturo Espinoza; Soura Dasgupta; Nandakumar Narayanan

doi:10.82901/nemar.on007020

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EEG Mortality Dataset in Parkinson's Disease

Simin Jamshidi, Arturo Espinoza, Soura Dasgupta and Nandakumar Narayanan

NEMAR (Neuroelectromagnetic Data Archive and Tools Resource)

06/29/2026

DOI: 10.82901/nemar.on007020

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Abstract

This dataset comprises de-identified resting-state EEG recordings from individuals with Parkinson's disease and age-matched healthy controls, collected to evaluate whether EEG biomarkers can distinguish subjects with differential mortality outcomes. Recordings were acquired using standard clinical EEG systems at 500 Hz sampling rate with 10–20 electrode montage during eyes-open rest conditions. The dataset includes mortality classification labels (living/deceased) and is structured according to BIDS EEG standards, enabling investigation of EEG correlates of mortality risk and development of machine learning classification models.

Biomarkers

Neuroscience

BIDS

EEG

machine learning classification

mortality prediction

Parkinson's disease

resting-state

Details

Title: Subtitle: EEG Mortality Dataset in Parkinson's Disease
Creators: Simin Jamshidi
Arturo Espinoza
Soura Dasgupta
Nandakumar Narayanan
Resource Type: Dataset
DOI: 10.82901/nemar.on007020
Publisher: NEMAR (Neuroelectromagnetic Data Archive and Tools Resource)
Language: English
Date published: 06/29/2026
Academic Unit: Neurology; Iowa Neuroscience Institute
Record Identifier: 9985180969002771

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