Work

EEG Mortality Dataset in Parkinson's Disease

Year: 2026

Type: dataset

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.

Source: UC San Diego

DOI: 10.82901/nemar.on007020.v1.0.0

Authors: Simin Jamshidi, Arturo Espinoza, Soura Dasgupta, Nandakumar Narayanan

Language: English

Topic: Parkinson's Disease Mechanisms and Treatments

Subfield: Neurology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7166547867

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