Simultaneous ECG-EEG Recordings for Arrhythmia Detection, 478 Patient Sample

478 routine electroencephalogram recordings with simultaneous 2-lead electrocardiogram data from patients aged 16 to 95, collected between January and March 2016. The dataset was analyzed by cardiology specialist Halil Önder to investigate arrhythmia rates. Findings include ventricular extrasystole in 5.6% of patients and a 17% overall arrhythmia detection rate by cardiologist evaluation.

Use Cases

• Train models to detect ventricular extrasystoles based on simultaneous ECG-EEG signals.
• Compare automated arrhythmia detection rates with neurologist keyword screening mentioned in the description.
• Analyze the correlation between patient age and specific arrhythmia subtypes like atrial fibrillation.
• Benchmark ECG abnormality detection algorithms using the cardiologist-interpreted labels.
• Study the discrepancy in detection rates between specialist cardiologist evaluation and routine EEG report screening.

Strengths

• Includes 478 patient records with a defined age range of 16 to 95 years.
• Provides cardiologist-evaluated labels for multiple arrhythmia subtypes, with specific counts like 27 cases of ventricular extrasystole.
• Contains a direct comparison metric: 17% arrhythmia detection by cardiologist vs. 9.4% keyword presence in EEG reports.

Limitations

• Row count for the underlying data is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect temporal and institutional bias inherent to the single study described.

Provenance

Source

Halil Önder

Collection Method

Retrospective analysis of simultaneous 2-lead ECG recordings during routine EEG.

Time Range

January to March 2016