What question did this study set out to answer?

To present a curated dataset of EEG and ECG recordings to establish normative data and develop age prediction algorithms.

May 7, 2026Open Access

A dataset of EEG and ECG recordings around the onset of NREM sleep from infancy to adolescence

NSNathan J. StevensonQIMR Berghofer Medical Research Institute KIKartik K. IyerQIMR Berghofer Medical Research Institute JRJames A. RobertsThe University of Queensland

Key Points

To present a curated dataset of EEG and ECG recordings to establish normative data and develop age prediction algorithms.
Curated dataset includes EEG and ECG recordings from 1032 subjects aged 2 months to 16 years.
Subjects underwent clinical review to confirm neurodevelopmental appropriateness over four years post-recording.
Data collection supports the training of machine learning models for pediatric brain activity analysis.
Dataset facilitates the establishment of normative ranges for pediatric EEG/ECG across age groups.
Enables development of algorithms for predicting brain age gaps based on EEG/ECG data.
Supports research into the neurodevelopmental trajectories of brain activity in children.

Abstract

Abstract Paediatric brain activity can be measured effectively during light sleep; a vigilance state that manifests with similar phenomenology on the EEG across childhood. Here, we describe a curated dataset of EEG and ECG recordings from 1032 subjects from 2 months to 16 years of age (Helsinki Kids 1 K – HK1K). All subjects had age-appropriate EEG and ECG recordings, along with typical neurodevelopment, as confirmed by a clinical review of their medical records over the four years following the recording. These data can be used to define normative ranges of paediatric EEG/ECG, train foundation models of paediatric EEG/ECG, and generate age prediction algorithms that underpin measures of brain age gap.

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