A Complete Pipeline for Heart Rate Extraction from Infant ECG

Harry Thomas Mason*, Priscilla Martinez Cedillo, Quoc Vuong, Maria Del Carmen Garcia De Soria Bazan, Stephen Leslie Smith, Elena Geangu, Marina Iuliana Knight

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Infant electrocardiograms (ECG) and heart rates (HR) are very useful biosignals for psychological research and clinical work, but can be hard to analyze properly, particularly long form (≥5 minutes) recordings taken in naturalistic environments. Infant HRs are typically much faster than adult HRs, and so some of the underlying frequency assumptions made about adult ECGs may not hold for infants. However, the bulk of publicly available ECG approaches focus on adult data. Here, existing open-source ECG approaches are tested on infant datasets. The best performing open-source method is then modified to maximize its performance on infant data (e.g., including a 15Hz high pass filter, adding local peak correction). The HR signal is then subsequently analyzed, developing an approach for cleaning data with separate sets of parameters for the analysis of cleaner and noisier HR. A Signal Quality Index (SQI) for HR is also developed, providing insight into where a signal is recoverable and where it is not, allowing for more confidence in analysis performed on naturalistic recordings. The tools developed and reported in this paper provide a base for future analysis of infant ECG and related biophysical characteristics. Of particular importance, the proposed solutions outlined here can be efficiently applied to real-world large datasets.
Original languageEnglish
Publication statusAccepted/In press - 6 Mar 2024

Bibliographical note

© 2023 by the authors


  • ECG
  • Infant ECG
  • Heart Rate
  • R-Peaks
  • Open-Source
  • Naturalistic
  • Longform

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