Identifying heart rate characteristics of sleep states of preterm infants using video analysis

Objective is to identify changes in heart rate (HR) corresponding to different behavioral state of preterm infants determined through video analysis. Video electroencephalogram (EEG) and electrocardiogram (ECG) data were collected from infants. Videos were reviewed visually for active sleep (AS), and quiet sleep (QS) states. HR was calculated from the ECG, and its variability (range) was analyzed using a 30-s window with a 2-s sliding interval. HR ranges were compared between AS and QS using a receiver operator characteristic (ROC) analysis. To investigate the cortical correlates of these states, EEG data were analyzed for spectral power in the delta frequency band (0.5 - 4 Hz). The dependence of EEG metrics on sleep state was examined using linear mixed-effects models, with sex and postmenstrual age (PMA) at study included as covariates. This study included 68 infants born between 23 and 36 weeks of gestational age. EEG recordings were obtained between 34.857-and 40.714-weeks PMA. On average, infants spent 38% of the time in QS and 62% in AS. ROC analysis distinguished heart rate ranges between AS (median: 27.597 [minimum: 12.385, maximum: 106.705] beats per minute [bpm]) and QS (13.943 [5.261, 36.284] bpm), with an area under the curve of 0.88 at a threshold of 18 bpm. The reliability of the results was assessed by dividing the cohort into two groups and repeating the same analysis, which produced findings consistent with those obtained from the original cohort. Delta power was significantly higher during QS compared to AS (P < 0.05), independent of PMA at the time of study and sex. Heart rate range demonstrates distinct variability patterns between QS and AS. Validation of these findings in younger preterm infants is currently underway.

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Journal
Scientific Reports
Published
2026-01-28
DOI
https://doi.org/10.1038/s41598-025-31873-7
Primary Topic
Neonatal and fetal brain pathology
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article
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article

Identifying heart rate characteristics of sleep states of preterm infants using video analysis

Venkata C. Chirumamilla, Sarah B. Mulkey, Robin Baker, R. B. Govindan et al.
Scientific Reports
Neonatal and fetal brain pathology
article

Identifying heart rate characteristics of sleep states of preterm infants using video analysis

Venkata C. Chirumamilla, Sarah B. Mulkey, Robin Baker, R. B. Govindan, Adre du Plessis
article en

Abstract

Objective is to identify changes in heart rate (HR) corresponding to different behavioral state of preterm infants determined through video analysis. Video electroencephalogram (EEG) and electrocardiogram (ECG) data were collected from infants. Videos were reviewed visually for active sleep (AS), and quiet sleep (QS) states. HR was calculated from the ECG, and its variability (range) was analyzed using a 30-s window with a 2-s sliding interval. HR ranges were compared between AS and QS using a receiver operator characteristic (ROC) analysis. To investigate the cortical correlates of these states, EEG data were analyzed for spectral power in the delta frequency band (0.5 - 4 Hz). The dependence of EEG metrics on sleep state was examined using linear mixed-effects models, with sex and postmenstrual age (PMA) at study included as covariates. This study included 68 infants born between 23 and 36 weeks of gestational age. EEG recordings were obtained between 34.857-and 40.714-weeks PMA. On average, infants spent 38% of the time in QS and 62% in AS. ROC analysis distinguished heart rate ranges between AS (median: 27.597 [minimum: 12.385, maximum: 106.705] beats per minute [bpm]) and QS (13.943 [5.261, 36.284] bpm), with an area under the curve of 0.88 at a threshold of 18 bpm. The reliability of the results was assessed by dividing the cohort into two groups and repeating the same analysis, which produced findings consistent with those obtained from the original cohort. Delta power was significantly higher during QS compared to AS (P < 0.05), independent of PMA at the time of study and sex. Heart rate range demonstrates distinct variability patterns between QS and AS. Validation of these findings in younger preterm infants is currently underway.

Scientific ReportsVol. 16(1)
Children's National (US), George Washington University (US), Fairfax Neonatal Associates (US)
Good health and well-being
Openalex Percentile: Top 75%
Neonatal and fetal brain pathology
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Identifying heart rate characteristics of sleep states of preterm infants using video analysis — Venkata C. Chirumamilla, Sarah B. Mulkey, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS