Technical section
Machine classification of infant sleep state using cardiorespiratory measures

https://doi.org/10.1016/0013-4694(87)90126-XGet rights and content

Abstract

We examined the potential to classify sleep and waking states over the first 6 months of life in normal infants using only cardiac and respiratory measures. Twelve hour all-night polygraph recordings which included EEG, eye movement, whole body movement, facial muscle electromyographic, cardiac, and respiratory activity from 25 normal infants were collected at 1 week, and at 1, 2, 3, 4, and 6 months of age. Each minute of these recordings was classified into quiet sleep, waking, or rapid eye movement sleep by trained observers using EEG and somatic criteria. Respiratory rate and variability, heart rate and variability, and cardiac interbeat interval variation at respiratory and lower frequencies from 12 of the 25 infants were used as measures in discriminant analyses of sleep state for test on the 13 remaining infants. Using all 7 cardiac and respiratory measures, sleep states were classified with an accuracy approximating that attained by trained observers who had available all polygraph tracings (84.8% overall correct classification). Using only cardiac measures, the accuracy of classification decreased slightly, with an overall correct classification of 82.0%. Using only respiratory measures, the accuracy of classification diminished further, with an overall correct classification of 80.0%. Cardiac and respiratory measures provide quantifiable indications of sleep and waking states over the first 6 months of life in normal infants.

References (18)

There are more references available in the full text version of this article.

Cited by (92)

  • Audio- and video-based estimation of the sleep stages of newborns in Neonatal Intensive Care Unit

    2019, Biomedical Signal Processing and Control
    Citation Excerpt :

    The automatic sleep stage classification has been much less addressed in newborns, full-term or preterm, than in adults. However, several modalities were studied including EEG [11–16], cardiorespiratory signals [17] and facial expressions [18]. Though, these methods offer a sleep stage classification more or less specific regarding the PMA.

  • Disorders of Breathing During Sleep

    2019, Kendig's Disorders of the Respiratory Tract in Children
  • Newborn electroencephalographic correlates of maternal prenatal depressive symptoms

    2018, Journal of Developmental Origins of Health and Disease
View all citing articles on Scopus

Supported by PHS/NICHD N01-HD-3-2830. Data collection efforts were previously supported by HD-4-2810 and HD-2-2777.

View full text