Sleep-wake identification in infants: heart rate variability compared to actigraphy

Heart rate variability and actigraphy offer alternative techniques for sleep-wake identification compared to manual sleep scoring from a polysomnograph. The advantages include high accuracy, simplicity of use, and low intrusiveness. These advantages are valuable for determining sleep-wake states in such highly sensitive groups as infants. A learning vector quantization neural network was tested as a predictor. The accuracy of the neural network was compared to "gold standard" hand-scored polysomnographs. The prediction results are in agreement with other studies, thus validating the suggested methodology.

[1]  V. L. Schechtman,et al.  Development of Heart Rate Dynamics during Sleep-Waking States in Normal Infants , 1993, Pediatric Research.

[2]  P. C. Richardson,et al.  Detection of cyclic sleep phenomena using instantaneous heart rate. , 1976, Electroencephalography and clinical neurophysiology.

[3]  D O Walter,et al.  Cardiac waveform alterations during sleep in the infant. , 1976, Psychophysiology.

[4]  D. J. Mullaney,et al.  Automatic sleep/wake identification from wrist activity. , 1992, Sleep.

[5]  H. Stanley,et al.  Characterization of sleep stages by correlations in the magnitude and sign of heartbeat increments. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

[6]  P. C. Richardson,et al.  Computer sleep stage classification using heart rate data. , 1973, Electroencephalography and clinical neurophysiology.

[7]  G. Lister,et al.  Multivariable cardiorespiratory monitoring at home: collaborative home infant monitoring evaluation (CHIME) , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  X Xu,et al.  Automatic detection of artifacts in heart period data. , 2001, Journal of electrocardiology.

[9]  R. Sack,et al.  A comparison of sleep detection by wrist actigraphy, behavioral response, and polysomnography. , 1997, Sleep.

[10]  Stephanie Schuckers,et al.  Activity-based sleep-wake identification in infants , 2002, Computers in Cardiology.

[11]  M R Neuman,et al.  Cardiopulmonary monitoring at home: the CHIME monitor. , 2001, Physiological measurement.

[12]  P Lavie,et al.  Actigraphic home-monitoring sleep-disturbed and control infants and young children: a new method for pediatric assessment of sleep-wake patterns. , 1991, Pediatrics.

[13]  R. Harper,et al.  Machine classification of infant sleep state using cardiorespiratory measures. , 1987, Electroencephalography and clinical neurophysiology.

[14]  A. Sadeh,et al.  Activity-based sleep-wake identification: an empirical test of methodological issues. , 1994, Sleep.

[15]  Mingui Sun,et al.  Characterization of heart rate dynamics in infants as a probe for neural state and age , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[16]  A. Sadeh,et al.  Activity-based assessment of sleep-wake patterns during the 1st year of life , 1995 .

[17]  Theofanis Sapatinas,et al.  Wavelet packet modelling of infant sleep state using heart rate data , 2001 .

[18]  S. Ancoli-Israel,et al.  Use of wrist activity for monitoring sleep/wake in demented nursing-home patients. , 1997, Sleep.

[19]  Michael R. Neuman,et al.  Infant polysomnography: Reliability , 1997 .

[20]  C. Medigue,et al.  Discrete wavelet transform applied to heart rate variability analysis in iron-deficient anemic infants , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[21]  Edward Sazonov,et al.  Activity-based sleep-wake identification in infants. , 2004, Physiological measurement.