Pulse Rate Variability Analysis for Discrimination of Sleep-Apnea-Related Decreases in the Amplitude Fluctuations of Pulse Photoplethysmographic Signal in Children

• Published in: IEEE journal of biomedical and health informatics Vol. 18; no. 1; pp. 240 - 246
• Main Authors: Lazaro, Jesus, Gil, Eduardo, Vergara, Jose Maria, Laguna, Pablo
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Child; Child, Preschool; Children; decreases in the amplitude fluctuations of pulse photoplethysmographic signal (DAP); Detectors; Electrocardiography; Female; Heart Rate - physiology; Heart rate variability; Humans; Male; photoplethysmographic (PPG); Photoplethysmography - methods; Pulse oximeter; pulse rate variability (PRV); Signal Processing, Computer-Assisted; Sleep apnea; Sleep Apnea Syndromes - physiopathology; Sleep disorders; time frequency; Time-frequency analysis
• ISSN: 2168-2194; 2168-2208; 2168-2208
• DOI: 10.1109/JBHI.2013.2267096

A technique for ambulatory diagnosis of the obstructive sleep apnea syndrome (OSAS) in children based on pulse photoplethysmographic (PPG) signal is presented. Decreases in amplitude fluctuations of the PPG signal (DAP) events have been proposed as OSAS discriminator, since they are related to vasoconstriction associated to apnea. Heart rate variability (HRV) analysis during these DAP events has been proposed to discriminate between DAP events related or unrelated to an apneic event. The use of HRV requires electrocardiogram (ECG) as an additional recording, meaning a disadvantage that takes more relevance in sleep studies context where the number of sensors is tried to be minimized in order not to affect the physiological sleep. This study proposes the use of pulse rate variability (PRV) extracted from the PPG signal instead of HRV. Polysomnographic registers from 21 children (aged 4.47 ±2.04 years) were studied. The subject classification based on DAP events and PRV analysis obtained an accuracy of 86.67% which represents an improvement of 6.67% with respect to the HRV analysis. These results suggest that PRV can be used in apnea detectors based on DAP events, to discriminate apneic from nonapneic events avoiding the need for ECG recordings.