Developing robust recurrence plot analysis techniques for investigating infant respiratory patterns.
Recurrence plot analysis is a useful non-linear analysis tool. There are still no well formalised procedures for carrying out this analysis on measured physiological data, and systemising analysis is often difficult. In this paper, the recurrence based embedding is compared to radius based embedding by studying a logistic attractor and measured breathing data collected from sleeping human infants. Recurrence based embedding appears to be a more robust method of carrying out a recurrence analysis when attractor size is likely to be different between datasets. In the infant breathing data, the radius measure calculated at a fixed recurrence, scaled by average respiratory period, allows the accurate discrimination of active sleep from quiet sleep states (AUC=0.975, Sn=098, Sp=0.94).
Terrill
Philip I
PI
School of Medicine, University of Queensland, St. Lucia, Qld. 4067 Australia. p.terrill@uq.edu.au
Wilson
Stephen
S
Suresh
Sadasivam
S
Cooper
David M
DM
D000465:Algorithms; D001185:Artificial Intelligence; D001683:Biological Clocks / Q000502:physiology; D003196:Computer Graphics; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008954:Models, Biological; D009991:Oscillometry / Q000379:methods*; D017286:Polysomnography / Q000379:methods*; D015203:Reproducibility of Results; D012129:Respiratory Function Tests / Q000379:methods*; D012680:Sensitivity and Specificity; D012894:Sleep Stages / Q000502:physiology*; D014584:User-Computer Interface