Abstract
PurposeTo develop a reliable and powerful method for detecting the ocular dicrotism from non-invasively acquired signals of corneal pulse without the knowledge of the underlying cardiopulmonary information present in signals of ocular blood pulse and the electrical heart activity.MethodsRetrospective data from a study on glaucomatous and age-related changes in corneal pulsation [PLOS ONE 9(7),(2014):e102814] involving 261 subjects was used. Continuous wavelet representation of the signal derivative of the corneal pulse was considered with a complex Gaussian derivative function chosen as mother wavelet. Gray-level Co-occurrence Matrix has been applied to the image (heat-maps) of CWT to yield a set of parameters that can be used to devise the ocular dicrotic pulse detection schemes based on the Conditional Inference Tree and the Random Forest models. The detection scheme was first tested on synthetic signals resembling those of a dicrotic and a non-dicrotic ocular pulse before being used on all 261 real recordings.ResultsA detection scheme based on a single feature of the Continuous Wavelet Transform of the corneal pulse signal resulted in a low detection rate. Conglomeration of a set of features based on measures of texture (homogeneity, correlation, energy, and contrast) resulted in a high detection rate reaching 93%.ConclusionIt is possible to reliably detect a dicrotic ocular pulse from the signals of corneal pulsation without the need of acquiring additional signals related to heart activity, which was the previous state-of-the-art. The proposed scheme can be applied to other non-stationary biomedical signals related to ocular dynamics.
Highlights
Ocular dicrotism, manifested as a double-peak shaped feature in corneal pulsation [1,2,3], is a newly observed phenomenon [4, 5]
Gray-level Co-occurrence Matrix has been applied to the image of Continuous Wavelet Transform (CWT) to yield a set of parameters that can be used to devise the ocular dicrotic pulse detection schemes based on the Conditional Inference Tree and the Random Forest models
A detection scheme based on a single feature of the Continuous Wavelet Transform of the corneal pulse signal resulted in a low detection rate
Summary
Ocular dicrotism, manifested as a double-peak shaped feature in corneal pulsation [1,2,3], is a newly observed phenomenon [4, 5]. Using an innovative noninvasive and noncontact ultrasonic technique [6, 7], ocular dicrotic pulse (ODP) has been observed in a substantial proportion of older subjects (about 70%) but was not evident in the population of younger participants of the study ( 35 y.o.) [4]. It was found that the ODP incidence increases with age and that it increases more rapidly in glaucoma patients than in healthy subjects. Both studies concluded that ODP is the natural sign of aging and may have hemodynamic etiology. Automatizing the ODP detection process is of particular importance in large longitudinal studies, involving hundreds of subjects and multiple measurements of the corneal pulse (CP) signal [5]
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