Melcer Tomasz, Danielewska Monika E, Iskander D Robert
Department of Biomedical Engineering, Wroclaw University of Technology, Wroclaw, Poland.
PLoS One. 2015 Apr 23;10(4):e0124721. doi: 10.1371/journal.pone.0124721. eCollection 2015.
To 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.
Retrospective 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.
A 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%.
It 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.
开发一种可靠且强大的方法，用于从无创获取的角膜脉搏信号中检测眼重搏波，而无需了解眼血脉搏信号和心脏电活动信号中存在的潜在心肺信息。
使用了一项关于青光眼和年龄相关性角膜搏动变化的研究[《公共科学图书馆·综合》9(7)，(2014):e102814]中的回顾性数据，该研究涉及261名受试者。考虑角膜脉搏信号导数的连续小波表示，选择复高斯导数函数作为母小波。灰度共生矩阵已应用于连续小波变换的图像（热图），以产生一组参数，可用于基于条件推理树和随机森林模型设计眼重搏波检测方案。该检测方案首先在类似于重搏性和非重搏性眼脉搏的合成信号上进行测试，然后应用于所有261个真实记录。
基于角膜脉搏信号连续小波变换的单个特征的检测方案导致检测率较低。基于纹理度量（均匀性、相关性、能量和对比度）的一组特征的聚合导致高检测率，达到93%。
无需获取与心脏活动相关的额外信号，就能够从角膜搏动信号中可靠地检测到重搏性眼脉搏，而这是以前的技术水平。所提出的方案可应用于与眼动力学相关的其他非平稳生物医学信号。
