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USF Tampa Graduate Theses and Dissertations

2016

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Full-Text Articles in Physical Sciences and Mathematics

Automatic Pain Assessment From Infants’ Crying Sounds, Chih-Yun Pai Nov 2016

Automatic Pain Assessment From Infants’ Crying Sounds, Chih-Yun Pai

USF Tampa Graduate Theses and Dissertations

Crying is infants utilize to express their emotional state. It provides the parents and the nurses a criterion to understand infants’ physiology state. Many researchers have analyzed infants’ crying sounds to diagnose specific diseases or define the reasons for crying. This thesis presents an automatic crying level assessment system to classify infants’ crying sounds that have been recorded under realistic conditions in the Neonatal Intensive Care Unit (NICU) as whimpering or vigorous crying. To analyze the crying signal, Welch’s method and Linear Predictive Coding (LPC) are used to extract spectral features; the average and the standard deviation of the frequency …


Time Dependent Kernel Density Estimation: A New Parameter Estimation Algorithm, Applications In Time Series Classification And Clustering, Xing Wang May 2016

Time Dependent Kernel Density Estimation: A New Parameter Estimation Algorithm, Applications In Time Series Classification And Clustering, Xing Wang

USF Tampa Graduate Theses and Dissertations

The Time Dependent Kernel Density Estimation (TDKDE) developed by Harvey & Oryshchenko (2012) is a kernel density estimation adjusted by the Exponentially Weighted Moving Average (EWMA) weighting scheme. The Maximum Likelihood Estimation (MLE) procedure for estimating the parameters proposed by Harvey & Oryshchenko (2012) is easy to apply but has two inherent problems. In this study, we evaluate the performances of the probability density estimation in terms of the uniformity of Probability Integral Transforms (PITs) on various kernel functions combined with different preset numbers. Furthermore, we develop a new estimation algorithm which can be conducted using Artificial Neural Networks to …