Asymmetric detrended fluctuation analysis in neonatal stress

Neonatal heart rate variability: a contemporary scoping review of analysis methods and clinical applications

BACKGROUND

Neonatal heart rate variability (HRV) is widely used as a research tool. However, HRV calculation methods are highly variable making it difficult for comparisons between studies.

OBJECTIVES

To describe the different types of investigations where neonatal HRV was used, study characteristics, and types of analyses performed.

ELIGIBILITY CRITERIA

Human neonates ≤1 month of corrected age.

SOURCES OF EVIDENCE

A protocol and search strategy of the literature was developed in collaboration with the McGill University Health Center's librarians and articles were obtained from searches in the Biosis, Cochrane, Embase, Medline and Web of Science databases published between 1 January 2000 and 1 July 2020.

CHARTING METHODS

A single reviewer screened for eligibility and data were extracted from the included articles. Information collected included the study characteristics and population, type of HRV analysis used (time domain, frequency domain, non-linear, heart rate characteristics (HRC) parameters) and clinical applications (physiological and pathological conditions, responses to various stimuli and outcome prediction).

RESULTS

Of the 286 articles included, 171 (60%) were small single centre studies (sample size <50) performed on term infants (n=136). There were 138 different types of investigations reported: physiological investigations (n=162), responses to various stimuli (n=136), pathological conditions (n=109) and outcome predictor (n=30). Frequency domain analyses were used in 210 articles (73%), followed by time domain (n=139), non-linear methods (n=74) or HRC analyses (n=25). Additionally, over 60 different measures of HRV were reported; in the frequency domain analyses alone there were 29 different ranges used for the low frequency band and 46 for the high frequency band.

CONCLUSIONS

Neonatal HRV has been used in diverse types of investigations with significant lack of consistency in analysis methods applied. Specific guidelines for HRV analyses in neonates are needed to allow for comparisons between studies.

Research on risk early warning algorithm for asymmetric samples in multifractal financial market

This paper takes 11-year 5-minute high-frequency trading data of the Shanghai and Shenzhen 300 Index (CSI300) as a research sample. First, it proposes a method to define the normal state and the state of attention of the financial market based on multi-fractal characteristics, and randomly owes it Sampling (RU), synthetic minority oversampling (SMOTE) and traditional support vector machine (SVM) are combined to propose an improved SVM model—RU-SMOTE-SVM model to predict extreme risks in China’s financial market, and compare Traditional SVM, SMOTE-SVM, RU-SMOTE-NN and RU-SMOTE-DT are compared. The empirical results show that the price fluctuations of China’s emerging financial markets have significant multi-fractal characteristics; the normal and concerned states defined based on the multi-fractal feature parameters are not only accurate, but also have obvious statistical test significance and clear practical significance; and traditional SVM and Compared with BP neural network (NN), RU-SMOTE-SVM is not only significantly higher in prediction accuracy, but also in terms of prediction stability. That is, RU-SMOTE-SVM can effectively solve the problems of other early warning models to solve the symmetrical sample problem.

Multi-lag tone-entropy in neonatal stress

Heart rate variability (HRV) has been analysed using linear and nonlinear methods. In the framework of a controlled neonatal stress model, we applied tone-entropy (T-E) analysis at multiple lags to understand the influence of external stressors on healthy term neonates. Forty term neonates were included in the study. HRV was analysed using multi-lag T-E at two resting and two stress phases (heel stimulation and a heel stick blood drawing phase). Higher mean entropy values and lower mean tone values when stressed showed a reduction in randomness with increased sympathetic and reduced parasympathetic activity. A ROC analysis was used to estimate the diagnostic performances of tone and entropy and combining both features. Comparing the resting and simulation phase separately, the performance of tone outperformed entropy, but combining the two in a quadratic linear regression model, neonates in resting as compared to stress phases could be distinguished with high accuracy. This raises the possibility that when applied across short time segments, multi-lag T-E becomes an additional tool for more objective assessment of neonatal stress.