Superposed epoch analysis of physiological fluctuations: possible space weather connections

Abstract

There is a strong connection between space weather and fluctuations in technological systems. Some studies also suggest a statistical connection between space weather and subsequent fluctuations in the physiology of living creatures. This connection, however, has remained controversial and difficult to demonstrate. Here we present support for a response of human physiology to forcing from the explosive onset of the largest of space weather events-space storms. We consider a case study with over 16 years of high temporal resolution measurements of human blood pressure (systolic, diastolic) and heart rate variability to search for associations with space weather. We find no statistically significant change in human blood pressure but a statistically significant drop in heart rate during the main phase of space storms. Our empirical findings shed light on how human physiology may respond to exogenous space weather forcing.

About-Weekly Pattern in the Dynamic Complexity of a Healthy Subject’s Cellular Immune Activity: A Biopsychosocial Analysis

“…To identify dominant frequencies and repeating patterns in the DC time series of neopterin, autocorrelation functions (ACF) and spectral analysis were applied after first-order differentiation ( 19 ). To evaluate the impact of discrete events on the neopterin complexity time series, a superposed epoch analysis (SEA) ( 20 , 21 ) was computed. To do so, vectors of data points around each discrete event were combined into a composite matrix, with the width of the matrix indicating the number of data points around the event and the length of the matrix the number of events.…”

Correlative Connections between Chronostructures of Water-Mineral Homeostasis and Weather Indices in Cardiovascular Pathology

“…

Chronoperiodical systems and dynamics of biological rhythms evolved in the process of evolution under the influence of environmental factors [1][2][3][4]. Circadian structure had been considered

…”

Impact of Extreme Weather Disasters on China’s Barley Industry under the Background of Trade Friction—Based on the Partial Equilibrium Model

“…At the same time, it is able to eliminate noise due to extraneous variables [ 39 ]. SEA suppresses noise by averaging the impact of events, which effectively amplifies the relative magnitude of the response signal and extracts the impact of a specific event from the accompanying noise [ 40 ]. The assessment using SEA begins by creating a composite matrix, which is a fixed window of continuous observations plotted over a continuous time series before, during, and after the “event”.…”