Python for segregated signal averaging of cardiac baroreflex response in humans

05:00 PM - 05:25 PM on July 16, 2016, Room CR6

Trevor Witter

Audience level:

novice

Watch:

https://www.youtube.com/watch?v=sRdTrqsPB0c

Description

The cardiovascular system is regulated through complex interactions between the central nervous system, the heart and systemic arteries. Quantifying the underlying interactions can provide detailed diagnostic information on an individual’s health. Python and libraries such as pandas, scipi, numpi and matplotlib provide the tools needed to process and quantify the relationship between recordings of multiple simultaneous cardiovascular signals.

Abstract

The cardiovascular system is regulated by a number of complex mechanisms ensuring that continuous blood flow is maintained to the vital organs. Without a stable, continuous supply of blood, organs, such as the brain, will cease to function. Quantifying the sensitivity of these mechanisms may provide better diagnostic information than current clinical measurements. The baroreflex is one such system, which works to maintain blood pressure within an optimal range. Unlike a simple static blood pressure measurement, quantification of the baroreflex indicates how well a person can react to sudden changes in blood pressure. However, the quantification of the baroreflex is much more complex than simply measuring a person’s blood pressure with a sphygmomanometer. Modern laboratory equipment allows for the measurement of continuous blood pressure, heart rate, and nerve activity. Python, along with the pandas, scipi, numpy, and matplotlib libraries provides the ability to effortlessly process these signals and quantify how they relate to one another. The resulting information from this signal processing may provide greater detailed and reliable diagnostic information if implemented in a clinical setting.