event thumbnail image
Optimization and inference in machine learning and physics Workshop

Leave-one-out prediction error as a diagnostic tool

author: Sebino Stramaglia, University of Bari

Description

We consider here predictability of Systolic Blood Pressure (SAP) time series under paced respiration (Akselrod et al 1985), and show that a suitable index separates healthy subjects from Chronic Heart Failure (CHF) patients. Systolic blood pressure (SAP) is the maximal pressure within the cardiovascular system as the heart pumps blood into the arteries. Paced respiration (breathing is synchronized with some external signal) is a well-established tool for relaxation and for the treatment of chronic pain and insomnia, dental and facial pain, etc. (Freedman and Woodward 1992). Entrainment between heart and respiration rate (cardiorespiratory synchronization) has been detected in subjects undergoing paced respiration (Pomortsev et al 1998). Paced breathing can prevent vasovagal syncope during head-up tilt testing; in healthy subjects under paced respiration the synchronization between the main processes governing cardiovascular system is stronger than the synchronization in the case of spontaneous respiration (Prokhorov et al 2003). However, a number of important questions remain open about paced breathing, including the dependence on the frequency of respiration and whether it affects the autonomic balance.

You might be experiencing some problems with Your Video player.

Lecture rating

People found this lecture:
Worth seeing
because it is:
 Valuable and informative
Well presented
Easily understandable
Acceptably recorded
You need to login to cast your vote.

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment: