Featured Research

from universities, journals, and other organizations

Seeing the forest and the trees reveals heart problems

Date:
July 27, 2010
Source:
Inderscience Publishers
Summary:
A statistical analysis of publicly available heart rate data using three classification tools -- Random Forests, Logistic Model Tree and Neural Network -- could lead to a rapid and precise way to diagnose heart problems, according to new research.

A statistical analysis of publicly available heart rate data using three classification tools -- Random Forests, Logistic Model Tree and Neural Network -- could lead to a rapid and precise way to diagnose heart problems, according to research in the International Journal of Electronic Healthcare.

Related Articles


"Heart rate and Heart Rate Variability (HRV) are important measures that reflect the state of the cardiovascular system. HRV analysis has gained prominence in the field of cardiology for detecting cardiac abnormalities," explains C. Vimal and colleagues at the PSG College of Technology, in Coimbatore, India.

Vimal and his team in the Department of Biomedical Engineering have worked with V. Mahesh in the Department of Information Technology to investigate whether or not it might be possible to more quickly detect heart problems and possible indicators of imminent heart failure more quickly than with current techniques.

"Automated detection and classification of cardiac diseases can aid the physician in speedy diagnosis of cardiac abnormalities," the team explains, "The starting point of any study is usually an Electrocardiogram (ECG), which records the heart's electrical activity." The ECG is a basic but widely used non-invasive diagnostic tool.

Unfortunately, the ECG suffers from a major drawback, given that the heart's behavior can be inconsistent and symptoms of disease may show up at any time. The heart rate variability signal monitored over a long period is more time-consuming but can be more productive in detecting abnormalities.

"The analysis of HRV data yields various features that have proved to be a better aid in classification," explains the team. Short-term variability in heart rate might be looked at or low and high frequency electrical changes. Indeed, the low frequency/high frequency ratio has been found to be the most influential HRV determinant of death and could help to identify patients at risk, the team adds.

The team sourced heart data from various heart disease databases on the Physionet website, a site dedicated to medical data of various diseases and their study, and processed the signals using three different approaches: Random Forests, Logistic Model Tree and Multilayer Perceptron Neural Network -- to validate the diagnostic conclusions. The team was able to obtain a classification accuracy of 98.17%. "The validated system can assist physicians in the classification of heart diseases," the researchers say, " Future work will be aimed at studying the performance of the system using real-time patient data from hospitals to further validate the observations."


Story Source:

The above story is based on materials provided by Inderscience Publishers. Note: Materials may be edited for content and length.


Journal Reference:

  1. Mahesh et al. Cardiac disease classification using heart rate signals. International Journal of Electronic Healthcare, 2010; 5 (3): 211 DOI: 10.1504/IJEH.2010.034173

Cite This Page:

Inderscience Publishers. "Seeing the forest and the trees reveals heart problems." ScienceDaily. ScienceDaily, 27 July 2010. <www.sciencedaily.com/releases/2010/07/100726094747.htm>.
Inderscience Publishers. (2010, July 27). Seeing the forest and the trees reveals heart problems. ScienceDaily. Retrieved March 2, 2015 from www.sciencedaily.com/releases/2010/07/100726094747.htm
Inderscience Publishers. "Seeing the forest and the trees reveals heart problems." ScienceDaily. www.sciencedaily.com/releases/2010/07/100726094747.htm (accessed March 2, 2015).

Share This


More From ScienceDaily



More Health & Medicine News

Monday, March 2, 2015

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

The Best Ways To Celebrate National Nutrition Month

The Best Ways To Celebrate National Nutrition Month

Buzz60 (Mar. 2, 2015) Just when your New Year&apos;s Resolution is losing steam, March comes with fresh inspiration. TC Newman (@PurpleTCNewman) has some tips to incorporate into your lifestyle during National Nutrition Month. Video provided by Buzz60
Powered by NewsLook.com
WHO: 1.1 Billion At Risk Of Hearing Loss, Will They Listen?

WHO: 1.1 Billion At Risk Of Hearing Loss, Will They Listen?

Newsy (Mar. 2, 2015) According to the World Health Organization, 1.1 billion young people are at risk of hearing loss. Can this staggering number change things? Video provided by Newsy
Powered by NewsLook.com
Rehab Robot Helps Restore Damaged Muscles and Nerves

Rehab Robot Helps Restore Damaged Muscles and Nerves

Reuters - Innovations Video Online (Mar. 1, 2015) A rehabilitation robot prototype to help restore deteriorated nerves and muscles using electromyography and computer games. Ben Gruber reports. Video provided by Reuters
Powered by NewsLook.com
How Facebook Use Can Lead To Depression

How Facebook Use Can Lead To Depression

Newsy (Mar. 1, 2015) Margaret Duffy of the University of Missouri talks about her study on the social network and the envy and depression that Facebook use can cause. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:

Strange & Offbeat Stories


Health & Medicine

Mind & Brain

Living & Well

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins