Sounding out heart problems automatically

July 11, 2008

Sounding the chest with a cold stethoscope is probably one of the most commonly used diagnostics in the medical room after peering down the back of the throat while the patient says, "Aaaah". But, research published in the inaugural issue of the International Journal of Medical Engineering and Informatics looks set to add an information-age approach to diagnosing heart problems. The technique could circumvent the problem of the failing stethoscope skills of medical graduates and reduce errors of judgment

Listening closely to the sound of the beating heart can reveal a lot about its health. Healthcare workers can identify murmurs, palpitations, and other anomalies quickly and then carry out in-depth tests as appropriate. Now, Samit Ari and Goutam Saha of the Indian Institute of Technology in Kharagpur have developed an analytical method that can automatically classify a much wider range of heart sounds than is possible even by the most skilled stethoscope-wielding physician.

Their approach is based on a mathematical analysis of the sound waves produced by the beating heart known as Empirical Mode Decomposition (EMD). This method breaks down the sounds of each heart cycle into its component parts. This allows them to isolate the sound of interest from background noise, such as the movements of the patient, internal body gurgles, and ambient sounds.

The analysis thus produces a signal based on twenty five different sound qualities and variables, which can then be fed into a computer-based classification system. The classification uses an Artificial Neural Network (ANN) and a Grow and Learn (GAL) network. These are trained with standardized sounds associated with a specific diagnosis.

The team then tested the trained networks using more than 100 different recordings of normal heart sounds, sounds from hearts with a variety of valve problems, and different background noises. They found that the EMD system performs more effectively in all cases than conventional electronic, wavelet-based, approaches to heart sound classification.

A disturbing percentage of medical graduates cannot properly diagnose heart conditions using a stethoscope, the researchers explain, and the poor sensitivity of the human ear to low frequency heart sounds makes this task even more difficult. The automatic classification of heart sounds based on Ari and Saha's technique could remedy these failings.

Source: Inderscience Publishers

Explore further: Music therapy helps preemie babies thrive

Related Stories

'Business diet' a bad deal for the heart

August 19, 2016

(HealthDay)—The typical "social business diet"—heavy on red meats, sweet drinks, processed snacks and booze—takes a toll on the heart, a new study finds.

Will our black hole eat the Milky Way?

August 16, 2016

Want to hear something cool? There's a black hole at the center of the Milky Way. And not just any black hole, it's a supermassive black hole with more than 4.1 million times the mass of the Sun.

Recommended for you

How the finch changes its tune

August 3, 2015

Like top musicians, songbirds train from a young age to weed out errors and trim variability from their songs, ultimately becoming consistent and reliable performers. But as with human musicians, even the best are not machines. ...

Cow embryos reveal new type of chromosome chimera

May 27, 2016

I've often wondered what happens between the time an egg is fertilized and the time the ball of cells that it becomes nestles into the uterine lining. It's a period that we know very little about, a black box of developmental ...

Shaving time to test antidotes for nerve agents

February 29, 2016

Imagine you wanted to know how much energy it took to bike up a mountain, but couldn't finish the ride to the peak yourself. So, to get the total energy required, you and a team of friends strap energy meters to your bikes ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.