Limits...
Improved Bat algorithm for the detection of myocardial infarction.

Kora P, Kalva SR - Springerplus (2015)

Bottom Line: The first step in the detection of MI is Preprocessing of ECGs which removes noise by using filters.Feature extraction is the next key process in detecting the changes in the ECG signals.It has been observed that the performance of the classifier is improved with the help of the optimized features.

View Article: PubMed Central - PubMed

Affiliation: Department of ECE, GRIET, Bachupally, 500090 Hyderabad, India.

ABSTRACT
The medical practitioners study the electrical activity of the human heart in order to detect heart diseases from the electrocardiogram (ECG) of the heart patients. A myocardial infarction (MI) or heart attack is a heart disease, that occurs when there is a block (blood clot) in the pathway of one or more coronary blood vessels (arteries) that supply blood to the heart muscle. The abnormalities in the heart can be identified by the changes in the ECG signal. The first step in the detection of MI is Preprocessing of ECGs which removes noise by using filters. Feature extraction is the next key process in detecting the changes in the ECG signals. This paper presents a method for extracting key features from each cardiac beat using Improved Bat algorithm. Using this algorithm best features are extracted, then these best (reduced) features are applied to the input of the neural network classifier. It has been observed that the performance of the classifier is improved with the help of the optimized features.

No MeSH data available.


Related in: MedlinePlus

Bat algorithm flowchart
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4631839&req=5

Fig8: Bat algorithm flowchart

Mentions: The original BA has been demonstrated in the following algorithm and the flowchart is as shown in Fig. 8. In this algorithm, the bat behavior has been analyzed based on the its fitness function. It consists of the following points:


Improved Bat algorithm for the detection of myocardial infarction.

Kora P, Kalva SR - Springerplus (2015)

Bat algorithm flowchart
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4631839&req=5

Fig8: Bat algorithm flowchart
Mentions: The original BA has been demonstrated in the following algorithm and the flowchart is as shown in Fig. 8. In this algorithm, the bat behavior has been analyzed based on the its fitness function. It consists of the following points:

Bottom Line: The first step in the detection of MI is Preprocessing of ECGs which removes noise by using filters.Feature extraction is the next key process in detecting the changes in the ECG signals.It has been observed that the performance of the classifier is improved with the help of the optimized features.

View Article: PubMed Central - PubMed

Affiliation: Department of ECE, GRIET, Bachupally, 500090 Hyderabad, India.

ABSTRACT
The medical practitioners study the electrical activity of the human heart in order to detect heart diseases from the electrocardiogram (ECG) of the heart patients. A myocardial infarction (MI) or heart attack is a heart disease, that occurs when there is a block (blood clot) in the pathway of one or more coronary blood vessels (arteries) that supply blood to the heart muscle. The abnormalities in the heart can be identified by the changes in the ECG signal. The first step in the detection of MI is Preprocessing of ECGs which removes noise by using filters. Feature extraction is the next key process in detecting the changes in the ECG signals. This paper presents a method for extracting key features from each cardiac beat using Improved Bat algorithm. Using this algorithm best features are extracted, then these best (reduced) features are applied to the input of the neural network classifier. It has been observed that the performance of the classifier is improved with the help of the optimized features.

No MeSH data available.


Related in: MedlinePlus