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Cognitive Recognition of Heart Ailments Using Fuzzy Logic on ECG Samples

Kora, Padmavathi / Swaraja, K. / Meenakshi, K. / Kumari, Ch. Usha / Karuna, G.

Abstract The electrocardiogram (ECG) is a graphical representation of the electrical activity of the heart. Signal modelling is a powerful technique used in the automatic ECG signal analysis. To identify different pathologies, some classification are applied to ECG signal. The peaks and segments are called features, helps us to recognize the ECG segments. Calculation of the general health indicators like beat-per-minute (bpm), QRS width and the presence/absence of a segment are done. The standard rule-set is applied to the above features to recognize the type of heart ailment the patient is suffering from. The decision making is implemented by a multi-level system and fuzzy logic. This is the flow of events of the project.

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Cognitive Recognition of Heart Ailments Using Fuzzy Logic on ECG Samples

Kora, Padmavathi / Swaraja, K. / Meenakshi, K. / Kumari, Ch. Usha / Karuna, G.

Abstract The electrocardiogram (ECG) is a graphical representation of the electrical activity of the heart. Signal modelling is a powerful technique used in the automatic ECG signal analysis. To identify different pathologies, some classification are applied to ECG signal. The peaks and segments are called features, helps us to recognize the ECG segments. Calculation of the general health indicators like beat-per-minute (bpm), QRS width and the presence/absence of a segment are done. The standard rule-set is applied to the above features to recognize the type of heart ailment the patient is suffering from. The decision making is implemented by a multi-level system and fuzzy logic. This is the flow of events of the project.

Cognitive Recognition of Heart Ailments Using Fuzzy Logic on ECG Samples

Kora, Padmavathi / Swaraja, K. / Meenakshi, K. / Kumari, Ch. Usha / Karuna, G.

Abstract The electrocardiogram (ECG) is a graphical representation of the electrical activity of the heart. Signal modelling is a powerful technique used in the automatic ECG signal analysis. To identify different pathologies, some classification are applied to ECG signal. The peaks and segments are called features, helps us to recognize the ECG segments. Calculation of the general health indicators like beat-per-minute (bpm), QRS width and the presence/absence of a segment are done. The standard rule-set is applied to the above features to recognize the type of heart ailment the patient is suffering from. The decision making is implemented by a multi-level system and fuzzy logic. This is the flow of events of the project.

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Titel:

Cognitive Recognition of Heart Ailments Using Fuzzy Logic on ECG Samples

Beteiligte:

Kora, Padmavathi (Autor:in) / Swaraja, K. (Autor:in) / Meenakshi, K. (Autor:in) / Kumari, Ch. Usha (Autor:in) / Karuna, G. (Autor:in)

Erschienen in:

ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management ; 474-479

Erscheinungsdatum:

28.06.2019

Format / Umfang:

6 pages

ISBN:

978-981-13-8460-8 , 978-981-13-8461-5

DOI:

https://doi.org/10.1007/978-981-13-8461-5_53

Medientyp:

Aufsatz/Kapitel (Buch)

Format:

Elektronische Ressource

Sprache:

Englisch

Schlagwörter:

ECG (Electrocardiogram/Electrocardiograph) , Fuzzy logic , Health indicators , Arrhythmias , Rules set , Feature extraction Engineering , Quality Control, Reliability, Safety and Risk , Performance and Reliability , Circuits and Systems , Operations Research, Management Science

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