Statistical analysis of ECG signals for arrhythmia detection

G. S. Nayak; C. Puttamadappa; A. Surekha Kamatha

doi:10.1007/978-3-540-69139-6-65

Statistical analysis of ECG signals for arrhythmia detection

G. S. Nayak, C. Puttamadappa, A. Surekha Kamatha

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

Electrocardiogram is one important physiological signal, which is used in assessing cardiac health. The extraction of features used for identification of the state of ECG is discussed in this paper. Using MAT LAB programs/tools, different statistical features are extracted from both normal and arrhythmia spectra. These features include differentiation and count of spikes for different thresholds, mean, standard deviation, energy, residuals on curve fitting, LPC coefficients etc. The values of the feature vector reveal information regarding cardiac health state. These parameters have been analyzed for discrimination between normal and arrhythmia conditions. For analysis a specific data set has been considered.

Original language	English
Title of host publication	4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008
Pages	251-253
Number of pages	3
Volume	21 IFMBE
Edition	1
DOIs	https://doi.org/10.1007/978-3-540-69139-6-65
Publication status	Published - 2008
Event	4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008 - Kuala Lumpur, Malaysia Duration: 25-06-2008 → 28-06-2008

Conference

Conference	4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008
Country/Territory	Malaysia
City	Kuala Lumpur
Period	25-06-08 → 28-06-08

All Science Journal Classification (ASJC) codes

Biomedical Engineering
Bioengineering

Access to Document

10.1007/978-3-540-69139-6-65

Cite this

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title = "Statistical analysis of ECG signals for arrhythmia detection",

abstract = "Electrocardiogram is one important physiological signal, which is used in assessing cardiac health. The extraction of features used for identification of the state of ECG is discussed in this paper. Using MAT LAB programs/tools, different statistical features are extracted from both normal and arrhythmia spectra. These features include differentiation and count of spikes for different thresholds, mean, standard deviation, energy, residuals on curve fitting, LPC coefficients etc. The values of the feature vector reveal information regarding cardiac health state. These parameters have been analyzed for discrimination between normal and arrhythmia conditions. For analysis a specific data set has been considered.",

author = "Nayak, {G. S.} and C. Puttamadappa and Kamatha, {A. Surekha}",

year = "2008",

doi = "10.1007/978-3-540-69139-6-65",

language = "English",

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volume = "21 IFMBE",

pages = "251--253",

booktitle = "4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008",

edition = "1",

note = "4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008 ; Conference date: 25-06-2008 Through 28-06-2008",

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Nayak, GS, Puttamadappa, C & Kamatha, AS 2008, Statistical analysis of ECG signals for arrhythmia detection. in 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008. 1 edn, vol. 21 IFMBE, pp. 251-253, 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008, Kuala Lumpur, Malaysia, 25-06-08. https://doi.org/10.1007/978-3-540-69139-6-65

TY - GEN

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AU - Nayak, G. S.

AU - Puttamadappa, C.

AU - Kamatha, A. Surekha

PY - 2008

Y1 - 2008

N2 - Electrocardiogram is one important physiological signal, which is used in assessing cardiac health. The extraction of features used for identification of the state of ECG is discussed in this paper. Using MAT LAB programs/tools, different statistical features are extracted from both normal and arrhythmia spectra. These features include differentiation and count of spikes for different thresholds, mean, standard deviation, energy, residuals on curve fitting, LPC coefficients etc. The values of the feature vector reveal information regarding cardiac health state. These parameters have been analyzed for discrimination between normal and arrhythmia conditions. For analysis a specific data set has been considered.

AB - Electrocardiogram is one important physiological signal, which is used in assessing cardiac health. The extraction of features used for identification of the state of ECG is discussed in this paper. Using MAT LAB programs/tools, different statistical features are extracted from both normal and arrhythmia spectra. These features include differentiation and count of spikes for different thresholds, mean, standard deviation, energy, residuals on curve fitting, LPC coefficients etc. The values of the feature vector reveal information regarding cardiac health state. These parameters have been analyzed for discrimination between normal and arrhythmia conditions. For analysis a specific data set has been considered.

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U2 - 10.1007/978-3-540-69139-6-65

DO - 10.1007/978-3-540-69139-6-65

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SN - 9783540691389

VL - 21 IFMBE

SP - 251

EP - 253

BT - 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008

T2 - 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008

Y2 - 25 June 2008 through 28 June 2008

ER -

Statistical analysis of ECG signals for arrhythmia detection

Abstract

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