Classification of ECG signal-based cardiac abnormalities using fluctuation-based dispersion entropy and first-order statistics
The heart is one of the most important organs in the human body. The presence of abnormalities in the heart can be fatal for a person. One way to detect heart abnormalities is an Electrocardiogram (EKG) signal examination. To facilitate the detection of ECG signal abnormalities, an automatic classification method is needed. Therefore, in this study, a method for classifying ECG signals using FdispEn (Fluctuation-based dispersion Entropy) and first-order statistics is proposed. FdispEn measures the uncertainty in the signal and is expected to be able to distinguish the physiological state of the ECG signal time series. In this study FdispEn and statistical computing were used as feature extraction of the ECG signal and combined with the Support Vector Machine (SVM) for the classification process of Normal ECG, AFIB (Atrial Fibrilation), and CHF (Congestive Heart Failure). The method proposed in this study generates an accuracy of 91.5%. The system proposed in this study is expected to assist in the clinical diagnosis of abnormalities in the heart..
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2022 |
|---|---|
| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:14 |
|---|---|
| Enthalten in: |
Jurnal Infotel - 14(2022), 2, Seite 85-92 |
| Sprache: |
Indonesisch |
|---|
| Beteiligte Personen: |
Naufal Juhaidi Jafal [VerfasserIn] |
|---|
| Links: |
doi.org [kostenfrei] |
|---|
| Themen: |
Heart abnormalities, electrocardiogram, fluctuation-based dispersion entropy, statistics |
|---|
| doi: |
10.20895/infotel.v14i2.768 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
DOAJ027669327 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | DOAJ027669327 | ||
| 003 | DE-627 | ||
| 005 | 20230503143246.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 230226s2022 xx |||||o 00| ||ind c | ||
| 024 | 7 | |a 10.20895/infotel.v14i2.768 |2 doi | |
| 035 | |a (DE-627)DOAJ027669327 | ||
| 035 | |a (DE-599)DOAJc31a62bbc72344ea8ad6f9165747ee0f | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a ind | ||
| 050 | 0 | |a TK5101-6720 | |
| 100 | 0 | |a Naufal Juhaidi Jafal |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Classification of ECG signal-based cardiac abnormalities using fluctuation-based dispersion entropy and first-order statistics |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a The heart is one of the most important organs in the human body. The presence of abnormalities in the heart can be fatal for a person. One way to detect heart abnormalities is an Electrocardiogram (EKG) signal examination. To facilitate the detection of ECG signal abnormalities, an automatic classification method is needed. Therefore, in this study, a method for classifying ECG signals using FdispEn (Fluctuation-based dispersion Entropy) and first-order statistics is proposed. FdispEn measures the uncertainty in the signal and is expected to be able to distinguish the physiological state of the ECG signal time series. In this study FdispEn and statistical computing were used as feature extraction of the ECG signal and combined with the Support Vector Machine (SVM) for the classification process of Normal ECG, AFIB (Atrial Fibrilation), and CHF (Congestive Heart Failure). The method proposed in this study generates an accuracy of 91.5%. The system proposed in this study is expected to assist in the clinical diagnosis of abnormalities in the heart. | ||
| 650 | 4 | |a heart abnormalities, electrocardiogram, fluctuation-based dispersion entropy, statistics | |
| 653 | 0 | |a Telecommunication | |
| 700 | 0 | |a Yuli Sun Hariyani |e verfasserin |4 aut | |
| 700 | 0 | |a Sugondo Hadiyoso |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i In |t Jurnal Infotel |d LPPM Institut Teknologi Telkom Purwokerto, 2015 |g 14(2022), 2, Seite 85-92 |w (DE-627)DOAJ000088870 |x 24600997 |7 nnns |
| 773 | 1 | 8 | |g volume:14 |g year:2022 |g number:2 |g pages:85-92 |
| 856 | 4 | 0 | |u https://doi.org/10.20895/infotel.v14i2.768 |z kostenfrei |
| 856 | 4 | 0 | |u https://doaj.org/article/c31a62bbc72344ea8ad6f9165747ee0f |z kostenfrei |
| 856 | 4 | 0 | |u https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/768 |z kostenfrei |
| 856 | 4 | 2 | |u https://doaj.org/toc/2085-3688 |y Journal toc |z kostenfrei |
| 856 | 4 | 2 | |u https://doaj.org/toc/2460-0997 |y Journal toc |z kostenfrei |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_DOAJ | ||
| 912 | |a SSG-OLC-PHA | ||
| 951 | |a AR | ||
| 952 | |d 14 |j 2022 |e 2 |h 85-92 | ||