An Improved Firefly Optimization Algorithm for Analysis of Arrhythmia Types

Main Article Content

Mala Sinnoor
Shanthi Kaliyil Janardhan

Abstract

Irregular heartbeats rhythm is the result of arrhythmia condition which can be a threat to life if not treated at the early stage. If it is necessary to know the type of arrhythmia to treat the patient appropriately. The traditional method is complex and an efficient algorithm is required to diagnose. An improved firefly optimization algorithm is proposed to analyze arrhythmia types. Four performance measures confirm the model's effectiveness and experimental evaluation shows that it achieves a sensitivity of 86.27%, accuracy of 86.14%, precision of 87.52%, and specificity of 87.37% in arrhythmia-type classification. The algorithm can effectively classify the arrhythmia types with high accuracy and specificity.

Article Details

How to Cite
Sinnoor, M. ., & Janardhan, S. K. . (2023). An Improved Firefly Optimization Algorithm for Analysis of Arrhythmia Types . International Journal on Recent and Innovation Trends in Computing and Communication, 11(7s), 430–436. https://doi.org/10.17762/ijritcc.v11i7s.7019
Section
Articles

References

Thion Ming Chieng, Yuan wen Hau, Zaid Omar, “The study and comparison between various digital filters for ECG De-noising”, IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES) 2018.

Mala Sinnoor, Shanthi K J, “Survey on Filtering Techniques Applied to ECG Signal”, International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-X, Issue-X, July 2019.

PanelSomaraju Boda, Manjunatha Mahadevappa, Pranab Kumar Dutta, “A hybrid method for removal of power line interference and baseline wander in ECG signals using EMD and EWT”, Biomedical Signal Processing and Control, Volume 67, May 2021, 102466.

M. Sinnoor and S.K. Janardhan, An ECG Denoising Method Based on Hybrid MLTP-EEMD Model, International Journal of Intelligent Engineering and Systems 15(1) (2022), 575-583. DOI: 10.22266/ijies2022.0228.52

Varsha Harpale, Vinayak Bairagi, “An adaptive method for feature selection and extraction for classification of epileptic EEG signal in significant states”, Journal of King Saud University – Computer and Information Science, https://doi.org/10.1016/j.jksuci.2018.04.014

Majid Ali Khan Quaid, Ahmad Jalal, “Wearable sensors based human behavioral pattern recognition using statistical features and reweighted genetic algorithm”, Multimedia Tools and Applications https://doi.org/10.1007/s11042-019-08463-7

Seung-Hyeon Oh, Yu-Ri Lee, Hyoung-Nam Kim, “A Novel EEG Feature Extraction Method Using Hjorth Parameter”, International Journal of Electronics and Electrical Engineering 2(2):106-110, DOI:10.12720/ijeee.2.2.106-110

Reza Yahyaei, Tolga Esat Ozkurt, “Mean curve length: An efficient feature for brainwave biometrics”, Biomedical Signal Processing and Control 76 (2022)

V. S. Mahalle, G. N. Bonde, S. S. Jadhao, and S. R. Paraskar, “Teager Energy Operator: A Signal Processing Approach for Detection and Classification of Power Quality Events”, Proceedings of the 2nd International Conference on Trends in Electronics and Informatics (ICOEI 2018) IEEE Conference Record: # 42666; IEEE Xplore ISBN:978-1-5386-3570-4

Varun Gupta, Monika Mittal, Vikas Mittal, Arvind Kumar Sharma, Nitin Kumar Saxena, “A novel feature extraction-based ECG signal analysis”, J. Inst. Eng. India Ser. B (October 2021) 102(5):903–913 https://doi.org/10.1007/s40031-021-00591-9

C. Kamath, “ECG beat classification using features extracted from Teager energy functions in time and frequency domains”, IET Signal Process., 2011, Vol. 5, Iss. 6, pp. 575–581 575 doi: 10.1049/iet-spr.2010.0138

Alan S. Said Ahmad, Salah Matti , Adel Sabry Essa, Omar A.M. ALhabib, Sabri Shaikhow , “Features Optimization for ECG Signals Classification”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 9, No. 11, 2018 383.

Dr. S.A. Sivakumar. (2019). Hybrid Design and RF Planning for 4G networks using Cell Prioritization Scheme. International Journal of New Practices in Management and Engineering, 8(02), 08 - 15. https://doi.org/10.17762/ijnpme.v8i02.76

Dr. Padmavathi Kora, “ECG based Myocardial Infarction Detection using Hybrid Firefly Algorithm”, Computer Methods and Programs in Biomedicine,March 2017, DOI: 10.1016/j.cmpb.2017.09.015

Sofiah Ishlakhul Abda, Auli Damayanti & Edi Winarko, “Detection of Heart Abnormalities Based On ECG Signal Characteristics using Multilayer Perceptron with Firefly Algorithm-Simulated Annealing”, Contemporary Mathematics and Applications Vol. 3, No. 1, 2021, pp. 45-55.

Tonghui Li, Jieming Ma, Xinyu Pan, Yujia Zhai, and Ka Lok Man, “Classification of Arrhythmia using Multi-ClassSupport Vector Machine”, Proceedings of the International MultiConference of Engineers and Computer Scientists 2017 Vol II,IMECS 2017, March 15 - 17, 2017, Hong Kong

Tharun J. Iyer, B. Kishan & Ruban Nersisson, “Prediction and Classification of Cardiac Arrhythmia Using a Machine Learning Approach”, International Conference on Automation, Signal Processing, Instrumentation and Control, Advances in Automation, Signal Processing, Instrumentation, and Control pp 603–610 i-CASIC 2020

Van Nam Pham, Hoai Linh Tran, “Electrocardiogram (ECG) Circuit Design and Using the Random Forest to ECG Arrhythmia Classification”, International Conference on Engineering Research and Applications ICERA 2022: Advances in Engineering Research and Application pp 477–494

Sihem NITA; Salim BITAM; Abdelhamid MELLOUK, “An Enhanced Random Forest for Cardiac Diseases Identification based on ECG signal” , International Wireless Communications & Mobile Computing Conference (IWCMC), June 2018, ISSN: 2376-6506, IEEE, DOI: 10.1109/IWCMC.2018.8450361

Saumendra Kumar Mohapatra, Tripti Swarnkar, Mihir Narayan Mohanty, “Design of Random Forest Algorithm Based Model for Tachycardia Detection”, Advanced Computing and Intelligent Engineering, pp 191–199

B. Venkataramanaiah, J. Kamala, “ECG signal processing and KNN classifier-based abnormality detection by VH-doctor for remote cardiac healthcare monitoring”, Soft Computing (2020) 24:17457–17466 https://doi.org/10.1007/s00500-020-05191-1

Toulni Youssef, Belhoussine Drissi Taoufiq, Benayad Nsiri, “ECG signal diagnosis using Discrete Wavelet Transform and K-Nearest Neighbor classifier”, The 4th International Conference on Networking, Information Systems & Security, Kenitra, April 202, DOI:10.1145/3454127.3457628

Mwangi, J., Cohen, D., Costa, R., Min-ji, K., & Suzuki, H. Optimizing Neural Network Architecture for Time Series Forecasting. Kuwait Journal of Machine Learning, 1(3). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/132

Indu Saini, Dilbag Singh, Arun Khosla, “QRS detection using K-Nearest Neighbor algorithm (KNN) and evaluation on standard ECG databases”, Journal of Advanced Research, (2013) 4, 331-344, doi.org/10.1016/j.jare.2012.05.007

Muhammad Rausan Fikri, Indah Soesanti, Hanung Adi Nugroho, “ECG Signal Classification Review”, IJITEE (International Journal of Information Technology and Electrical Engineering), Vol. 5, No. 1, June 2021, DOI:10.22146/ijitee.60295

Krishna Teja, Rahul Tiwari and Satish Mohanty “Adaptive denoising of ECG using EMD, EEMD and CEEMDAN signal processing techniques”, Journal of Physics: Conference Series 1706 (2020) 012077, IOP Publishing, doi:10.1088/1742-6596/1706/1/012077

Dengyong Zhang , Shanshan Wang, Feng Li, Shang Tian, Jin Wang, Xiangling Ding, and Rongrong Gong , “An Efficient ECG Denoising Method Based on Empirical Mode Decomposition, Sample Entropy, and Improved Threshold Function”, Hindawi Wireless Communications and Mobile Computing Volume 2020, Article ID 8811962, 11 pages https://doi.org/10.1155/2020/8811962

Lahcen El Bouny · Mohammed Khalil · Abdellah Adib, “Ecg Signal Filtering Based On Ceemdan With Hybrid Interval Thresholding And Higher Order Statistics To Select Relevant Modes”, May 2019 Multimedia Tools And Applications 78(6). Doi:10.1007/S11042-018-6143-X

Mehrnoosh Sadat Safi , Seyed Mohammad Mehdi Safi, “Early detection of Alzheimer’s disease from EEG signals using Hjorth parameters”, Biomedical Signal Processing and Control, 2021, https://doi.org/10.1016/j.bspc.2020.102338

Gunjal, M. B. ., & Sonawane, V. R. . (2023). Multi Authority Access Control Mechanism for Role Based Access Control for Data Security in the Cloud Environment. International Journal of Intelligent Systems and Applications in Engineering, 11(2s), 250 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2623

Xin-She Yang, “Firefly Algorithm, Lévy Flights and Global Optimization”, Research and Development in Intelligent Systems XXVI pp 209–218, Springer

J. Wu, Y.-G. Wang, K. Burrage, Y.-C. Tian, B. Lawson and Z. Ding, An improved firefly algorithm for global continuous optimization problems, Expert Systems with Applications 149 (2020), 113340. https://doi.org/10.1016/j.eswa.2020.113340