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https://doi.org/10.1080/00051144.2018.1541642

Performance analysis of swarm intelligence algorithms in removal of ECG artefact from tainted EEG signal

S. Suja Priyadharsini ; Department of Electronics and Communication Engineering, Anna University Regional Campus - Tirunenveli, Tirunelveli, Tamil Nadu, India
S. Edward Rajan ; Department of Electrical and Electronics Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India

Puni tekst: engleski, pdf (2 MB) str. 408-415 preuzimanja: 114* citiraj
APA 6th Edition
Priyadharsini, S.S. i Rajan, S.E. (2018). Performance analysis of swarm intelligence algorithms in removal of ECG artefact from tainted EEG signal. Automatika, 59 (3-4), 408-415. https://doi.org/10.1080/00051144.2018.1541642
MLA 8th Edition
Priyadharsini, S. Suja i S. Edward Rajan. "Performance analysis of swarm intelligence algorithms in removal of ECG artefact from tainted EEG signal." Automatika, vol. 59, br. 3-4, 2018, str. 408-415. https://doi.org/10.1080/00051144.2018.1541642. Citirano 29.09.2020.
Chicago 17th Edition
Priyadharsini, S. Suja i S. Edward Rajan. "Performance analysis of swarm intelligence algorithms in removal of ECG artefact from tainted EEG signal." Automatika 59, br. 3-4 (2018): 408-415. https://doi.org/10.1080/00051144.2018.1541642
Harvard
Priyadharsini, S.S., i Rajan, S.E. (2018). 'Performance analysis of swarm intelligence algorithms in removal of ECG artefact from tainted EEG signal', Automatika, 59(3-4), str. 408-415. https://doi.org/10.1080/00051144.2018.1541642
Vancouver
Priyadharsini SS, Rajan SE. Performance analysis of swarm intelligence algorithms in removal of ECG artefact from tainted EEG signal. Automatika [Internet]. 2018 [pristupljeno 29.09.2020.];59(3-4):408-415. https://doi.org/10.1080/00051144.2018.1541642
IEEE
S.S. Priyadharsini i S.E. Rajan, "Performance analysis of swarm intelligence algorithms in removal of ECG artefact from tainted EEG signal", Automatika, vol.59, br. 3-4, str. 408-415, 2018. [Online]. https://doi.org/10.1080/00051144.2018.1541642

Sažetak
Electroencephalogram (EEG) is the recording of electrical activities of the brain. It is contaminated by other biological signals, known as artefacts. In this research paper, the performance analysis
of three swarm intelligence incorporated adaptive neuro fuzzy inference system (ANFIS) - based techniques is made with respect to ECG artefact removal from the corrupted EEG signal. Swarm intelligence algorithms such as improved artificial immune system (IAIS), artificial immune system (AIS) and particle swarm optimization (PSO) are employed for artefact removal, by tuning the parameters of ANFIS individually. The performances of the methods are experimentally validated for both simulated and real data sets. Measures such as signal to noise ratio (SNR), mean square error (MSE) value, correlation coefficient, power spectrum density plot, sensitivity, specificity and accuracy are used for analysing the performance of the methods of simulated data set.
The sensitivity, specificity and accuracy of ANFIS-tuned IAIS (ANFIS-IAIS), are found to be 94.9%, 100% and 99.2%, respectively The sensitivity, specificity and accuracy of ANFIS-AIS and ANFISPSO are 91.9%, 100%, 98.7% and 87.9%, 100%, 98.3%, respectively. From the results, it is found that ANFIS-IAIS is more effective in removing ECG artefacts from EEG signals than ANFIS-AIS and ANFIS-PSO.

Ključne riječi
Artificial immune system (AIS); electrocardiogram (ECG); electroencephalogram (EEG); improved artificial immune system (IAIS); particle swarm optimization (PSO)

Hrčak ID: 225225

URI
https://hrcak.srce.hr/225225

Posjeta: 190 *