Accurate tunable-Q wavelet transform based method for QRS complex detection. (May 2019)

• Record Type: Journal Article
• Authors: Sharma, Ashish; Patidar, Shivnarayan; Upadhyay, Abhay; Rajendra Acharya, U.
• Is Part Of: Computers & electrical engineering. Volume 75(2019)
• Page Start: 101
• Page End: 111
• Publication Date: 2019-05
• Subjects: TQWT -- ECG -- QRS complex -- Correntropy; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.01.025
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: A novel method to detect the QRS complexes from ECG signals is presented. Tunable-Q wavelet transform and correntropy are employed. System is validated using the MIT-BIH arrhythmia dataset. Obtained accuracy is 99.88%. Abstract: The patient monitoring and diagnosis using electrocardiogram (ECG) signal involve accurate QRS complex detection. However, the reliability of QRS detection is limited by the presence of variety of noises and morphologies. A high performance QRS complex detection scheme based on the tunable-Q wavelet transform (TQWT) is presented in this paper. The tunable parameters of TQWT can improve the localization of QRS when selected suitably. These parameters help to choose appropriate mother wavelet and proper sub-band of interest with fine separation from the undesired sub-bands. The method starts with TQWT based decomposition and reconstruction of the ECG signal with optimally selected input parameters and sub-bands. The correntropy envelope is computed from the resultant QRS enhanced signal which in turn assists the QRS localization. Our proposed method has yielded an average detection accuracy of 99.88%, sensitivity of 99.89% and positive productivity of 99.83% on the MIT-BIH arrhythmia database.