Detection of Murmur from Non-Stationarity of Heart Sounds
P. Careena1, M. Mary Synthuja Jain Preetha2 and P. Arun31Department of Electronics and Communication Engineering, Amal Jyothi College of Engineering, 686518-Kanjirapally.
2Department of Electronics and Communication Engg., Noorul Islam University, 629180- Nagercoil.
3Department of Electronics and Communication Engineering, St. Joseph’s College of Engineering and Technology, 686579- Palai.
Corresponding Author E-mail: careenaarun@gmail.com
Abstract: Early diagnosis of heart diseases bears a major role in saving lives. Presence of spurious extra-frequency components, termed as murmurs within the phonocardiography record may be indicative of valvular disorders like stenosis, lesions or regurgitation. It is difficult to identify the subtitle spectral components of murmurs through subjective audition. In this paper, a technique is proposed to detect the presence of murmur from the heart signal by analyzing their non-stationarity behavior by using autocorrelation based features namely, Standard Error (SE) of Auto-Correlation Function (ACF) and absolute deviation of SE from the reciprocal of the square root of number of samples (β). The selected features corresponding to normal and murmur differ with a ‘P’ value of 1.80 x10-14 (dataset 1) and 2.20 x10-76 (dataset 2) for SE and β, respectively. It is found that SE and β could effectively distinguish normal and murmur with 100% accuracy, sensitivity, and specificity.
Keywords: Autocorrelation; Heart Abnormality; Murmur, Non-Stationarity; PCG Signal; Time Domain Features; Type of Heart Signal Back to TOC