Key result
A proposed wavelet-based QRS complex detection algorithm for a smartphone-based ECG and phonocardiogram monitoring system achieved 99.90% positive prediction and 99.82% sensitivity.
Why the study?
Discriminating the first and second heart sounds is difficult when additional heart sounds and murmurs are present.
A novel ECG and PCG monitoring system with a smartphone application and high-accuracy QRS detection algorithm may assist in cardiac auscultation and diagnosis.
Heart-sound auscultation is a rapid and fundamental technique used for examining the cardiovascular system. The main components of heart sounds are the first and second heart sounds. Discriminating these heart sounds under the presence of additional heart sounds and murmurs will be difficult. To recognize these signals efficiently, this study proposes a monitoring system with phonocardiogram and electrocardiogram. This system has two key points. The first is chip implementation, including capacitor coupled amplifier, transimpedance amplifier, high-pass sigma-delta modulator, and digital signal processing block. The chip in the system is fabricated in 0.18 μm standard complementary metal-oxide-semiconductor process. The second is a software application on smartphones for heart-related physiological signal recording, display, and identification. A wavelet-based QRS complex detection algorithm verified by MIT/BIH Arrhythmia Database is also proposed. The overall measured positive prediction, sensitivity, and error rate of the proposed algorithm are 99.90%, 99.82%, and 0.28%, respectively. During auscultation, doctors may refer to these physiological signals displayed on the smartphone and simultaneously listen to the heart sounds to diagnose the potential heart disease. By taking advantage of signal visualization and keeping the original diagnosis procedure, the uncertainty existing in heart sounds can be eliminated, and the training period to acquire auscultation skills can be reduced.
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Lee et al. (2019) studied Cardiac auscultation and arrhythmia. Electrocardiogram and phonocardiogram monitoring system with wavelet-based QRS detection algorithm was evaluated on Algorithm performance (positive prediction, sensitivity, and error rate). A proposed wavelet-based QRS complex detection algorithm for a smartphone-based ECG and phonocardiogram monitoring system achieved 99.90% positive prediction and 99.82% sensitivity.
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