Combining algorithms in automatic detection of R-peaks in ECG signals
ABSTRACT R-peak detection is the crucial first step in every automatic ECG analysis. Much work has been carried out in this field, using various methods ranging from filtering and threshold methods, through wavelet methods, to neural networks, and others. Performance is generally good, but each method has situations where it fails. In this paper we suggest an approach to automatically combine different algorithms, here the Pan Tompkins and wavelet algorithms, for detection of R-peaks in ECG signals, in order to benefit from the strengths of both algorithms. Experimental results and analysis are provided on the MIT-BIH Arrhythmia Database. We obtained substantial improvements on the test data with respect to the best individual algorithm.
- SourceAvailable from: Hrishikesh Mishra[Show abstract] [Hide abstract]
ABSTRACT: Chaotic behavior of electrocardiogram (ECG) signal of myocardial and non-myocardial infarctions is differentiated using neuro-GA approach, incorporating heuristically chosen phase space fractal dimension (PSFD) of ECG data. A remarkable improvement of diagnostic efficiency, sensitivity and specificity was observed in case study.Journal of Scientific & Industrial Research. 01/2009; 68:866-870.
Conference Paper: Low Cost, Low Power QRS Detection Module Using PIC[Show abstract] [Hide abstract]
ABSTRACT: This paper presents an efficient, low cost, low power QRS complexes detection module for ECG analysis. In past lot of research on algorithms for QRS detection has been carried out. All such methods mostly rely on a priori knowledge of the shape of the QRS complexes and general aspects of the ECG. Most of approaches require more CPU time and involve complex mathematics which is difficult to implement for low cost, low power pacemaker design. Moreover, baseline shift, power line interference, muscle noise and other artifacts poses further bottleneck for accurate QRS detection. Detailed analysis of various approaches and their constraints for real time pacemaker application has been done in this paper. A simple, cost competitive smart design has also been proposed. Our solution has very low power requirement and achieves high QRS detection performance without compromising timing accuracy and reliability. To achieve improved QRS detection reliability, various noise components have been attenuated by clever implementation of optimized prefiltering in conjunction with a A/D conversion and Zero-crossing detection. Complete system proposed in this paper has been designed around a PIC microcontroller, Data Acquisition module and a display unit. Proposed design has been tested for extensive data collected from hospitals. Result achieved confirms the design approach illustrated.Communication Systems and Network Technologies (CSNT), 2011 International Conference on; 07/2011
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ABSTRACT: This work presents a novel easy-to-use system intended for the fast and non-invasive monitoring of the Lead I electrocardiogram (ECG) signal by using a wireless steering wheel. The system uses a dual ground electrode configuration connected to a low-power analog front-end to reduce 50/60 Hz interference and it is able to show a stable ECG signal with good enough quality for monitoring purposes in less than 5 s. A novel heart rate detection algorithm based on the continuous wavelet transform (CWT) has been implemented, which is specially designed to be robust against the most common sources of noise and interference present when acquiring the ECG in the hands, i.e., electromyographic (EMG) noise and baseline wandering. The algorithm shows acceptable performance even under non-ordinary high levels of EMG noise and yields a positive predictivity value of 100.00 % and a sensitivity of 99.75 % when tested in normal use with subjects of different age, gender and physical condition.IEEE Sensors Journal 01/2012; · 1.48 Impact Factor