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In this paper, an automatic detecting algorithm for QRS complex detecting was applied for analyzing ECG recordings and five criteria for dangerous arrhythmia diagnosing are applied for a protocol type of automatic arrhythmia diagnosing system. The automatic detecting algorithm applied in this paper detected the distribution of QRS complexes in ECG...
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The extraction of the QRS waveform from the electrocardiogram (ECG) signal is an important part for cardiac disease detection. Pan and Tompkins algorithm of QRS detection is an established method for extraction of this part of ECG. This paper proposes a real time implementation of this algorithm using new technology of low power and cost micro-cont...
In this paper a hardware implementation of the finite impulse response narrow band-stop time-varying filter based on the infinite impulse prototype filter is proposed. The notch filter is used for removing power-line interferences from biomedical source, i.e. ECG signal. In order to suppress the transient state of the proposed filter, the pole radi...
Heart rate sensing is very important. Method of measuring heart pulse by using an electrocardiogram (ECG) technique is described. Electrocardiogram is a measurement of the potential difference (the electrical pulse) generated by a cardiac tissue, mainly the heart. This paper also reports the development of a three lead ECG hardware system that woul...
QRS complex (heart beat) detection is frequently used by physicians to detect abnormal electrical activities (such as the cardiac arrhythmia, tachycardia, and bradycardia) in the heart. Algorithms for real-time detection of cardiac arrhythmia are critical, as ambulances and critical care facilities often require heart rate data for in-situ diagnosi...
Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite...
Citations
... Median type filters have been used in medical applications. For example, median filters are used in denoising electrocardiography signals which indicate the heart health of patients (Yeh et al. 2008) and for mechatronics applications (Leeb et al. 1997). ...
A novel weighted recursive median (WRM) filter for denoising vibration signals is presented in this paper. Vibration signals emanating from rotating systems are typically periodic as the transients die out with time due to damping. The weights of this nonlinear filter are optimized for typical vibration signals encountered in helicopter main rotor vibration such as multi-frequency sinusoids. The resulting filter removes outliers and reduces noise to a considerable extent when compared to a baseline noisy signal. FFT results show that the WRM filter is able to perform the noise removal while causing no change to the underlying frequencies in the ideal signal. The integer design space for the filter is multimodal with several local minima and the filter design problem presents a benchmark problem for testing integer programming algorithms. An exhaustive search of the design space ensures that all the local minimum points are found and the global minimum is identified. The 5-point median filter with weights [2 1 2 1 2] is found to be good choice for denoising vibration signals. The WRM filter can be used as a data preprocessor before subjecting the vibration signals to fault detection and isolation algorithm.
The removal of noise and outliers from health signals is an important problem in jet engine health monitoring. Typically, health signals are time series of damage indicators, which can be sensor measurements or features derived from such measurements. Sharp or sudden changes in health signals can represent abrupt faults and long term deterioration in the system is typical of gradual faults. Simple linear filters tend to smooth out the sharp trend shifts in jet engine signals and are also not good for outlier removal. We propose new optimally designed nonlinear weighted recursive median filters for noise removal from typical health signals of jet engines. Signals for abrupt and gradual faults and with transient data are considered. Numerical results are obtained for a jet engine and show that preprocessing of health signals using the proposed filter significantly removes Gaussian noise and outliers and could therefore greatly improve the accuracy of diagnostic systems. [DOI: 10.1115/1.3200907]
