Fast Electrocardiogram Amplifier Recovery after Defibrillation Shock

A procedure for fast ECG amplifier recovery after defibrillation shocks was developed and simulated in the MATLAB environment. Exponentially decaying post-shock voltages have been recorded. Signals from the AHA database are taken and mixed with the recorded exponential disturbances. The algorithm applies moving averaging (comb filter) on the compound input signal, thereby obtaining the samples of the disturbance. They are currently subtracted from the input signal. The results obtained show that its recovery is practically instantaneous

Locally-adaptive Myriad Filtration of One-dimensional Complex Signal

Locally-adaptive algorithms of myriad filtering are proposed with adaptation of a sample myriad linearity parameter K, depending upon local estimates of a signal, and with “hard” switching of sliding window length settings and a coefficient which influences on the parameter K. Statistical estimates of the filters quality are obtained using a criterion of a minimum mean-square error for a model of one-dimensional complex signal that includes different elementary segments under conditions of additive Gaussian noise with zero mean and different variances and possible spikes presence. Improvement of integral and local performance indicators is shown in comparison to the highly effective non-linear locally-adaptive algorithms for the considered test signal. Having a complex signal of high efficiency, one of the proposed algorithms provides nearly optimal noise suppression at the segments of linear change of a signal; other algorithm provides higher quality of step edge preservation and the best noise suppression on a const signal. Better efficiency in cases of low and high noise levels is achieved by preliminary noise level estimation through comparison of locally-adaptive parameter and thresholds. It is shown that, in order to ensure better spikes removal, it is expedient to pre-process the signal by robust myriad filter with small window length. The considered adaptive nonlinear filters have possibility to be implemented in a real time mode

Common-Mode Driven Synchronous Filtering of the Powerline Interference in ECG

Powerline interference (PLI) is a major disturbing factor in ground-free biopotential acquisition systems. PLI produces both common-mode and differential input voltages. The first is suppressed by a high common-mode rejection ratio of bioamplifiers. However, the differential PLI component evoked by the imbalance of electrode impedances is amplified together with the diagnostic differential biosignal. Therefore, PLI filtering is always demanded and commonly managed by analog or digital band-rejection filters. In electrocardiography (ECG), PLI filters are not ideal, inducing QRS and ST distortions as a transient reaction to steep slopes, or PLI remains when its amplitude varies and PLI frequency deviates from the notch. This study aims to minimize the filter errors in wide deviation ranges of PLI amplitudes and frequencies, introducing a novel biopotential readout circuit with a software PLI demodulator–remodulator concept for synchronous processing of both differential-mode and common-mode signals. A closed-loop digital synchronous filtering (SF) algorithm is designed to subtract a PLI estimation from the differential-mode input in real time. The PLI estimation branch connected to the SF output includes four stages: (i) prefilter and QRS limiter; (ii) quadrature demodulator of the output PLI using a common-mode driven reference; (iii) two servo loops for low-pass filtering and the integration of in-phase and quadrature errors; (iv) quadrature remodulator for synthesis of the estimated PLI using the common-mode signal as a carrier frequency. A simulation study of artificially generated PLI sinusoids with frequency deviations (48–52 Hz, slew rate 0.01–0.1 Hz/s) and amplitude deviations (root mean square (r.m.s.) 50–1000 μV, slew rate 10–200 μV/s) is conducted for the optimization of SF servo loop settings with artificial signals from the CTS-ECG calibration database (10 s, 1 lead) as well as for the SF algorithm test with 40 low-noise recordings from the Physionet PTB Diagnostic ECG database (10 s, 12 leads) and CTS-ECG analytical database (10 s, 8 leads). The statistical study for the PLI frequencies (48–52 Hz, slew rate ≤ 0.1 Hz/s) and amplitudes (≤1000 μV r.m.s., slew rate ≤ 40 μV/s) show that maximal SF errors do not exceed 15 μV for any record and any lead, which satisfies the standard requirements for a peak ringing noise of < 25 μV. The signal-to-noise ratio improvement reaches 57–60 dB. SF is shown to be robust against phase shifts between differential- and common-mode PLI. Although validated for ECG signals, the presented SF algorithm is generalizable to different biopotential acquisition settings via surface electrodes (electroencephalogram, electromyogram, electrooculogram, etc.) and can benefit many diagnostic and therapeutic medical devices

Common-Mode Driven Synchronous Filtering of the Powerline Interference in ECG

Powerline interference (PLI) is a major disturbing factor in ground-free biopotential acquisition systems. PLI produces both common-mode and differential input voltages. The first is suppressed by a high common-mode rejection ratio of bioamplifiers. However, the differential PLI component evoked by the imbalance of electrode impedances is amplified together with the diagnostic differential biosignal. Therefore, PLI filtering is always demanded and commonly managed by analog or digital band-rejection filters. In electrocardiography (ECG), PLI filters are not ideal, inducing QRS and ST distortions as a transient reaction to steep slopes, or PLI remains when its amplitude varies and PLI frequency deviates from the notch. This study aims to minimize the filter errors in wide deviation ranges of PLI amplitudes and frequencies, introducing a novel biopotential readout circuit with a software PLI demodulator&ndash;remodulator concept for synchronous processing of both differential-mode and common-mode signals. A closed-loop digital synchronous filtering (SF) algorithm is designed to subtract a PLI estimation from the differential-mode input in real time. The PLI estimation branch connected to the SF output includes four stages: (i) prefilter and QRS limiter; (ii) quadrature demodulator of the output PLI using a common-mode driven reference; (iii) two servo loops for low-pass filtering and the integration of in-phase and quadrature errors; (iv) quadrature remodulator for synthesis of the estimated PLI using the common-mode signal as a carrier frequency. A simulation study of artificially generated PLI sinusoids with frequency deviations (48&ndash;52 Hz, slew rate 0.01&ndash;0.1 Hz/s) and amplitude deviations (root mean square (r.m.s.) 50&ndash;1000 &mu;V, slew rate 10&ndash;200 &mu;V/s) is conducted for the optimization of SF servo loop settings with artificial signals from the CTS-ECG calibration database (10 s, 1 lead) as well as for the SF algorithm test with 40 low-noise recordings from the Physionet PTB Diagnostic ECG database (10 s, 12 leads) and CTS-ECG analytical database (10 s, 8 leads). The statistical study for the PLI frequencies (48&ndash;52 Hz, slew rate &le; 0.1 Hz/s) and amplitudes (&le;1000 &mu;V r.m.s., slew rate &le; 40 &mu;V/s) show that maximal SF errors do not exceed 15 &mu;V for any record and any lead, which satisfies the standard requirements for a peak ringing noise of &lt; 25 &mu;V. The signal-to-noise ratio improvement reaches 57&ndash;60 dB. SF is shown to be robust against phase shifts between differential- and common-mode PLI. Although validated for ECG signals, the presented SF algorithm is generalizable to different biopotential acquisition settings via surface electrodes (electroencephalogram, electromyogram, electrooculogram, etc.) and can benefit many diagnostic and therapeutic medical devices

Separation of the Electromyographic from the Electrocardiographic Signals and Vice Versa : A Topical Review of the Dynamic Procedure

Electrocardiographic (ECG) and electromyographic (EMG) signals are inevitably and simultaneously recorded from the same electrodes and are respectively useful signal and noise in electrocardiography, and vice versa in electromyography. The frequency domains of the two signals overlap, making it difficult to filter the noise without distortion of the useful signal. An original ‘dynamic method’ for separation of the two signals was created. In a series of publications that began in 1999 with filtering of EMG noise from ECG signal, we have described the method and have made a number of improvements such as noise analysis and automatic on/off triggering in presence/absence of noise, online application, and tuning the parameters, to fulfill the last filtering recommendations of the American Heart Association. No matter if the Dynamic procedure is to be used in electrocardiography or in electromyography, the method contains the following: (i) Evaluation of the frequency bands of the ECG signal; (ii) filtering (suppression) of the EMG signal by dynamic change of the size of the filtering window for maximal preservation of the morphology of the ECG waves. The cutoff frequency is individual for any signal sample and varies from 13 Hz at the linear segments of the ECG signal, trough 25 Hz for the T-waves of high amplitude, and up to 400 Hz for the QRS-complexes; (iii) EMG signal separation by subtraction of the filtered ECG signal from ECG + EMG initial signal. With the current review, we are attempting to summarize all done over the years on the Dynamic procedure.publishedVersionPeer reviewe