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

Abstract

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.

Digital Filter Architecture Based on Modified Winograd Method F(2× 2, 5× 5) and Residue Number System

“…Let's choose a polynomial 𝑚(𝑥) = 𝑚 (0) (𝑥) • 𝑚 (1) (𝑥) • 𝑚 (2) (𝑥) • 𝑚 (3) (𝑥) • 𝑚 (4) (𝑥) • 𝑚 (5) (𝑥) • 𝑚 (6)…”

“…Then the remainder after division 𝑤(𝑥) by 𝑚 (𝑖) (𝑥) are 𝑤 (0) (𝑥) = 𝑤 0 , 𝑤 (1) (𝑥) = 𝑤 0 + 𝑤 1 + 𝑤 2 + 𝑤 3 + 𝑤 4 , 𝑤 (2) (𝑥) = 𝑤 0 − 𝑤 1 + 𝑤 2 − 𝑤 3 + 𝑤 4 , (8) 𝑤 (3) (𝑥) = 𝑤 0 + 2𝑤 1 + 4𝑤 2 + 8𝑤 3 + 16𝑤 4 , 𝑤 (4) (𝑥) = 𝑤 0 − 2𝑤 1 + 4𝑤 2 − 8𝑤 3 + 16𝑤 4 , w (5)…”

“…Digital filters are widely used as components of complex digital signal processing and analysis systems. These systems are used in practical tasks such as medicine [1][2][3][4], geolocation [5,6], video surveillance systems [7], product quality control in production [8], and many other areas. In these practical problems, performance plays a main role.…”