An efficient removal of power-line interference and baseline wander from ECG signals by employing Fourier decomposition technique

Analysis of electrocardiogram (ECG) signals helps us in detecting various abnormalities and diseases of heart. These signals commonly suffer from the problems of baseline wander and power-line interference. In this paper, we propose a new approach to eliminate such noises from ECG signals using the Fourier decomposition method. Simulation results are presented to show the efficacy of our method over previously used EMD-based methods. The proposed method has been shown to preserve shape characteristics of ECG signals of heart abnormalities.

Baseline Wander and Power-Line Interference Removal from ECG Signals Using Fourier Decomposition Method

The impulse components of different periods in the composite fault signal of rolling bearing are extracted difficultly due to the background noise and the coupling of composite faults, which greatly affects the accuracy of composite fault diagnosis. To accurately extract the periodic impulse components from the composite fault signals, we introduce the theory of Ramanujan sum to generate the precise periodic components (PPCs). In order to comprehensively extract major periods in composite fault signals, the SOSO-maximum autocorrelation impulse harmonic to noise deconvolution (SOSO-MAIHND) method is proposed to reduce noise and enhance the relatively weak periodic impulses. Based on this, an enhanced periodic mode decomposition (EPMD) method is proposed. The experimental results indicate that the EPMD is an effective method for composite fault diagnosis of rolling bearings.

Enhanced periodic mode decomposition and its application to composite fault diagnosis of rolling bearings.

The Ramanujan sum cq(n) has been used by mathematicians to derive many important infinite series expansions for arithmetic-functions in number theory. Interestingly, this sum has many properties wh...

https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2018.0446

Srinivasa Ramanujan and signal-processing problems

Ramanujan Periodic Transform (RPT) is a newly emerging transformation technique in the field of signal processing. It uses an integer bases (obtained from Ramanujan sum) for transformation. A recorded ECG signal often contains artifacts (bioelectric signals) namely, baseline wander, muscle artifacts (EMG-Electromyogram), motion artifacts, powerline interference (PLI) and its harmonics. With certain precautions during signal recording we can avoid both muscle and motion artifacts. The other noises can be reduced by preprocessing of the recorded ECG signal. In this paper, RPT is used for preprocessing, to reduce baseline wander noise, PLI and its harmonics. The proposed methodology is tested on a record from MIT-BIH Arrhythmia database for different block sizes. A sum (E) of Euclidean errors per block (e i -ith block), is used as a measure to compare the results of RPT with notch filter technique. From the results, the RPT is reducing the noise with minimum error (E), when compared with notch filter technique.

Joint reduction of baseline wander, PLI and its harmonics in ECG signal using Ramanujan Periodic Transform

Suppression of interference from narrowband frequency signals play vital role in many signal processing and communication applications. A transform based method for suppression of narrow band interference in a biomedical signal is proposed. As a specific example Electrocardiogram (ECG) is considered for the analysis. ECG is one of the widely used biomedical signal. ECG signal is often contaminated with baseline wander noise, powerline interference (PLI) and artifacts (bioelectric signals), which complicates the processing of raw ECG signal. This work proposes an approach using Ramanujan periodic transform for reducing PLI and is tested on a subject data from MIT-BIH Arrhythmia database. A sum (E) of Euclidean error per block (e i ) is used as measure to quantify the suppression capability of RPT and notch filter based methods. The transformation is performed for different lengths (N), namely 36, 72, 108, 144, 180. Every doubling of N-points results in 50% reduction in error (E).

Removal of narrowband interference (PLI in ECG signal) using Ramanujan periodic transform (RPT)

Ramanujan Periodic Transform (RPT) is the newly emerging transform to identify periodicities in the given data RPT represents the given finite length sequence into a weighted linear combination of signals from Ramanujan subspaces RPT has the inability of handling the frequency components with in the Ramanujan subspace This is due to the basis function (Ramanujan sum) used in RPT To overcome this, a new mixed basis representation is proposed which uses both the sequences from Ramanujan subspace and complex exponentials as basis and both the basis are orthogonal to each other Using this mixed basis representation, the problem of removing Power Line Interference (PLI) in ECG data is addressed The methodology is tested on the MIT-BIH Arrhythmia database and the obtained results are competitive when compared with other techniques

Ramanujan and DFT mixed basis representation for removal of PLI in ECG signal

The discrete control problem of vertical take-off and landing unmanned aerial vehicle (VTOL UAV) in the presence of time-varying uncertain disturbances is developed in this paper. The complexity of control problem is managed by dividing the dynamical model into two subsystems i.e. translational dynamics and rotational dynamics, where each subsystem is composed of three states. A discrete-time quasi-sliding mode control (DTQSMC) is extended to maintain the trajectory tracking control by proposing a new-reaching law for VTOL UAV. A robust controller is designed to handle unknown time-varying disturbances acting upon the translational and rotational dynamics. Moreover, the proposed controller is designed to reduce the chattering issue that commonly appears in conventional sliding mode control (SMC). Rigorous mathematical proof is presented to analyze the stability of the entire closed-loop system. The performance of this design is demonstrated with numerous numerical analyses and simulations.

Extended Discrete-Time Quasi-Sliding Mode Control for VTOL UAV in the Presence of Uncertain Disturbances

Reconfigurable aerial platforms such as multicopter unmanned aerial vehicles (UAVs) allow the design of fail-safe systems because of inherent redundancy in actuators and sensors to maintain stability with a reduction in flight performance. The methods based on univariate and multivariate time series analysis of just the attitude signals can pave the way for modelfree systems that can be generalized across a class of UAVs like multicopters. In this paper, we present a critical analysis of real-flight attitude time-series signals and investigate them for data-driven motor fault and failure detection and isolation (FDI), specifically for multicopters configurations like quadcopters and hexacopters. We analyze flight data for different scenarios of outdoor flights, healthy and faulty, hovering and cruising, loss of efficiency, and single-rotor failure of every motor. We tested it for small to medium-sized multi-copters. The failure detection and classification are performed without relying on analytical system modeling or the knowledge of the controller.Thus, we perform three major assessments: vector autoregression (VAR) using residual variance, time-frequency analysis, and dimensionality analysis of the recorded variables, to support the classification framework. To the author’s best knowledge, it is an early attempt at laying the foundation for engineering features from streaming attitude data, instead of simulations, that works on existing open-source autopilot hardware and is agnostic to the firmware as well. This foundation allows us to implement various FDI frameworks in real-time directly using the above variables on multicopters, which drastically increases the levels of safety and scalability of unmanned flights in drone applications.

Srikanth Goli

Papers

Removal of narrowband interference (PLI in ECG signal) using Ramanujan periodic transform (RPT)

Ramanujan and DFT mixed basis representation for removal of PLI in ECG signal

Extended Discrete-Time Quasi-Sliding Mode Control for VTOL UAV in the Presence of Uncertain Disturbances

Multivariate Data Analysis for Motor Failure Detection and Isolation in A Multicopter UAV Using Real-Flight Attitude Signals

Extended Sliding Mode Control Scheme for a VTOL UAV with Time-Varying Disturbances