Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

Automated detection and classification of electrocardiogram (ECG) noise sources can play a crucial role in reliable measurement of ECG parameters for accurate diagnosis of cardiovascular diseases (CVDs) under unsupervised telehealth monitoring and intensive care unit (ICU) applications. Although the methods had quite acceptable detection rates, most methods are too complicated for real-time implementation for wearable cardiac health monitoring devices. Therefore, in this paper, we present a low-complexity algorithm for automatically detecting and classifying the ECG noises including flat line (FL), time-varying noise (TVN), baseline wander (BW), abrupt change (ABC), muscle artifact (MA) and power line interference (PLI). The proposed method is based on the moving average (MAv) and derivative filters and the five temporal features including turning points, global and local amplitude estimates, zerocrossing and autocorrelation peak values. The proposed method is tested and validated using a wide variety of clean and noisy ECG signals taken from the MIT-BIH arrhythmia database and Physionet Challenge database. The method achieves an average sensitivity (Se) of 98.55%, positive productivity (+P) of 95.27% and overall accuracy (OA) of 94.19% for classifying the noises. Results show that the proposed method outperforms the other existing methods. © 2016 IEEE.

World University root node

Department of Electrical Engineering

2016 International Conference on Signal Processing and Communications, SPCOM 2016

Low-complexity detection and classification of ECG noises for automated ECG analysis system

Automatic modulation classification (AMC) plays an important role in identifying the modulation format of a signal. Most of the existing modulation classifiers assume the signal to be contaminated only by additive white Gaussian noise (AWGN). However, the performances of these traditional classifiers degrade in the presence of non-Gaussian impulsive noise. In this paper, we present a novel automatic modulation classification algorithm based on variational mode decomposition (VMD) in presence of non-Gaussian impulsive noise and additive white Gaussian noise. Our proposed method is a three step process. In the first step, received signal is decomposed into modes. It is clear from simulation results that impulse noise is effectively captured in the first mode. In the second step, all other modes are added except first mode to reduce the impact of impulse noise in the received signal. Then in the third step, cyclostationary feature based classifiers are employed to identify the modulation type. The proposed algorithm is evaluated using well-known existing classifiers for different digital modulation techniques. Comparative results depict the superior performance of our proposed method over other traditional methods under different noise conditions. © 2016 IEEE.

2016 22nd National Conference on Communication, NCC 2016

A novel method for automatic modulation classification under non-Gaussian noise based on variational mode decomposition

In this Letter, the authors propose an efficient and robust method for automatically determining the VT and VF events in the electrocardiogram (ECG) signal. The proposed method consists of: (i) discrete cosine transform (DCT)-based noise suppression; (ii) addition of bipolar sequence of amplitudes with alternating polarity; (iii) zero-crossing rate (ZCR) estimation-based VTVF detection; and (iv) peak-to-peak interval (PPI) feature based VT/VF discrimination. The proposed method is evaluated using 18,000 episodes of different ECG arrhythmias taken from 6 PhysioNet databases. The method achieves an average sensitivity (Se) of 99.61%, specificity (Sp) of 99.96%, and overall accuracy (OA) of 99.92% in detecting VTVF and non-VTVF episodes by using a ZCR feature. Results show that the method achieves a Se of 100%, Sp of 99.70% and OA of 99.85% for discriminating VT from VF episodes using PPI features extracted from the processed signal. The robustness of the method is tested using different kinds of ECG beats and various types of noises including the baseline wanders, powerline interference and muscle artefacts. Results demonstrate that the proposed method with the ZCR, PPI features can achieve significantly better detection rates as compared with the existing methods. © 2016 The Institution of Engineering and Technology.

Healthcare Technology Letters

Efficient and robust ventricular tachycardia and fibrillation detection method for wearable cardiac health monitoring devices

Removal of muscle artifacts from the ECG signals is crucial for a reliable and accurate measurement of local features of ECG signals. In this paper, we present an automatic method for removal of muscle artifacts from ECG signals, based on four steps: decomposing ECG signal using sparse signal decomposition on mixed dictionaries; obtaining QRS complex signal; determining time-instants of R-peak; and removal of muscle artifacts from ECG signal. The noise reduction performance of the proposed method is tested and validated using ECG signals taken from a standard MIT-BIH Arrhythmia database. The reconstructed signals are assessed using both subjective quality assessment test and objective quality assessment metrics. Performance evaluation results show that the proposed method outperforms other existing ECG denoising methods inadequately removing the muscle artifacts without significantly distorting the morphologies of P-wave, QRS-complex and T-wave of the ECG signals. © 2016 IEEE.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

A unified sparse signal decomposition and reconstruction framework for elimination of muscle artifacts from ECG signal

IgE is commonly known for its role in the Th2 responses, protection against helminth parasites and pathogenesis of allergy. A recent report shows that IgE autoantibodies to dsDNA plays a major role in the pathogenesis of lupus nephritis by exacerbating the interferon-alpha; responses in plasmacytoid dendritic cells.

Biological Sciences and Engineering

Fulltext

Cell Research

Lupus pathogenesis: Role of IgE autoantibodies

Cellular and Molecular Immunology

Impaired regulatory T cell function in autoimmune diseases: Are microRNAs the culprits?

The rapalogs everolimus and temsirolimus that inhibit mTOR signaling are used as antiproliferative drugs in several cancers. Here we investigated the influence of rapalogs-mediated immune modulation on their antitumor efficacy. Studies in metastatic renal cell carcinoma patients showed that everolimus promoted high expansion of FoxP3+ Helios Helios+Ki67+ regulatory CD4 T cells (Tregs ). In these patients, rapalogs strongly enhanced the suppressive functions of Tregs , mainly in a contact-dependent manner. Paradoxically, a concurrent activation of spontaneous tumor-specific Th1 immunity also occurred. Furthermore, a high rate of Eomes+ CD8+ T cells was detected in patients after a long-term mTOR inhibition. We found that early changes in the Tregs /antitumor Th1 balance can differentially shape the treatment efficacy. Patients presenting a shift toward decreased Tregs levels and high expansion of antitumor Th1 cells showed better clinical responses. Studies conducted in tumor-bearing mice confirmed the deleterious effect of rapalogs-induced Tregs via a mechanism involving the inhibition of antitumor T-cell immunity. Consequently, the combination of temsirolimus plus CCR4 antagonist, a receptor highly expressed on rapalogs-exposed Tregs , was more effective than monotherapy. Altogether, our results describe for the first time a dual impact of host adaptive antitumor T-cell immunity on the clinical effectiveness of rapalogs and prompt their association with immunotherapies. ©2016 American Association for Cancer Research.

Cancer Research

Rapalogs efficacy relies on the modulation of antitumor T-cell immunity

Low complexity distributed active noise control (ANC) systems are highly demanded for industrial applications. The ANC systems based on centralized multichannel filtered s least mean square (FsLMS) and Chebyshev-functional link artificial neural network (C-FLANN) FsLMS have shown promising results in cancellation of active noise. In distributed ANC scenario, there is a possibility in reducing the complexity by incorporating constraints on secondary paths. In this paper, we present improved distributed C-FLANN FsLMS algorithm for active control of nonlinear noise process. Based upon simulation study, it has been proven that the computational complexity can be significantly reduced by considering the error introduced at the target node due to the neighboring nodes in addition with self error of that node. Without significantly degrading the noise cancellation performance, the improved constrained distributed C-FLANN FsLMS scheme can achieve complexity improvement of 33.86% for multiplications and 22.58% for additions as compared with multichannel FsLMS considering 4 nodes. © 2016 IEEE.

2016 IEEE Region 10 Conference (TENCON)

Low complexity distributed active noise control using secondary path constraints

This paper presents a new control scheme for a single-phase PWM rectifier with Auxiliary Current Injection Circuit (ACIC) to improve the load transient response and DC bus voltage controller bandwidth. The PWM rectifier and ACIC are controlled to mitigate the 2nd harmonic ripple in the DC bus under steady-state as well as the peak undershoot and overshoot during load transients. Analytical equations governing the operation of the single phase PWM rectifier with proposed ACIC controller are derived and presented. The proposed controller is designed and simulated using MATLAB Simulink and implemented on a 100 W test setup. The simulation and experimental results are presented to validate the performance of proposed controller. © 2016 IEEE.

Conference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC

A new control scheme to improve load transient response of single phase PWM rectifier with Auxiliary Current Injection Circuit

In present era, day by day new engineering materials are forthcoming but among all, the composites, especially epoxy polymer composites have important advantages because of its superior mechanical properties such as high strength to weight ratio, high wear resistance, corrosion resistance, electrical resistance, and etc. It can replace the traditional materials for manufacturing different components with required properties. The major applications of these composites are in electronic industry, automobile industry and aerospace industry. In this work, a glass fibre reinforced polymer (GFRP) composite is fabricated using epoxy polymer Araldite LY556 matrix reinforced with 12 layers of glass fibers and properties such as tensile strength and hardness are measured. Generally, drilling of GFRP composites is difficult unlike traditional materials due to anisotropic nature. Hence, authors made an attempt to carry out the experimental study on drilling of GFRP composites and optimize the parameters based on material removal rate and delamination damage using Taguchi method. © 2016 IEEE.