Department of Electrical Engineering

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

Energy efficiency has become the new performance criterion in this era of pervasive embedded computing; thus, accelerator-rich multi-processor system-on-chips are commonly used in embedded computing hardware. Once computationally intensive machine learning applications gained much traction, they are now deployed in many application domains due to abundant and cheaply available computational capacity. In addition, there is a growing trend toward developing hardware accelerators for machine learning applications for embedded edge devices where performance and energy efficiency are critical. Although these hardware accelerators frequently use floating-point operations for accuracy, reduced-width floating-point formats are also used to reduce hardware complexity; thus, power consumption while maintaining accuracy. Vectorization concepts can also be used to improve performance, energy efficiency, and memory bandwidth. We propose the design of a vectorized floating-point adder/subtractor that supports arbitrary length floating-point formats with varying exponent and mantissa widths in this article. In comparison to existing designs in the literature, the proposed design is 2.57x area- and 1.56x power-efficient, and it supports true vectorization with no restrictions on exponent and mantissa widths.

World University root node

ACM TRANSACTIONS ON DESIGN AUTOMATION OF ELECTRONIC SYSTEMS

Design of Synthesis-time Vectorized Arithmetic Hardware for Tapered Floating-point Addition and Subtraction

Resource-constrained, wearable and continuous health-monitoring devices require automatic electrocardiogram (ECG) signal quality assessment (SQA) (ECG-SQA) to reduce false alarms and optimize energy consumption. In this paper, the ECG signals are classified as clean and noisy. The performance and computational complexity of convolutional neural network (CNN) based ECG-SQA models are compared for the derivative of ECG (dECG) and Fourier magnitude spectrum of ECG as input. We have evaluated 19 dECG-based and 16 Fourier magnitude spectrum-ECG-based CNNs to find the optimal CNN for ECG-SQA. The CNNs are analyzed for kernel sizes 3 × 1, 4×1, 5 × 1 and 6×1; convolution layers 2, 3 and 4; dense layers 3, 4 and 5; exponential linear unit (ELU) activation function. The proposed CNN-based SQA method with Fourier magnitude spectrum-based ECG-SQA is lightweight and less computationally complex, with a model size of 852 kB and 67,697 parameters. The robustness of the CNN-based ECG-SQA method is tested with two unseen datasets, such as the PhysioNet/Computing in Cardiology Challenge 2011 (PCCC2011) database and the St. Petersburg Institute of Cardiological Technics (INCART) 12-lead arrhythmia database. The method achieved the sensitivity of 99.30% and 98.41%, respectively and specificity of 95.40% and 99.3%, respectively, with unseen PCCC2011 and INCART datasets. For the assessment of 5 s ECG signal, the proposed method has a processing time of 62.6±12.6 ms. © 2023 IEEE.

ICSIMA 2023 - 9th IEEE International Conference on Smart Instrumentation, Measurement and Applications

A Comparative Study of Derivative and Fourier Magnitude Spectrum Based CNN Models for Automatic ECG Signal Quality Assessment

Continuous measurement of oxygen saturation (SpO2) and pulse rate (PR) is most essential for diagnosis of cardiovascular and chronic pulmonary diseases. Affordable miniaturized devices with limited battery capacity highly demand energy-efficient continuous vital sign measurement for long-term health and wellness monitoring. In this paper, we present compressed sensing (CS) based SpO2 and PR estimation method by directly processing compressive PPG measurements obtained by using deterministic binary block diagonal (DBBD) sensing matrix. The performance of CS-PPG is studied by using four SpO2 estimation equations with the duration of 2 and 3 seconds PPG signals. Results show that linear equation provides accurate SpO2 measurement with less estimation error in terms of mean absolute error (MAE) of 0.69% and Bland Altman ratio (BAR) of 0.94% as compared to that of the quadratic equation based SpO2 measurement. Evaluation results of PR estimation approach show that the average magnitude difference function (AMDF) based approach had the best estimation error range (EER) metric having more number of PPG segments with zero error and error less than 5 bpm and MAE of 2.94 bpm for red-wavelength PPG as compared to the fast Fourier transform (FFT) based PR estimation approach having MAE of 3.72 bpm for 10 second PPG segment. From this study, the proposed CS-PPG based SpO2 and PR estimation method can reduce computational load and overall energy consumption by a factor of 5 as compared to the uncompressed PPG based measurement method. © 2023 IEEE.

Compressed Sensing Based SpO2 and PR Estimation for Improving Resource Utilization Efficiency of Wearables in IoMT Applications

Due to the high demands of tiny, compact, lightweight, and low-cost photoplethysmogram (PPG) monitoring devices, these devices are resource-constrained including limited battery power. Consequently, it highly demands frequent charge or battery replacement in the case of continuous PPG sensing and transmission. Further, PPG signals are often severely corrupted under ambulatory and exercise recording conditions, leading to frequent false alarms. In this paper, we propose a unified quality-aware compression and pulse-respiration rates estimation framework for reducing energy consumption and false alarms of wearable and edge PPG monitoring devices by exploring predictive coding techniques for jointly performing signal quality assessment (SQA), data compression and pulse rate (PR) and respiration rate (RR) estimation without the use of different domains of signal processing techniques that can be achieved by using the features extracted from the smoothed prediction error signal. By using the five standard PPG databases, the performance of the proposed unified framework is evaluated in terms of compression ratio (CR), mean absolute error (MAE), false alarm reduction rate (FARR), processing time (PT) and energy saving (ES). The compression, PR, RR estimation, and SQA results are compared with the existing methods and results of uncompressed PPG signals with sampling rates of 125 Hz and 25 Hz. The proposed unified quality-aware framework achieves an average CR of 4%, SQA (Se of 92.00%, FARR of 84.87%), PR (MAE: 0.46 ±1.20) and RR (MAE: 1.75 (0.65-4.45), PT (sec) of 15.34 ±0.01) and ES of 70.28% which outperforms the results of uncompressed PPG signal with a sampling rate of 125 Hz. Arduino Due computing platform-based implementation demonstrates the real-time feasibility of the proposed unified quality-aware PR-RR estimation and data compression and transmission framework on the limited computational resources. Thus, it has great potential in improving energy-efficiency and trustworthiness of wearable and edge PPG monitoring devices. © 2013 IEEE.

IEEE Access

Unified Quality-Aware Compression and Pulse-Respiration Rates Estimation Framework for Reducing Energy Consumption and False Alarms of Wearable PPG Monitoring Devices

The common-mode (CM) noise is generally addressed using a CM choke due to its simple design and reliability. However, the performance of the CM choke degrades and the CM impedance starts decreasing after the resonant frequency. Hence, tuning the CM impedance of the CM choke is widely adapted by inserting an auxiliary winding on the CM choke core to alter the resonant frequency. Thus, in this paper, the analytical approach to estimate the CM impedance of the tunable CM choke with known external circuit parameters connected to the auxiliary winding terminals and vice-versa is presented. In addition, the estimated CM impedance profiles and the auxiliary winding parameters are simulated in MATLAB/Simulink and are validated through experimentation. © 2023 IEEE.

2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023

Analytical Modeling of Three-Winding Tunable Common-Mode Choke

Heart rate variability (HRV) denotes the natural variation in the time gaps between the consecutive heartbeats due to physiological changes. The HRV analysis is useful in the diagnosis of different clinical and functional conditions. Computation of HRV parameters from high-resolution electrocardiogram (ECG) signals on resource-constrained wearable internet of things (IoT) devices poses challenges due to the substantial computational load and increased energy consumption. Compressed ECG sensing for R-peak detection emerges as an approach for fast processing. Frequency domain HRV (FDHRV) analysis based on the power spectrum is capable for quantifying various clinical and functional conditions through the examination of ultra-short-term (1 minute) segments of ECG data. This paper presents a comparative study of FDHRV analysis using compressed ECG sensing for R-peak detection and FDHRV analysis through conventional high resolution R-peak detection. For this comparative study, 48 ECG records of MIT-BIH arrhythmia database and 18 ECG records of MIT-BIH normal sinus rhythm (NSR) database are used. During comparative FDHRV analysis, we have observed an average deviation of 0.003 Hz in respective band-wise peak frequencies. For both databases, the observed peak-frequency locations are 99.25% and 99.23% similar, respectively. Also, compared methods have provided relative power with 99.64% and 94.68% similar values for both databases, respectively. These findings support the suitability of compressed ECG sensing based FDHRV analysis for fast health monitoring using an ultra-short duration ECG signal. © 2023 IEEE.

Power Spectral Analysis of Heart Rate Variability using Compressed ECG Sensing for Energy-Constrained Fast Health Monitoring

Big Data Analytics For Synchrophasors (BigSync) is an offline engineering analysis software solution developed at Indian Institute of Technology Palakkad. The software solution allows the user to do post-event analysing utilising synchrophasor measurements of the power system. The software package includes applications such as signal trending, angle difference monitoring, event detection, transient stability prediction, fault diagnosis and inertia distribution monitoring. This paper details the applicability of offline engineering software solutions in operationalizing wide area measurement system(WAMS) solutions in the control room. Further, the applications integrated in BigSync are also demonstrated. © 2023 IEEE.

5th International Conference on Power, Control and Embedded Systems, ICPCES 2023

BigSync: Big Data Analytics For Synchrophasors

The proposed work depicts a compact Octuple Ridge Conical Horn (ORCH) antenna that can be utilized for Microwave Imaging (MI). The put forward ORCH is appended with a hemispherical dielectric lens to improve its gain and radiation properties. The proposed antenna achieves a bandwidth from 3 - 20 GHz with good return loss performance. The designed antenna obtains a maximum realized gain of 27.85 dBi at 20 GHz. The usage of the ORCH for MI applications is tested by checking its Specific Absorption Rate (SAR) readings in the Computer Simulation Technology (CST) simulation software. It is found that the SAR value complies with the international regulations. © 2023 IEEE.

2nd International Conference on Wireless, Antenna and Microwave Symposium, WAMS 2023

Octuple Ridge Conical Horn Antenna with Hemispherical Dielectric Lens Loading for Biomedical Imaging Applications

This work proposes a novel wideband reconfigurable via-less Frequency Selective Surface (FSS) based linear-circular, linear-cross polarizer in both reflection and transmission modes. The design consists of top and bottom FSSs on either side of the Taconic TLY-5 substrate. PIN diodes mounted on the back FSS turn the polarizer transmissive and reflective in different states. For a linearly polarized wave incidence, the transmitted wave would be circularly polarized with a 3 dB Axial Ratio (AR) from 8.03-16.30 GHz (67.98&#x0025;) and 30.05-31.70 GHz (5.54&#x0025;). In reflection mode, this design performs linear-circular conversion in 9.38-10.49 GHz (11.17&#x0025;) and 15.14-30.27 GHz (66.64&#x0025;). On the other hand, the unitcell behaves as a reflective linear-cross converter with a minimum 90&#x0025; Polarization Conversion Ratio over 11.43-13.43 GHz (16.09&#x0025;) and 31.67-34 GHz (7.10&#x0025;). Multiple surface plasmonic resonances are the reason behind the different conversions. The unitcell periodicity (0.150&#x03BB;L&#x00D7; 0.123&#x03BB;L) is the compact and low-profile thickness of 0.043&#x03BB;L. The proposed work&#x0027;s novelty lies in the miniaturized architecture of the linear-circular polarization converter, covering the lower frequency (X&#x002F;Ku) in transmission mode and higher frequency (Ku&#x002F;K) in the reflection mode, which made this polarizer a suitable candidate for vehicular satellite communication applications. IEEE

IEEE Transactions on Vehicular Technology

Wideband Via-less Reconfigurable Reflection and Transmission Linear-Circular/ Linear-Cross Polarizer for Vehicular Satellite Communication Applications

This work proposes a novel, extremely miniaturized wideband linear-circular and linear-cross metasurface-enabled reflective polarizer. This design comprises a Meander-line structure with horizontal dipoles as the top frequency selective surface, printed on a 1 mm thin-grounded FR-4 substrate. The x/y-polarized incident electromagnetic wave is converted as circularly polarized from 10.60 to 10.92 GHz (LHCP/RHCP), 12.12 to 17.32 GHz (RHCP/LHCP) and 22.72 to 37.76 GHz (LHCP/RHCP) during reflection with 2.97, 35.33 and 49.74% Fractional Bandwidth (FBW). In addition, this design shows linear-cross conversion with a minimum 90% polarization conversion ratio from 11.41 to 12, 19.01 to 22.34 and 40.74 to 46.82 GHz with an FBW of 5.04, 16.11 and 13.89%. The device performance is considerably stable under different oblique incidences and the polarizer's unitcell is compact with a structural periodicity of 0.089 × 0.064 and ultra-thin low-profile substrate thickness of 0.035λL. The proposed prototype is fabricated and the measured results are in good agreement with the simulated one. This article also mentions how this polarizer could be tuned for dual-band K- and Ka-band satellite applications. The authors believe that the design's novelty lies in the multiband conversion with circular-polarization orthogonality, a highly miniaturized unitcell's volume of 0.199 /1000 and better angular stability made this design a potential candidate for real-time satellite applications. Copyright © Indian Institute of Technology Palakkad, 2023. Published by Cambridge University Press in association with the European Microwave Association.