Dr. Vithalani Chandulal H

@ldce.ac.in

Retired Professor, Electronics and Communication Engineering
Retired Professor, Electronics and Communication Engineering

Dr. Vithalani Chandulal H


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https://researchid.co/chvithalani
I am retired professor and was working with technical education department, Gujarat State in Electronics and Communication Engineering department.

EDUCATION

Ph.D. (Electronics Engineering)

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering
19

Scopus Publications

184

Scholar Citations

7

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • Energy Harvesting in Implantable Bioelectronics: A Self-Sustained Approach for Long-Term Monitoring
    Rashmin S Tanna, Paresh P Kotak, C.H. Vithalani
    Proceedings of 8th International Conference on Trends in Electronics and Informatics Icoei 2025, 2025
    Implantable bioelectronics are engrossed in modern healthcare where they permit continuous monitoring and treatment of chronic diseases. Unfortunately, these devices all rely on traditional battery powered systems that need replacing surgically, and this is expensive and uncomfortable for the patient. To solve this problem, this study proposes a self-sustained energy management approach based on energy harvesting with an AI driven CNN application with MLP as the architecture. Piezoelectric and thermoelectric generators exploit the body heat and motion to harvest energy and store the converted energy in capacitors and supercapacitors for continuous operation. The real time sensor data is fed into the CNN component, which extracts relevant features and identifies energy consumption patterns; FNN identifies the future energy requirements and allocates energy optimally. A method is created to train and validate the model using an IEEE DataPort dataset including sensor readings, power usage metrics, and energy harvesting patterns. Results from the evaluation show that the CNN FNN prediction model achieves very good prediction accuracy, improves energy harvest efficiency and power consumption up by 20-30% for prolonging device lifespan. It is then compared with traditional battery powered and passive storage methods as the latter is found to be comparatively inferior to this AI based approach with regards to reduced maintenance and increased reliability. This work makes way for the next generation of autonomous implantable bioelectronics that operate well without frequent external interventions through allowing self-sustaining functionality. Real world hardware implementation, use of alternative energy harvesting sources, as well as refinement of the AI models towards higher accuracy and adaptability in dynamic patient conditions will be future subjects for work.
  • Hybrid MNN-CNN Data Fusion and Energy Harvesting Techniques in MEMS-based Smart Healthcare Sensors
    Rashmin S Tanna, Paresh P Kotak, C.H. Vithalani
    Proceedings of the 7th International Conference on Intelligent Sustainable Systems Iciss 2025, 2025
    Implementing advanced data fusion and energy harvesting mechanisms in MEMS-based wearable smart healthcare sensors is important for improving continuous health monitoring to provide real-time information on one or the other physiological indicator. However, general pre-existing studies possess the following challenges when incorporating data complexity, multi-sensor data, and controlling power consumption bearing the importance of lifetime for sensors. To overcome such challenges, this study presents a new approach of using an MNN-CNN hybrid to perform data fusion and energy harvesting mechanisms to increase the lifespan of the sensors. The MNN divides the multi-sensor data into several sub-regions of simpler data processing and the CNN focuses on deeper feature extraction to detect critical health related patterns. This hybrid model increases the detection accuracy and reliability, where the detecting accuracy is 99.4% compared to the conventional models. The implementation of the proposed method is in Python, allowing for high-speed data analysis and model fine-tuning. These high accuracy rates show the liveness and practical applicability of the proposed model in real life MEMS healthcare monitoring to make it far more scalable with very minimal energy requirements, quite applicable for real-time health monitoring analysis. Future work on this model will involve optimizing and implementing it for real-time use on wearable electronics issues of data protection alongside with a vision to enhance smart health-care engineering.
  • INDUSTRIAL INTELLIGENCE FOR SMART CITIES: THE ROLE OF AI AND IOT IN TRANSFORMING URBAN MOBILITY AND INFRASTRUCTURE
    Janak TRIVEDI, Mandalapu Sarada DEVI, Chandresh VITHALANI, Kiran PARMAR, Dhara DAVE
    Scientific Journal of Silesian University of Technology Series Transport, 2025
    This review synthesizes research on AI and IoT in urban mobility, focusing on traffic management, public transportation systems, and autonomous vehicles to address escalating urban congestion, environmental impact, and mobility demands. This review aimed to evaluate AI and IoT applications in traffic flow optimization, benchmark integration in public transit, identify autonomous vehicle frameworks, compare predictive models and sensor networks, and analyze adoption challenges. A systematic analysis of global empirical, simulation, and theoretical studies was conducted, emphasizing technological convergence, performance outcomes, data utilization, and barriers. The findings reveal that AI-driven predictive models combined with IoT sensor networks significantly improve traffic efficiency and reduce emissions, whereas AI-IoT integration enhances public transit reliability through predictive maintenance and dynamic scheduling. Autonomous vehicles, supported by IoT-enabled communication and AI decision-making, demonstrate the potential for safety and sustainability gains but face regulatory, infrastructural, and acceptance challenges. Advanced machine learning techniques optimize real-time data analytics but encounter scalability and explainability limitations. Collectively, these findings underscore the transformative potential of AI-IoT in urban mobility, contingent on addressing privacy, infrastructure, and social factors. The synthesis highlights the need for interdisciplinary approaches to advance scalable, secure, and user-centered AI-IoT urban mobility solutions that inform future research and practical implementations.
  • A Novel Morphological Feature Extraction Approach for ECG Signal Analysis Based on Generalized Synchrosqueezing Transform, Correntropy Function and Adaptive Heuristic Framework in FPGA
    Miloni M. Ganatra, Chandresh H. Vithalani
    Journal of Circuits Systems and Computers, 2022
    Nowadays, a computer-aided diagnosis system is required to monitor the cardiac patients continuously and detecting the heart diseases automatically. In this paper, a new field programmable gate array-based morphological feature extraction approach is proposed for electrocardiogram signal analysis. The proposed architecture is mainly based on the Generalized Synchrosqueezing transform but a detrended fluctuation analyzer is applied in the reconstruction stage for capturing the maximum information of QRS complexes and P-waves by eliminating a set of noisy intrinsic modes. Then, a correntropy envelope is determined from the QRS enhanced signal for localizing the QRS region accurately. Also, an adaptive heuristic framework is introduced to detect the true P-wave from the P-wave enhanced reconstructed signal by analyzing both the positive and negative amplitudes. In addition, a root mean square Error estimation-based adaptive thresholding approach is used to estimate the T-wave after removing the P-QRS complexes. The proposed architecture has been implemented on field programmable gate array using the Xilinx Vertex 7 platform. The performance of the proposed architecture is validated by performing a comparative study between the resultant performances and those attained with state-of-the-art feature descriptors, in terms of Sensitivity, accuracy, positive prediction, error rate and field programmable gate array resources estimation. The proposed sensitivity, accuracy and positive prediction are 99.84%, 99.85% and 99.86% for QRS detection approach. The proposed sensitivity, accuracy and positive prediction are 99.45%, 99.23% and 99.78% for P-wave detection approach. The proposed sensitivity, accuracy and positive prediction are 99.58%, 99.65% and 100% for T-wave detection approach. The simulation results show that the proposed architecture overtakes existing designs and minimizes hardware complexity, which proves the suitability of this approach on real-time applications of electrocardiogram signals.
  • Classification of lower limb rehabilitation exercises with multiple and individual inertial measurement units
    Rashmin S. Tanna, Chandulal H. Vithalani
    Indonesian Journal of Electrical Engineering and Computer Science, 2022
    Straight leg raise rehabilitation exercises (for both lying and seated position) for lower limb injuries play a critical role in terms of stress on joints after the injury. The primary objective of the paper is to find how accurately and efficiently a single and a two IMU sensor-based system could classify SSLR (Seated straight leg raise) and LSLR (Lying straight leg raise) exercises using machine learning. Inertial Measurement Units (IMUs) that include accelerometer and gyroscope were calibrated and tested, individual and combined, for classified seating as well as lying exercise and for different demanded personalities. Individual IMUs achieved about 96 % accuracy in binary classification. However, the combined (two) IMUs achieved about 96.8 % accuracy. The merits of the proposed IMU based sensor system are that it is easy to install, cost effective and very useful for telemedical operations in pandemic situations like COVID19. On the basis of these results, it could be concluded that the accuracy of a single IMU sensor system and a two IMU sensor-based system is approximately 96% and both were efficiently able to classify SSLR and LSLR exercises as well as identify the individual performing the exercise.
  • Correction to: FPGA Design of a Variable Step-Size Variable Tap Length Denlms Filter with Hybrid Systolic-Folding Structure and Compressor-Based Booth Multiplier for Noise Reduction in Ecg Signal (Circuits, Systems, and Signal Processing, (2022), 41, 6, (3592-3622), 10.1007/s00034-021-01933-0)
    Miloni M. Ganatra, Chandresh H. Vithalani
    Circuits Systems and Signal Processing, 2022
  • FPGA Design of a Variable Step-Size Variable Tap Length Denlms Filter with Hybrid Systolic-Folding Structure and Compressor-Based Booth Multiplier for Noise Reduction in Ecg Signal
    Miloni M. Ganatra, Chandresh H. Vithalani
    Circuits Systems and Signal Processing, 2022
  • A literature review: various learning techniques and its applications for eye disease identification using retinal images
    Vipul Rajyaguru, Chandresh Vithalani, Rohit Thanki
    International Journal of Information Technology Singapore, 2022
  • Outdoor object detection for surveillance based on modified GMM and Adaptive Thresholding
    Navneet S. Ghedia, C. H. Vithalani
    International Journal of Information Technology Singapore, 2021
  • Optimization in cooperative spectrum sensing in cognitive radio using jaya algorithm
    Journal of Advanced Research in Dynamical and Control Systems, 2019
  • Active inductor designs for RF CMOS receiver front - End
    International Journal of Applied Engineering Research, 2016
  • On performance analysis of OSTBC-MIMO systems for audio [mp3] transmission in rayleigh fading environments
    Paresh M. Dholakia, Sanjay Kumar, C.H. Vithlani, Mitesh Solanki
    Proceedings 2014 IEEE International Conference on Advances in Communication and Computing Technologies Icacact 2014, 2015
  • Performance Analysis of 4 × 4 and 8 × 8 MIMO System, to Achieve Higher Spectral Efficiency in Rayleigh and Rician Fading Distributions
    Paresh M. Dholakia, Sanjay Kumar, C. H. Vithalani
    Wireless Personal Communications, 2014
  • VLSI-oriented lossy image compression approach using DA-based 2D-discrete wavelet
    International Arab Journal of Information Technology, 2014
  • Notice of Removal: Distinguishing congestion loss from random loss on wireless erroneous links to improve performance of wireless TCP - SACK
    R.D. Mehta, C.H. Vithalani
    Proceedings International Conference on Communication Systems and Network Technologies Csnt 2012, 2012
  • Wideband local oscillator design for wideband transceivers
    Mehul R. Naik, C H Vithalani
    2011 IEEE International RF and Microwave Conference Rfm 2011 Proceedings, 2011
  • FPGA realization of DA-based 2D-discrete wavelet transform for the proposed image compression approach
    D. U. Shah, C. H. Vithlani
    2011 Nirma University International Conference on Engineering Current Trends in Technology Nuicone 2011 Conference Proceedings, 2011
  • A novel approach to design and implement Differential Time Lapse Video in real time application
    Dipesh G. Kamdar, C. H. Vithalani
    2011 International Conference on Emerging Trends in Electrical and Computer Technology Icetect 2011, 2011
  • Designing wideband voltage controlled oscillators for software-defined radio
    Mehul R. Naik, C H Vithalani
    2010 IEEE International Conference on Electronics Circuits and Systems Icecs 2010 Proceedings, 2010

RECENT SCHOLAR PUBLICATIONS

  • Smart Parking System for Single and Multiple Video Cameras using SBMA & Parking Slot Selection
    J Trivedi, C Vithalani, K Parmar, D Dhara
    Archiwum Motoryzacji 111 (1), 75-96 , 2026
    2026
  • Energy Harvesting in Implantable Bioelectronics: A Self-Sustained Approach for Long-Term Monitoring
    RS Tanna, PP Kotak, CH Vithalani
    2025 8th International Conference on Trends in Electronics and Informatics … , 2025
    2025
  • Hybrid MNN-CNN Data Fusion and Energy Harvesting Techniques in MEMS-based Smart Healthcare Sensors
    RS Tanna, PP Kotak, CH Vithalani
    2025 7th International Conference on Intelligent Sustainable Systems (ICISS … , 2025
    2025
  • INDUSTRIAL INTELLIGENCE FOR SMART CITIES: THE ROLE OF AI AND IOT IN TRANSFORMING URBAN MOBILITY AND INFRASTRUCTURE
    J TRIVEDI, MS DEVI, C VITHALANI, K PARMAR, D DAVE
    Journal of Silesian University of Technology. Series Transport 129, 261-281 , 2025
    2025
  • A novel morphological feature extraction approach for ECG signal analysis based on generalized synchrosqueezing transform, correntropy function and adaptive heuristic framework …
    MM Ganatra, CH Vithalani
    Journal of Circuits, Systems and Computers 31 (18), 2250312 , 2022
    2022
    Citations: 7
  • Classification of lower limb rehabilitation exercises with multiple and individual inertial measurement units
    RS Tanna, CH Vithalani
    Indonesian Journal of Electrical Engineering and Computer Science 28 (2 … , 2022
    2022
    Citations: 4
  • FPGA design of a variable step-size variable tap length denlms filter with hybrid systolic-folding structure and compressor-based booth multiplier for noise reduction in ECG signal
    MM Ganatra, CH Vithalani
    Circuits, Systems, and Signal Processing 41 (6), 3592-3622 , 2022
    2022
    Citations: 18
  • A literature review: various learning techniques and its applications for eye disease identification using retinal images
    V Rajyaguru, C Vithalani, R Thanki
    International Journal of Information Technology 14 (2), 713-724 , 2022
    2022
    Citations: 43
  • Object Tracking
    N Ghedia, C Vithalani, AM Kothari, RM Thanki
    Moving Objects Detection Using Machine Learning, 65-77 , 2022
    2022
  • Background Modeling
    N Ghedia, C Vithalani, AM Kothari, RM Thanki
    Moving Objects Detection Using Machine Learning, 33-64 , 2022
    2022
  • Existing Research in Video Surveillance System
    N Ghedia, C Vithalani, AM Kothari, RM Thanki
    Moving Objects Detection Using Machine Learning, 11-32 , 2022
    2022
    Citations: 1
  • Moving Objects Detection Using Machine Learning
    N Ghedia, C Vithalani, AM Kothari, RM Thanki
    Springer International Publishing , 2022
    2022
    Citations: 8
  • Summary of the Book
    N Ghedia, C Vithalani, AM Kothari, RM Thanki
    Moving Objects Detection Using Machine Learning, 79-80 , 2022
    2022
  • Optimization of Spectrum Sensing Technique in Cognitive Radio
    AA Vithalani, CH Vithalani
    Gujarat Technological University , 2021
    2021
    Citations: 4
  • Outdoor object detection for surveillance based on modified GMM and adaptive thresholding
    NS Ghedia, CH Vithalani
    International Journal of Information Technology 13 (1), 185-193 , 2021
    2021
    Citations: 21
  • Critical Comparative Analysis of Object Detection and Tracking Algorithms
    N Ghedia, C Vithalani, A Kothari
    AEGAEUM Journal , 2020
    2020
  • A comprehensive Survey: Background Estimation and Motion Detection Approaches
    N Ghedia, C Vithalani, A Kothari
    GIS Science Journal , 2020
    2020
  • Implementation of Foreground Detection Algorithm Using Modified GMM for Outdoor Surveillance
    N Ghedia, C Vithalani, A Kothari
    GIS Science Journal , 2020
    2020
  • 5. Intelligent approach for retinal disease identification
    VC Rajyaguru, CH Vithalani, RM Thanki
    Intelligent Decision Support Systems: Applications in Signal Processing 4, 99 , 2019
    2019
  • Integration of BCI and Eye Gaze Tracker to C ontrol M ouse
    HM Mehta, MP Patel, CH Vithalani
    2018

MOST CITED SCHOLAR PUBLICATIONS

  • A literature review: various learning techniques and its applications for eye disease identification using retinal images
    V Rajyaguru, C Vithalani, R Thanki
    International Journal of Information Technology 14 (2), 713-724 , 2022
    2022.0
    Citations: 43
  • Outdoor object detection for surveillance based on modified GMM and adaptive thresholding
    NS Ghedia, CH Vithalani
    International Journal of Information Technology 13 (1), 185-193 , 2021
    2021.0
    Citations: 21
  • FPGA design of a variable step-size variable tap length denlms filter with hybrid systolic-folding structure and compressor-based booth multiplier for noise reduction in ECG signal
    MM Ganatra, CH Vithalani
    Circuits, Systems, and Signal Processing 41 (6), 3592-3622 , 2022
    2022.0
    Citations: 18
  • VLSI-oriented lossy image compression approach using DA-based 2D-discrete wavelet.
    D Shah, C Vithlani
    Int. Arab J. Inf. Technol. 11 (1), 59-68 , 2014
    2014.0
    Citations: 15
  • Efficient implementations of discrete wavelet transforms using fpgas
    DU Shah, CH Vithlani
    International Journal of Advances in Engineering & Technology 1 (4), 100 , 2011
    2011.0
    Citations: 14
  • Application of combined TOPSIS and AHP method for spectrum selection in cognitive radio by channel characteristic evaluation
    AA Vithalani, CH Vithalani
    International journal of electronics and communication engineering 10 (2), 71-79 , 2017
    2017.0
    Citations: 12
  • Moving Objects Detection Using Machine Learning
    N Ghedia, C Vithalani, AM Kothari, RM Thanki
    Springer International Publishing , 2022
    2022.0
    Citations: 8
  • A novel morphological feature extraction approach for ECG signal analysis based on generalized synchrosqueezing transform, correntropy function and adaptive heuristic framework …
    MM Ganatra, CH Vithalani
    Journal of Circuits, Systems and Computers 31 (18), 2250312 , 2022
    2022.0
    Citations: 7
  • Over-under voltage protection of electrical appliances
    CH Vithalani
    Electronics for You. Com, March 1 , 2017
    2017.0
    Citations: 7
  • A novel approach for monocular 3d object tracking in cluttered environment
    N Ghedia, C Vithalani, A Kothari
    International Journal of Computational Intelligence Research , 2017
    2017.0
    Citations: 5
  • Classification of lower limb rehabilitation exercises with multiple and individual inertial measurement units
    RS Tanna, CH Vithalani
    Indonesian Journal of Electrical Engineering and Computer Science 28 (2 … , 2022
    2022.0
    Citations: 4
  • Optimization of Spectrum Sensing Technique in Cognitive Radio
    AA Vithalani, CH Vithalani
    Gujarat Technological University , 2021
    2021.0
    Citations: 4
  • Compressive Spectrum Sensing: An Overview
    CA Patel, CH Vithalani
    International Journal of Innovative Research in Electronics and … , 2014
    2014.0
    Citations: 4
  • FPGA realization of DA-based 2D-discrete wavelet transform for the proposed image compression approach
    DU Shah, CH Vithlani
    2011 Nirma University International Conference on Engineering, 1-6 , 2011
    2011.0
    Citations: 4
  • Active Inductor Designs for RF CMOS Receiver Front-End
    RK Lamba, CH Vithalani
    International Journal of Applied Engineering Research 11 (2), 904-908 , 2016
    2016.0
    Citations: 3
  • Performance Analysis of and MIMO System, to Achieve Higher Spectral Efficiency in Rayleigh and Rician Fading Distributions
    PM Dholakia, S Kumar, CH Vithalani
    Wireless personal communications 79 (1), 687-701 , 2014
    2014.0
    Citations: 3
  • A novel approach to design and implement Differential Time Lapse Video in real time application
    DG Kamdar, CH Vithalani
    2011 International Conference on Emerging Trends in Electrical and Computer … , 2011
    2011.0
    Citations: 3
  • Distinguishing congestion loss from random loss on wireless erroneous links to improve performance of wireless TCP-SACK
    RD Mehta, CH Vithalani
    Communication Systems and Network Technologies, International Conference on … , 2012
    2012.0
    Citations: 2
  • Dual layer data hiding using cryptography and steganography
    DG Kamdar, D Patira, DCH Vithalani
    International Journal of Scientific Engineering and Technology (ISSN: 2277 … , 0
    Citations: 2
  • Existing Research in Video Surveillance System
    N Ghedia, C Vithalani, AM Kothari, RM Thanki
    Moving Objects Detection Using Machine Learning, 11-32 , 2022
    2022.0
    Citations: 1