Dr, Balambigai S

Scopus Publications

RF-enabled embedded sanitation system for railway
Kalaiselvi T. C., Jeevanantham A., Sekaran B. S., Prasanth N., Balambigai Subramanian
Proceedings of SPIE the International Society for Optical Engineering, 2026
With the rapid growth of population and the increasing demand for efficient transportation, automation has become essential in enhancing passenger comfort and hygiene—particularly in railway systems. While modern trains such as India’s Vande Bharat Express have adopted advanced technologies, toilet automation remains an area with significant scope for improvement. This paper proposes a next-generation smart train toilet system that integrates automated flushing, intelligent water management, and touch-free operation to maintain a clean and hygienic environment throughout the journey. The system employs advanced sensors and controllers to optimize cleaning cycles, minimize water wastage, and ensure consistent sanitation without manual intervention. Additionally, an odor-control and fragrance-dispensing unit is incorporated to improve passenger experience. By combining automation, sustainability, and user-centric design, this solution aims to set a new benchmark for hygiene standards in railway travel.
INVESTIGATION AND DEVELOPMENT OF A MULTILEVEL INVERTER WITH A 29-LEVEL REDUCED SWITCH COUNT
Murugesan M, Suganya N, Sivaranjani S, Kesavan T, Bharani Prakash T, Sarathkumar D, Anand K, Balambigai S
Kufa Journal of Engineering, 2026
A novel multilevel inverter design for electric vehicle applications is presented in this research. In order to generate the necessary twenty-nine levels of output voltage and current waveforms, this multilevel inverter is developed using ten power switches and four distinct asymmetrical DC sources. Pulse width modulation is the most often utilized control method in multilevel inverters. This multilevel inverter uses sinusoidal pulse width modulation to remove low order harmonics. MATLAB is used for simulation, and a resistive load and resistive-inductive load is used for testing. A 210V, single phase, 29 level proposed architectural prototype uses MOSFETs as switching devices. In the hardware configuration, IRF840 MOSFETs are used. For inverter switches, the Ardiuno micro controller generates the gate signal. To achieve a twenty-nine level output waveform, typical multi-level inverters require a greater number of power components, which raises switching losses, costs, and harmonic distortion. By using 10 switches, the suggested inverter greatly reduces switching losses, low order harmonics, and switching costs, which in turn lowers overall harmonic distortions
INVESTIGATION OF MODIFIED NEW HYBRID MULTILEVEL INVERTER TOPOLOGY WITH REDUCED SWITCHES
Murugesan MANIVEL, Kesavan TAMILSELVEN, Suganya NAGULSAMY, Lakshmanan PALANI, Brindha SAMARASAM, Anand KARUPPANNAN, Jayanthi RAJADURAIPANDI, Balambigai SUBRAMANIAN
Advances in Electrical and Electronic Engineering, 2025
Refractive Index Biosensor–Based Detection of Mycobacterium Tuberculosis Using Sea Lion Political Optimizer and Deep Learning
V. K. Senthil Ragavan, N. S. Nithya, Anantharamaiah Vengala, Balambigai Subramanian, C. Ambhika
Plasmonics, 2025
An Efficient Radix-8 Factored Systolic Array for Machine Learning Acceleration
Agasthiya S, Balambigai S, Sarankumar R
Proceedings of 5th International Conference on Trends in Material Science and Inventive Materials Ictmim 2025, 2025
This research shows that there is a lot of room for improvement at the logic level, even if SAs have a common structure, and it suggests two new SA that use factoring and radix-8 multipliers. Eliminating shared hard-multiple generation and booth encoding across all Processing Elements (PEs) may assist to reduce the overall size and time of the SA. The proposed method employs a parallel prefix adder to finish the addition of a radix-8 multiplier at each processing element. We refer to this design as Factored Systolic Arrays (FSA). Furthermore, we use Kogge-stone (KS), a parallel prefix two-operand adder that significantly decreases critical route time while requiring extra hardware.It has low gate complexity and high performance. In comparison to the usual radix-4 SA, the suggested FSA design reduces space, power consumption, and latency over a wide range of bit widths. Modelsim is used to conduct simulations of the suggested design, which was produced in Verilog HDL. Xilinx ISE is used to provide a comparative study of current and future techniques.
Lightweight Route Propagation Delays Based Attack Detection for Underwater Acoustic Networks
Gayathri M, Balambigai S, Sarankumar R
Proceedings 3rd International Conference on Artificial Intelligence and Machine Learning Applications Healthcare and Internet of Things Aimla 2025, 2025
A physical-layer security approach for generating sequences of random bits (keys) between two Underwater Acoustic Network (UWAN) devices (Alice and Bob); the key must be kept hidden from a non-UWAN passive Eavesdropper (Eve). A single physical device may launch a coordinated attack on the network or swap identities to undermine the detection process, resulting in a lack of responsibility in the network. In dynamic networks with burst traffic, when lengthy periods of calm are anticipated between data bursts, this multicast state maintenance adds a significant amount of communication, processing, and memory overhead that is not beneficial to the application. Thus, we created a stateless receiver-based multicast protocol that merely uses a list of multicast members' (e.g., sinks’) addresses encoded in packet headers to allow receivers to choose the optimal method to transmit multicast data. Our solution is based on measuring the propagation delay of the underwater acoustic channel over numerous UWAN hops: this exploits the unpredictability in the UWAN architecture and uses the slow sound propagation in water to its advantage against eavesdropping
Hierarchical Graph Neural Network Framework for Multi-Metric Performance Prediction in VLSI and NoC Architectures
Sivapriya A, Balambigai S, Sarankumar R
Proceedings of the 7th International Conference on Innovative Data Communication Technologies and Application Icidca 2025, 2025
Precise and effective power, delay, and throughput estimations are essential challenges in the design of VLSI and Network-on-Chip (NoC) architectures. Conventional SPICE and cycle-accurate simulations, though very precise, are computationally intensive and not well-suited for rapid design space search. This work presents a hierarchical Graph Neural Network (GNN) framework that models circuits as heterogeneous graphs augmented with structural and workload-oriented features. The framework combines graph attention, edge convolution layers, and residual connections to retain both local gate-level dependencies and global architectural behavior. A multi-task learning strategy allows for the concurrent prediction power, delay, and throughput, for consistency among correlated metrics. Simulation-based validation on ISCAS, RISC-V, and mesh-based NoC benchmarks proves that the proposed model provides prediction errors regularly below 3% relative to the ground truth. Moreover, once trained, the model offers near-instant inference, decreasing the evaluation time from hours to milliseconds. These results validate the efficiency of hierarchical GNNs as scalable surrogate models, facilitating correct and efficient performance estimations for next-generation VLSI systems.
A Survey on the performance based implementation of Advanced Encryption Standard
A. Vennila, S. Balambigai, M. Jinisha, V.N. Kavyashree, S. Kowshick
2025 International Conference on Computational Innovations and Engineering Sustainability Iccies 2025, 2025
A key component of contemporary cryptography, the Advanced Encryption Standard (AES) is widely used in applications needing effective and safe data encryption. This paper offers a thorough examination of the many approaches used to optimize throughput, power, area, and latency—the four main performance metrics in AES implementations. The paper emphasizes methods specific to hardware and software platforms, including pipeline topologies, S-Box transformations, and datapath optimizations. It illustrates the benefits and trade-offs of these approaches by examining numerous implementations in high-performance systems and the Internet of Things. This paper provides useful information for developing AES systems that balance resource and performance limitations while satisfying certain application needs.
Automated Detection of Alzheimer's Disease using Transfer Learning Algorithm
Vennila A, Prawinbabu S, Mukunthan A, Balambigai S, Nitheesvar P
Proceedings of 3rd International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2025, 2025
Alzheimer's is one of the primary causes of dementia, in which cognitive functioning deteriorates over time in aging individuals. Though early stages show some improvement, subsequent stages turn out to be irreversible. Early intervention during the mild cognitive impairment stage offers potential reversibility.The inception V3 is pre-trained model so time for training will be less over other models. Structural biomarkers, such as brain atrophy and accumulation of plaques and tangles, are directly related to the pathology of AD and can be viewed and captured using sophisticated imaging technologies like MRI and PET scans. This project seeks to create a predictive model for the diagnosis of Alzheimer's disease based on an MRI dataset of about 1,332 images. 982 images are utilized for training, and 350 for validation. The validation set comprises 100 images of mild dementia, 52 of moderate dementia, 98 of normal, and 100 of very mild dementia. In addition, the half-diagonal images of the dataset are composed of 77 mild, 49 moderate, 98 normal, and 86 very mild. The research uses transfer learning from the Inception V3 model, which is traditionally used to identify neurological diseases. The project is hoping to classify Alzheimer's disease into four classes: Normal, Very Mild Dementia, Mild Dementia, and Moderate Dementia with the aid of this model.
Detection of Brain Haemorrhage Using Convolutional Neural Network
Mahesh Prasanna K, Gadidala Venkatesh, Kandle Navaneetha, N. Naveena, F. Sheeja Mary, Balambigai Subramanian
2025 International Conference on Cognitive Computing in Engineering Communications Sciences and Biomedical Health Informatics Ic3ecsbhi 2025, 2025
Recently, deep learning calculations have been used for picture identification and detection, with excellent results in the pharmaceutical industry, such as clinical image research and analysis. For patients with brain haemorrhages, prompt diagnosis of the drain type and application of the appropriate therapy is essential to enhancing their chances of long-term survival. It has been shown that machine learning models are incredibly useful for assisting doctors in the management of intracranial haemorrhages. We evaluate a few 2-dimensional (2D) convolutional neural organisations (CNNs) in this research. In order to identify cerebral haemorrhage in computed tomography (CT) images, this research will use convolutional neural networks (CNN) and deep learning computations.
Hemoglux Monitor: A Non-Invasive Glucose, Hemoglobin, and Pulse Monitor
Balambigai S, Sarankumar R, Kapilesh Kumar S, Girinath S, Sangeeth S, Nitheesh Kumar N
Proceedings of 8th International Conference on Trends in Electronics and Informatics Icoei 2025, 2025
Novel Smart Mountable Cooling Pad Using Type C Silica Gel
Balambigai Subramanian, Arun Vignesh N, Sarankumar R, Sivaram Krishnan M, Vennila A, Prawinraj G
2025 International Conference on Computational Innovations and Engineering Sustainability Iccies 2025, 2025
Leveraging Hybrid CNN Architecture for Accurate Detection of Lung Diseases
Prawin Raj G, Bhuvaneshvari R, Prathish J, Mohanraj V, Aadhavan R, Balambigai S
2025 3rd International Conference on Advancements in Electrical Electronics Communication Computing and Automation Icaeca 2025, 2025
CENTRAL LINE ASSOCIATED BLOODSTREAM INFECTION PREDICTION USING DEEP ATTENTION NETS IN THE HEALTHCARE FIELD
Sushama C, Shaik Mohammad Rafee, Senthil Kumar A, Srilakshmi A, Subbulakshmi R, Balambigai Subramanian
Informing Science, 2025
BAYESIAN OPTIMIZATION FOR HYPERPARAMETER TUNING IN HEALTHCARE FOR DIABETES PREDICTION
Annapantula Sudhakar, Sujatha S, Sathiya M., Sivaramakrishnan A, Balambigai Subramanian, Venkata Ramana K
Informing Science, 2025
Predictive Modeling of Cryptocurrency Prices through Random Forest Regression and Sentiment Insights
Srinivasan Balakrishnan, Balambigai Subramanian, Ashok Kumar Chinnathambi, Amit Gangopadhyay, Suchita Yadav, Jolly Sneh Kapoor
2025 5th International Conference on Advancement in Electronics and Communication Engineering Aece 2025, 2025
Real-Time Load Forecasting Enhances Energy Access in Remote Villages
Layth Hussein Jasim, Priya Paul, Namitha P, U. Esakkiammal, S. Balambigai, Chidanand T, K.R Deeksha
Proceedings of 2025 International Conference on Intelligent Systems and Pioneering Innovations in Robotics and Electric Mobility Transforming Mobility and Automation Through Intelligent Engineering Inspire 2025, 2025
Piezoelectric Footpaths Convert Pedestrian Motion into Clean Electricity
Ramy Read Hossain, Abhijeeta Nandha, Aswathi K, R. Padmavathy, S. Balambigai, Uganya G, K.R Deeksha
Proceedings of 2025 International Conference on Intelligent Systems and Pioneering Innovations in Robotics and Electric Mobility Transforming Mobility and Automation Through Intelligent Engineering Inspire 2025, 2025
Securing Open Banking APIs Against Automated Credential Stuffing Attacks
S. Kanmani Jebaseeli, Abdullayeva Shakhnoza Anvarovna, Mohhamied HusaeinSallaah, Rajesh Sehgal, S. Balambigai, D. Beulah Pretty, Dilli Ganesh V, K Srikanth Bhat
Proceedings of 2025 International Conference on Intelligent Systems and Pioneering Innovations in Robotics and Electric Mobility Transforming Mobility and Automation Through Intelligent Engineering Inspire 2025, 2025
Performance Investigation of New Reduced Switch Count Thirty-Three Level Multilevel Inverter
, Manivel MURUGESAN, N. SUGANYA, , Karuppannan ANAND, , Tamilselven KESAVAN, , Duraisamy SARATHKUMAR, , R. JAYANTHI, , S. BALAMBIGAI, , V.J. VIJAYALAKSHMI, and
Eea Electrotehnica Electronica Automatica, 2025
Real-Time V2V Communication for Collision Avoidance in AV Networks
S Sivasubramanian, Nabiev Bosit Sobirovich, Zaeid Ajsan Salami, Sandeep Soni, S. Balambigai, Manzura Pirnazarova, Yogapriya J, M.O Pallavi
Proceedings of 2025 International Conference on Intelligent Systems and Pioneering Innovations in Robotics and Electric Mobility Transforming Mobility and Automation Through Intelligent Engineering Inspire 2025, 2025
AI-Integrated Disaster Risk Reduction System for Real-Time Response and Prevention in Vulnerable Regions
R. Ahila, Bekmirzayev Mirjalol Xusanboy Ugli, Haayder M. Abbas, Jainish Roy, S. Balambigai, P. Haridha, Dilli Ganesh V, Dhananjaya B
Proceedings of 2025 International Conference on Intelligent Systems and Pioneering Innovations in Robotics and Electric Mobility Transforming Mobility and Automation Through Intelligent Engineering Inspire 2025, 2025
RETRACTION:Future directions of artificial intelligence integration: Managing strategies and opportunities
R. Sundar, Ziaul Haque Choudhury, M. Chiranjivi, Gayatri Parasa, Praseeda Ravuri, M. Sivaram, Balambigai Subramanian, Kireet Muppavaram, Vijaya Madhavi Lakshmi.Challa
Journal of Intelligent and Fuzzy Systems, 2024
A Novel Approach Using Transfer Learning Architectural Models Based Deep Learning Techniques for Identification and Classification of Malignant Skin Cancer
Balambigai Subramanian, Suresh Muthusamy, Kokilavani Thangaraj, Hitesh Panchal, Elavarasi Kasirajan, Abarna Marimuthu, Abinaya Ravi
Wireless Personal Communications, 2024
Enabling secure and efficient industry 4.0 transformation through trust-authorized anomaly detection in cloud environments with a hybrid AI approach
N. Prakash, J. Vignesh, M. Ashwin, Sudhir Ramadass, N. Veeranjaneyulu, Shashikant V. Athawale, Ananda Ravuri, Balambigai Subramanian
Optical and Quantum Electronics, 2024
18 Deep Learning Model for Image Fusion and Accurate Classification of Remote Sensing Images
M. Sunil Kumar, T. Gnanasekaran, Balambigai Subramanian
Mathematical Methods in the Digital Age, 2024
Smart Car Parking System
T.C. Kalaiselvi, K. Sathyavardhan, S. Balambigai, S. Santhoshsiva
2nd International Conference on Emerging Trends in Information Technology and Engineering Ic Etite 2024, 2024
Innovative Practice on Tuberculosis Detection for Pneumonia Diagnosis using Machine Learning
K. Manju, P. M Dinesh, M. Thiyagarajan, Manjunathan Alagarsamy, Balambigai Subramanian, G. Prasanna Lakshmi
International Conference on Intelligent and Innovative Practices in Engineering and Management 2024 Iipem 2024, 2024
Predicting Solar and Wind Power Production with the Weather Map Data Approach
A. Vennila, S. Balambigai, Pradeepa V, Sabari U P, V.N. Kavyashree, M. Jinisha
2024 International Conference on Signal Processing Computation Electronics Power and Telecommunication Iconscept 2024 Proceedings, 2024
A Novel Method of Parkinson's Disease Detection from Acoustic Features using Machine Learning Systems
A. Vennila, S. Balambigai, A.S. Renugadevi, F.Mohammad Ashiq, V.N. Kavyashree, M. Jinisha
2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024
Retraction Notice: A Novel Method of Parkinson's Disease Detection from Acoustic Features using Machine Learning Systems (2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) DOI: 10.1109/ICCCNT61001.2024.10725678)
A. Vennila, S. Balambigai, A.S. Renugadevi, F.Mohammad Ashiq, V.N. Kavyashree, M. Jinisha
2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024
Mental stress detection using bidirectional encoder representations from transformers
A. Vennila, S. Balambigai, A. S. Renugadevi, J. Charanya
Machine Learning Algorithms Using Scikit and Tensorflow Environments, 2023
Radar optical communication for analysing aerial targets with frequency bandwidth and clutter suppression by boundary element mmwave signal model
V. P. Kavitha, D. Prabakar, S Ranjith subramanian, S. Balambigai
Optical and Quantum Electronics, 2023
Introduction to artificial intelligence
Mahesh Maurya, Vishal Gangadhar Puranik, A. Senthil Kumar, Balambigai Subramanian
Toward Artificial General Intelligence Deep Learning Neural Networks Generative AI, 2023
A Novel Hybrid Based Method in Covid 19 Health System for Data Extraction with Blockchain Technology
C. R. Rene Robin, Diana Moses, D. Vijendra Babu, Balambigai Subramanian, Siva Shankar S
International Journal on Recent and Innovation Trends in Computing and Communication, 2023
Verilog Implementation and Functional Verification of Hybrid Cryptography Algorithm
Sasikala. S, Sivaranjani. P, Balambigai. S, Keerthana. M
2023 14th International Conference on Computing Communication and Networking Technologies Icccnt 2023, 2023
Challenges and Application of 3D Printing in Radiation Oncology
A. Chandrashekhar, D. Sugumar, Balambigai Subramanian, N. Basker
2023 International Conference on Disruptive Technologies Icdt 2023, 2023
Design of Arithmetic Logic Unit Using Hybrid Power Reduction Methodologies For Super Computer Applications
S. Sasikala, S. Balambigai, P. Sivaranjani, V. Udhayasuriyan
2023 14th International Conference on Computing Communication and Networking Technologies Icccnt 2023, 2023
Design and Analysis of Annular Slot Antenna with Monopole for WLAN using Computer Simulation Technology
Thakur Rithika, Pathuri Sree Mahalakshmi, Brahmandlapally Anil, N. Arun Vignesh, Balambigai Subramanian
2023 International Conference on Computer Communication and Informatics Iccci 2023, 2023
Design and Analysis of M-Shaped Monopole Antenna for Bluetooth communications
Andrews Jogu, Kakinada Leelavathi, Iruvuru Manogna, N Arun Vignesh, Balambigai Subramanian
2023 International Conference on Computer Communication and Informatics Iccci 2023, 2023
Soft Computing Approach To Prevent Derailments Due To Landslides
S. Balambigai, P. V. Shreeram, J. Sureshkanna, S. Sasikala, S. Sowmika, N. Arun Vignesh
2023 14th International Conference on Computing Communication and Networking Technologies Icccnt 2023, 2023
Facial Recognition and Animal Recognition from Live Stream Video Using Machine Learning
Deepika Dua, Rahul Chauhan, Kiran Kumar C, S. Radhika, Balambigai Subramanian, Chandradeep Bhatt
2023 3rd International Conference on Advancement in Electronics and Communication Engineering Aece 2023, 2023
Evaluating the Solutions to Predict the Impact of Lung Cancer with an Advanced Intelligent Computing Method
R. Sundar, Sudhir Ramadass, D. Meeha, Balambigai Subramanian, S Siva Shankar, Gayatri Parasa
Proceedings 5th International Conference on Smart Systems and Inventive Technology Icssit 2023, 2023
XG Boost Algorithm based Hardware Trojan Detection in Hardware Circuits
A. Vennila, S. Balambigai, A. Arulmurugan, M. Hema, M. Kamali, M. Kishore
2023 5th International Conference on Electrical Computer and Communication Technologies Icecct 2023, 2023
Transfer learning based recurrent neural network algorithm for linguistic analysis
S. Sasikala, S Ramesh, S Gomathi, S Balambigai, V Anbumani
Concurrency and Computation Practice and Experience, 2022
Detection and optimization of skin cancer using deep learning
S Balambigai, K Elavarasi, M Abarna, R Abinaya, N Arun Vignesh
Journal of Physics Conference Series, 2022
Block Chain Technology Implementations for Secured Financial Transactions using Cloud Environment
T Vara Lakshmi, Naveen S.M Raja, Sudhir Ramadass, Sreekumar Narayanan, Velagapudi Sreenivas, Balambigai Subramanian
International Interdisciplinary Humanitarian Conference for Sustainability Iihc 2022 Proceedings, 2022
Cross Coupled Power Effective Quick Level Shifter
N. Sai Kiran, N. Arun Vignesh, S. Kanithan, E. Shobhana, N. Kumareshan, S. Madhusudhanan, Balambigai Subramanian, Prajith Prakash Nair
2022 International Conference on Computer Communication and Informatics Iccci 2022, 2022
Biometric Based Voting System Using Aadhar Database
G. Deepa, Balambigai Subramanian, A. Vennila, T.C. Kalaiselvi, B. Navin Yeshvanth, N. Sountharya, K.M. Sowndharya, M. Sivasamy
Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy Icais 2022, 2022
ROBOVAC-Automatic Floor Cleaning Robot
G. Deepa, Balambigai Subramanian, T. C. Kalaiselvi, A. Vennil, Nandhitha Kalyanasundaram, S. Preethi
Proceedings of the 3rd International Conference on Inventive Research in Computing Applications Icirca 2021, 2021
Chemically treated activated carbon for supercapacitor electrode derived from starch of solanum tuberosum
Senthil Kumar Kandasamy, Balambigai Subramanian, Hemalatha Krishnamoorthy, Chandrasekaran Arumugam, Suganthi V, Yuvasri M, Shreelogesh D
Journal of New Materials for Electrochemical Systems, 2021
Internet of Things Based Innovative and Cost-effective Smart Sericulture Farm Incubator
V. Mekala, K. S. Tamilsehan, Vibin Mammen Vinod, S. Balambigai, Kousalya J, Medhini K, Nandhini R
Proceedings of the 5th International Conference on Electronics Communication and Aerospace Technology Iceca 2021, 2021
Speech enhancement through improvised conditional generative adversarial networks
Saravana Ram Ram, Vinoth Kumar M, Balambigai Subramanian, Nebojsa Bacanin, Miodrag Zivkovic, Ivana Strumberger
Microprocessors and Microsystems, 2020
A study on detection of tuberculosis from chest x ray images and microscopic images based on deep learning techniques
International Journal of Scientific and Technology Research, 2020
Diagnosed image of breast cancer by antenna MVDR beamforming algorithm with composites
V. Nagaraju, Abhisek Sethy, Raja Sarath Kumar Boddu, S. Balambigai, K. Sakthisudhan
Materials Today Proceedings, 2020
A survey on investigation of vital human parameters from photoplethsmography signal to predict the risk of cardiovascular diseases
S. Balambigai, P. Jeevitha
2017 4th International Conference on Advanced Computing and Communication Systems Icaccs 2017, 2017
Investigation on the Compression of Electrocardiogram Signals Using Dual Tree Complex Wavelet Transform
Balambigai Subramanian, Asokan Ramasamy
IETE Journal of Research, 2017
ECG signal classification and parameter estimation using multiwavelet transform
Biomedical Research India, 2017
Anatomizing electrocardiogram using fractal features and GUI based detection of P and T waves
Balambigai Subramanian, K. Ramya, R. Asokan
Proceedings of the 2016 IEEE International Conference on Wireless Communications Signal Processing and Networking Wispnet 2016, 2016
Secure real time web based electrocardiogram monitoring system for improved healthcare
J. Vellingiri, S. Balambigai, K. Saravanan, R. Asokan
Journal of Medical Imaging and Health Informatics, 2016
Enhanced signature verification using neural network based on statistical features
International Journal of Simulation Systems Science and Technology, 2015
Performance comparison of electrocardiogram de-noising based on adaptive filter and gamma filter
Information Japan, 2014
Performance comparison of wavelet and multiwavelet denoising methods for an electrocardiogram signal
Balambigai Subramanian, Asokan Ramasamy, Kamalakannan Rangasamy
Journal of Applied Mathematics, 2014
Performance comparison of hybrid empirical mode decomposition based techniques for electrocardiogram denoising
International Journal of Simulation Systems Science and Technology, 2013
ECG de-noising based on hybrid technique
IEEE International Conference on Advances in Engineering Science and Management Icaesm 2012, 2012
Efficient zigbee based health care system for arrhythmia detection in electrocardiogram
European Journal of Scientific Research, 2012
Performance comparison of genetic algorithm and principal component analysis methods for ECG signal extraction
S. Balambigai, R. Asokan
International Journal of Healthcare Technology and Management, 2011

Dr, Balambigai S

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