Improving Blood Pressure Rate Measurement Accuracy With Deep Learning-based Sensor Fusion and Feature Selection Sakshi Sobti, Dr. Saurabh Jain, Dr. Arunkumar Devalapura Thimmappa, Dr. Shaikh Adil, Lovish Dhingra, et al. Journal of Wireless Mobile Networks Ubiquitous Computing and Dependable Applications, 2025 Hypertension is the predominant cardiovascular disease (CVD) risk factor, but the standard method of blood pressure (BP) assessment has proven unreliable. This has led to an increasing interest in developing more sophisticated and accurate methods. In this paper, we present a novel technique that incorporates deep learning, sensor fusion, and feature selection strategies for precise blood pressure measurement. This approach requires no additional records beyond the data from blood pressure cuffs, ECG, photoplethysmography (PPG), and sensor data, and features with a strong one-to-one positive relationship with blood pressure are identified. A deep-learning model using these features, sensor fusion, and feature selection techniques is trained over the dataset. Deep learning model - trained on a large dataset of blood pressure values to know the complex correlations between the features and blood pressure. The results of our research, presented in Section 6, show that our novel methodology significantly increased the accuracy of the blood pressure rate by 8% on average. Our deep learning approach is orders of magnitude more sensitive and substantially more resistant to sensor noise and artifacts compared to classical approaches, allowing even minute changes in blood pressure measurements to be accurately captured. This makes our method applicable in practice where accurate and reliable blood pressure measurements are required. Crucially, we can also apply our method to blood pressure monitoring in chronic patients for telemedicine. In this sense, considering the increasing omnipresence and acceptance of wearable devices, we foresee the integration of our proposed methodology, hopefully in the form of such wearables, to enable noninvasive and continuous blood pressure (BP) monitoring. In general, this approach offers a promising alternative for improving the accuracy of BP rate measurements. This work demonstrates the potential to leverage information from multiple sensors by utilizing deep learning for sensor fusion and feature selection processes, resulting in more accurate and reliable blood pressure (BP) measurements. That could make a significant difference in the accuracy of diagnosing or treating high blood pressure with the potential to improve patient outcomes and reduce healthcare costs in the long run.
AI-Powered Framework for Non-Invasive Continuous Blood Pressure Tracking Using Smartwatch Sensors Dr. Sangita Babu, Dr. Arun Khatri, Abhinav Rathour, Dinesh Kumar Jayaraman Rajendiran, Bharat Bhushan, et al. Journal of Wireless Mobile Networks Ubiquitous Computing and Dependable Applications, 2025 Real-time monitoring of blood pressure is crucial for detecting early hypertension and other cardiovascular diseases. However, the common method of measuring blood pressure remains invasive and intermittent, causing inconvenience and discomfort to patients. Smartwatches as a potential platform for continuous blood pressure (BP) measurements have recently attracted a great deal of interest, thanks to developments in wearables, and have been approached with different methodologies. In this paper, we propose a deep learning-based framework for predicting wearable blood pressure using smartwatch sensors. We utilize the smartwatch's optical heart rate sensor and accelerometer to collect physiological signals, including heart rate and motion. A DCNN, followed by an LSTM, is used on the signal values. The concatenated features are then fed to the regression model for estimating blood pressure from the concatenated features using a CNN-LSTM. A dataset of 50 participants' physiological signals and ground-truth blood pressures is collected to validate and test the framework. Datasets: The dataset was partitioned into training, validation, and test splits, which were used to train and test our framework. Our method achieved mean errors of 3.26 mmHg for systolic blood pressure (SBP) and 2.12 mmHg for diastolic blood pressure (DBP), which were superior to state-of-the-art results. This work enables smartwatches for non-intrusive and effortless blood pressure monitoring processes with long-term and online applications. It can be worn daily, and we use the Teal-Time blood pressure tracker to identify certain abnormal blood flow patterns. This could significantly impact the control of these conditions (such as hypertension) and likely improve overall health. For these factors, our system is generalizable to other wearables, allowing it to be widely used in the population. Our study demonstrated that blood pressure (BP) was monitored continuously under a real-world setting using a smartwatch and played a significant role in healthcare.
Integrated biodiesel and biopolymer production from Nannochloropsis biomass: a closed-loop biorefinery approach N. Nirmala, J. Arun, Sivasubramanian Palanisamy, R. S. Ernest Ravindran, Mohamed Abbas, et al. Rsc Advances, 2025 A closed-loop biorefinery using Nannochloropsis sp. achieved 90.4% biodiesel conversion and 39% PHB yield from deoiled biomass, demonstrating sustainable dual production of biofuel and biopolymer for a circular bioeconomy.
Molecular Evolution of Invasive Species and their Ecological Impacts on Global Fisheries and Aquaculture Systems Dr.T.R. Vijaya Lakshmi, Gulzat Ziyatbekova, Aditya Pratap Singh, Dr. Bhanu Sree Reddy, Dr. Purva Mange, et al. Natural and Engineering Sciences, 2025 The increasing rate of international trading and global warming has supported the fatality of introducing non-native species in large numbers, which is a major threat to aquatic biodiversity and world food security. In this paper, consider the molecular evolution of the invasive species and the implications that it has had on the global fisheries and aquaculture systems. Recent discoveries in genomics, such as epigenetic plasticity, hybridization, and adaptive evolution at high rates, are combined to describe how the invasive population of a species can break the founder effect and initial genetic bottleneck to conquer new environments. Nature is found to be unstable through molecular shifts in invasive taxa that cause much ecological disturbance, including genetic pollution of wild stocks by introgression and introduction of new pathogens that annihilate commercial aquaculture. It also elaborates on the effect of the Trojan horse, where the genomic strength of invaders enables them to act as unrelenting vectors of diseases in warming oceans. The shortcomings of conventional ecological modeling are shown through analysis of case studies, including the Lessepsian migration and the invasion of Atlantic lionfish, which are in favor of merging the environmental surveillance systems of environmental DNA (eDNA) and genomic biosecurity. As a possible way to reduce the invasive effects, the potential and ethical aspects of biotechnological interventions, including CRISPR-based gene drives, are considered. Conclusion: It is determined that to have a sustainable management of the global blue economy, knowledge of the molecular basis of invasiveness is a prerequisite. To protect the sustainability of fisheries and the socio-economic well-being of coastal societies all over the globe, the integration of genomic insights into international policy is needed.
Development of a Fully Differential-Difference Transconductance-Based Filter for Cardiac Troponin Sensor J. Shailaja, R. S. Ernest Ravindran Journal of Circuits Systems and Computers, 2024 Acute myocardial infarction (AMI) is one of the foremost global health threats. Human cardiac troponin I (cTnI) is an effective and golden biomarker for accurately diagnosing AMI. Owing to higher fatality worldwide, an accurate, rapid diagnosis of AMI is highly significant at the early stage for effective treatment. This study designed a novel portable cardiac troponin sensor using a fully differential-difference transconductance-based fifth-order double-notch low pass filter (FDdiff_5thDNLPF) for accurate and early diagnosis of AMI by identifying cTnI. The developed biosensor system can identify cTnI from the blood samples. The twofold ion-sensitive gated field effect transistor (TISG-FET), which can provide a dynamic range, high sensitivity, and high selectivity to target analyte, is used to identify cTnI level and transform the cTnI concentration to drain the current signal. The differential-input instrumentation amplifier (DiffInp_IA) is used as a preamplifier to receive and amplify the input current. The FDdiff_5thDNLPF circuit removes unwanted noises and eliminates available frequencies greater than 50 Hz powerline interference. The signals are then provided to an intermediate amplifier and converted to digital form using an analog-to-digital converter (ADC) circuit. Further, the digital signals have been processed through a central processing unit (CPU), and the data can be displayed. The proposed system for cTnI detection is simulated on the cadence Virtuoso tool. As a result, the proposed system exhibited a minimum detection limit of 0.31 pg/ml, a wide linear range among 1–1000 pg/ml and higher sensitivity of 131 pA pg[Formula: see text] ml[Formula: see text].
A Fusion Classification Prototypical for Eye State Recognition in Stroke Patients Using Electroencephalogram (EEG) Data International Journal of Intelligent Systems and Applications in Engineering, 2023
Enhancing Decision Making Through Smart Predictive Analysis Using AI Nishit Kumar Srivastava, Aditya Dhiman, Naresh Kedia, R.S. Ernest Ravindran, Shweta Saxena, et al. 2023 3rd International Conference on Smart Generation Computing Communication and Networking Smart Gencon 2023, 2023
Design and verification of half adder using look up table (LUT) in quantum dot cellular automata (QCA) International Journal of Advanced Science and Technology, 2019
Design and simulation of low power consuming digital controlled oscillator in all digital phase locked loop Research Scholar, Assistant Professor, ECE Department, K L University Campus, Vaddeswaram Village, Andhra Pradesh, India.., Sudhakiran Gunda*, Dr. Ernest Ravindran R. S, Assistant Professor, ECE Department, K L University Campus, Vaddeswaram Village, Andhra Pradesh, India. International Journal of Innovative Technology and Exploring Engineering, 2019
Design and implementation of dual edge triggered shift registers for iot applications International Journal of Scientific and Technology Research, 2019
Design of RAM using Quantum Cellular Automata (QCA) designer International Journal of Scientific and Technology Research, 2019
A novel 24t conventional adder vs low power reconstructable transistor level conventional adder International Journal of Engineering and Advanced Technology, 2019
A novel two fold edge activated memory cell with low power dissipation and high speed International Journal of Recent Technology and Engineering, 2019
Comparative analysis of efficient hierarchy multiplier using Vedic mathematics International Journal of Innovative Technology and Exploring Engineering, 2019
A detailed scrutiny and reasoning on VLSI binary adder circuits and architectures International Journal of Innovative Technology and Exploring Engineering, 2019
Design of low-power, area efficient 2-4 and 4-16 mixed-logic line decoders Journal of Advanced Research in Dynamical and Control Systems, 2019
Five Input Multilayer Full Adder by QCA Designer D. Naveen Sai, G. Surya Kranth, Damarla Paradhasaradhi, R. S. Ernest Ravindran, M. Lakshmana Kumar, et al. Communications in Computer and Information Science, 2019
An eco-friendly approach for synthesis of silver nanoparticles using Ipomoea pes-caprae root extract and their antimicrobial properties Asian Journal of Pharmaceutical and Clinical Research, 2015
Bioreduction of silver nanoparticles from aqueous stem extract of catharanthus roseus and bactericidal effects Asian Journal of Pharmaceutical and Clinical Research, 2015
Green synthesis and characterization of silver nanoparticle using leaf extract of Capparis zeylanica Asian Journal of Pharmaceutical and Clinical Research, 2014
Synthesis and characterization of silver nanoparticle from Erythrina indica Asian Journal of Pharmaceutical and Clinical Research, 2014
Improving Blood Pressure Rate Measurement Accuracy With Deep Learning-based Sensor Fusion and Feature Selection DRSER Sakshi Sobti1* , Dr. Saurabh Jain2 , Dr. Arunkumar Devalapura ... Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable … , 2025 2025
AI-Powered Framework for Non-Invasive Continuous Blood Pressure Tracking Using Smartwatch Sensors DRSER Dr. Sangita Babu1* , Dr. Arun Khatri2 , Abhinav Rathour3 , Dinesh ... Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable … , 2025 2025
A Review of PVT analysis of various CMOS current mirror configurations in 180 nm technology R Ningampalli, S Donti, RSE Ravindran Proceedings of the Indian National Science Academy, 1-13 , 2025 2025
Research Article P Sharma, S Vyas, M Kaushal, NV Mahure, N Sivakumar, R Kumar, ... HARYANA VETERINARIAN 64, 1 , 2025 2025
Unleashing the Truth: Insights into Canine Mammary Tumours A Kumar, P Syal, R Ravindran Bio Vet Innovator Magazine 2 , 2025 2025
Integrated biodiesel and biopolymer production from Nannochloropsis biomass: a closed-loop biorefinery approach N Nirmala, J Arun, S Palanisamy, RSE Ravindran, M Abbas, S Kalathil, ... RSC advances 15 (50), 42513-42521 , 2025 2025 Citations: 2
Familial Congenital Hyperplastic and Colloidal Goitre in a Beetle Goat. R Ravindran, V Bassessar, P Syal, S Punia International Journal of Bio-Resource & Stress Management 15 (11) , 2024 2024
Development of a Fully Differential-Difference Transconductance-Based Filter for Cardiac Troponin Sensor J Shailaja, RSE Ravindran Journal of Circuits, Systems and Computers 33 (15), 2450263 , 2024 2024
Diagnosis of Diabetic Retinopathy Through Retinal Image Segmentation ERRS Y Madhu Sudhana Reddy ISBN-978-6207475551 , 2024 2024
Kidney stone detection using ultrasonographic images by support vector machine classification D Manjunatha, V Vishwakarma, A Mishra, RE Ravindran, K Kumari Nanotechnology Perceptions 20 (S2), 93-106 , 2024 2024 Citations: 10
Development of a Fully Differential-Difference Transconductance-Based Filter for Cardiac Troponin Sensor RSE Shailaja J, Ravindran Journal of Circuits, Systems and Computers , 2024 2024
Kidney Stone Detection Using Ultrasonographic Images by Support Vector Machine Classification KKBM Manjunatha D, Vishwakarma, Vinayak, Mishra, Alina, Ernest Ravindran R.S Nanotechnology Perceptions 20 (52) , 2024 2024
Silica coated Iron Oxide Nanoparticles - Performance Evaluation for Drug Delivery Applications R Veeramani, Subha, Ravindran, Ernest, Mayakrishnan, Vishnuvarthanan, V ... Silicon 16 (5) , 2024 2024
Retracted: Enhancing Decision Making Through Smart Predictive Analysis Using AI NK Srivastava, A Dhiman, N Kedia, RSE Ravindran, S Saxena, P Varma 2023 3rd International Conference on Smart Generation Computing … , 2023 2023 Citations: 2
A Commercial-Scale, Circular-Economical Bio-Refinery Model for Sustainable Yields of Mushrooms, Cellulase-Complex, Bio-Priming Agents, Bio-Ethanol, and Bio-Fertilizer NK Ramamoorthy, V Vengadesan, RB Pallam, V Krishnasamy, ... Kavaka 59, 26-39 , 2023 2023 Citations: 4
Compared to The Threshold Dependent Segmentation Technique, Normal Type Lung Cancer Identification in CT Images Utilizing Structural Flood Segmentation Process to Enhance … AK Yadav, S Kashyap, SS Pund, HM Salman, RSE Ravindran, ... 2023 3rd International Conference on Advance Computing and Innovative … , 2023 2023
Cellulase production from disposed COVID-19 personal protective equipment (PPE) using cyclic fed-batch strategies NK Ramamoorthy, RB Pallam, S Renganathan, VV Sarma Process Biochemistry 127, 112-126 , 2023 2023 Citations: 5
Enhancing the performance of piezoelectric wind energy harvester using curve‐shaped attachments on the bluff body P Poudel, S Sharma, MNM Ansari, R Vaish, R Kumar, SM Ibrahim, ... Global Challenges 7 (4), 2100140 , 2023 2023 Citations: 22
Design of Low-Drop-Out Voltage Regulator using CMOS Technology for Microprocessor Applications TPSK Kusumanchi, RS Ernest Ravindran, K Jaya Sankar Krishna, ... Journal of Physics: Conference Series 2471 (1), 012017 , 2023 2023 Citations: 1
Design and simulation of a low power and high speed Fast Fourier Transform for medical image compression ER RS, PS Ngangbam, S Gunda MDPI , 2023 2023
MOST CITED SCHOLAR PUBLICATIONS
Green synthesis of iron oxide nanoparticles from Mimosa pudica root extract VA Niraimathee, V Subha, RSE Ravindran, S Renganathan International Journal of Environment and Sustainable Development 15 (3), 227-240 , 2016 2016 Citations: 199
Synthesis and characterization of copper nanoparticle using Capparis zeylanica leaf extract K Saranyaadevi, V Subha, RE Ravindran, S Renganathan Int J Chem Tech Res 6 (10), 4533-41 , 2014 2014 Citations: 196
Synthesis and characterization of silver nanoparticle from Erythrina indica P Kalainila, V Subha, RS Ernest Ravindran, R Sahadevan Asian Journal of Pharmaceutical and Clinical Research 7 (2), 39-43 , 2014 2014 Citations: 68
Silver nanoparticles blended PEG/PVA nanocomposites synthesis and characterization for food packaging RSE Ravindran, V Subha, R Ilangovan Arabian Journal of Chemistry 13 (7), 6056-6060 , 2020 2020 Citations: 63
Dielectric properties of Poly(methyl methacrylate) (PMMA)/CaCu 3 Ti 4 O 12 composites P Thomas, RSE Ravindran, KBR Varma 2012 IEEE 10th International Conference on the Properties and Applications … , 2012 2012 Citations: 55
GREEN SYNTHESIS OF COPPER NANOPARTICLE FROM PASSIFLORA FOETIDA LEAF EXTRACT AND ITS ANTIBACTERIAL ACTIVITY RS SAMAR FATMA, KALAINILA P, ERNEST RAVINDRAN Asian Journal of Pharmaceutical and Clinical Research 10 (4), 79-83 , 2017 2017 Citations: 54
Green synthesis and characterization of silver nanoparticle using leaf extract of Capparis zeylanica K Saranyaadevi, V Subha, RSE Ravindran, S Renganathan Asian J. Pharm. Clin. Res 7 (2), 44-48 , 2014 2014 Citations: 52
Structural, thermal and electrical properties of poly(methyl methacrylate)/CaCu 3 Ti 4 O 12 composite sheets fabricated via melt mixing P Thomas, RS Ernest Ravindran, KBR Varma Journal of Thermal Analysis and Calorimetry 115 (2), 1311-1319 , 2014 2014 Citations: 49
Nanomaterials: Synthesis, physicochemical characterization, and biopharmaceutical applications R Ilangovan, V Subha, RSE Ravindran, S Kirubanandan, S Renganathan Nanoscale Processing, 33-70 , 2021 2021 Citations: 34
Silver nanoparticles green synthesis with Aq. extract of stems Ipomoea pes-caprae, characterization, antimicrobial and anti-cancer potential S Veeramani, E Ravindran, P Ramadoss, C Joseph, K Shanmugam, ... Int J Med Nano Res 5 (024), 10-23937 , 2018 2018 Citations: 30
Enhancing the performance of piezoelectric wind energy harvester using curve‐shaped attachments on the bluff body P Poudel, S Sharma, MNM Ansari, R Vaish, R Kumar, SM Ibrahim, ... Global Challenges 7 (4), 2100140 , 2023 2023 Citations: 22
Dielectric properties of nylon 11/CaCu 3 Ti 4 O 12 (CCTO) nanocomposite films with high permittivity P Thomas, A Ashokbabu, RSE Ravindran, R Vaish IEEE Transactions on Dielectrics and Electrical Insulation 26 (2), 568-575 , 2019 2019 Citations: 18
An Eco friendly approach for synthesis of Silver Nanoparticles Using Ipomoea Pes-caprae Root Extract and their Antimicrobial Properties RS Subha V, Ernest Ravindran R S, Sruthi P Asian Journal of Pharmaceutical and Clinical Research 8 (5), 1-4 , 2015 2015 Citations: 17
A comparative study on dielectric, structure, and thermal behavior of micro‐and nano‐sized CCTO in nylon 6, 9 matrix ER Ramaswami Sachidanandan, T Paramanandam, R Sahadevan Polymer Composites 38 (5), 927-935 , 2017 2017 Citations: 16
Detection of heavy metal ions using star-shaped microfluidic channel C Santhosh, KH Kishore, GP Lakshmi, G Kushwanth, PRKD Teja, ... International Journal of Emerging Trends in Engineering Research, ISSN, 2347 … , 2019 2019 Citations: 14
A Detailed Scrutiny and Reasoning on VLSI Binary Adder Circuits and Architectures PRB K Mariya Priyadarshini, R. S. Ernest Ravindran International Journal of Innovative Technology and Exploring Engineering … , 2019 2019 Citations: 13
Effect on dielectric, structural and thermal behaviour of in a Nylon 11 matrix RS Ernest Ravindran, P Thomas, S Renganathan Bulletin of Materials Science 42 (1), 28 , 2019 2019 Citations: 13
Fabrication and characterization of poly(methyl methacrylate)/CaCu 3 Ti 4 O 12 composites P Thomas, RSE Ravindran, KBR Varma Polymer Engineering & Science 54 (3), 551-558 , 2014 2014 Citations: 13
Diabetic retinopathy through retinal image analysis: A review YMS Reddy, RSE Ravindran, KH Kishore International Journal of Engineering & Technology 7 (1.5), 19-25 , 2018 2018 Citations: 12
Kidney stone detection using ultrasonographic images by support vector machine classification D Manjunatha, V Vishwakarma, A Mishra, RE Ravindran, K Kumari Nanotechnology Perceptions 20 (S2), 93-106 , 2024 2024 Citations: 10
