Biomedical Engineering, Multidisciplinary, Engineering, Metals and Alloys
15
Scopus Publications
385
Scholar Citations
9
Scholar h-index
8
Scholar i10-index
Scopus Publications
Cancer Detection Using Artificial Intelligence: A Paradigm in Early Diagnosis Gayathri Bulusu, K. E. Ch Vidyasagar, Malini Mudigonda, Manob Jyoti Saikia Archives of Computational Methods in Engineering, 2025 Cancer detection has long been a continuous key performer in oncological research. The revolution of artificial intelligence (AI) and its application in the field of cancer turned out to be more promising in the recent years. This paper provides a detailed review of the various aspects of AI in different cancers and their staging. The role of AI in interpreting and processing the imaging data, its accuracy and sensitivity to detect the tumors is examined. The images obtained through imaging modalities like MRI, CT, ultrasound etc. are considered in this review. Further the review highlights the implementation of AI algorithms in 12 types of cancers like breast cancer, prostate cancer, lung cancer etc. as discussed in the recent oncological studies. The review served to summarize the challenges involved with AI application. It revealed the efficacy of AI in detecting the region, size, and grade of cancer. While CT and ultrasound proved to be the ideal imaging modalities for cancer detection, MRI was helpful for cancer staging. The review bestows a roadmap to fully utilize the potential of AI in early cancer detection and staging to enhance patient survival.
Gamified Rehabilitation and Physiotherapy Using MediaPipe for Posture and Hand Gesture Recognition K.E.Ch Vidyasagar, G. N. K. Anantha Sai, Munagala Ruchita, Manob Jyoti Saikia Proceedings of 2024 2nd International Conference on Recent Trends in Microelectronics Automation Computing and Communications Systems Exploration and Blend of Emerging Technologies for Future Innovation Icmacc 2024, 2024 Introduction: Rehabilitation for conditions affecting mobility, such as stroke, muscle atrophy, and others, poses significant challenges in traditional physiotherapy practices. Engaging patients in enjoyable exercises is crucial for maintaining compliance with rehabilitation protocols. In response, this paper introduces a pioneering game-based approach to rehabilitation, leveraging posture detection technology. Materials and Methods: A game-based rehabilitation system was developed utilizing deep learning techniques through the MediaPipe framework for posture and hand gesture recognition. The system analyzes user posture in real time via a webcam and translates these movements into game controls, allowing patients to interact with popular games like Subway Surfers to simulate physical activities such as running and jumping. Latency between patient movements and in-game responses was measured across three hardware configurations (8GB, 12GB, and 16GB RAM) to evaluate system performance and responsiveness. Results and Discussion: Latency decreased with higher RAM, with the lowest measured at 430 ms on a 16GB configuration. This real-time responsiveness enhances patient engagement, making the rehabilitation process more immersive and effective. By leveraging posture detection technology, this innovative system bridges the gap between the necessity of rehabilitation exercises and the appeal of gaming, offering a promising solution for improving treatment outcomes across diverse age groups and conditions.
Portable Multiparameter Biomedical Sensor Fusion for Home Healthcare K.E.Ch Vidyasagar, Venkata Jaideep Datta Manchikanti, Harika Kanduri, Manob Jyoti Saikia Proceedings of 2024 2nd International Conference on Recent Trends in Microelectronics Automation Computing and Communications Systems Exploration and Blend of Emerging Technologies for Future Innovation Icmacc 2024, 2024 The ever-increasing focus on preventative healthcare and remote patient monitoring has driven the need for innovative solutions. Traditionally, measuring vital signs in both clinical and home settings has relied on a collection of individual devices, often leading to cluttered setups, patient discomfort, and potential inaccuracies due to user error. This paper proposes a multi-parameter acquisition system designed to address these limitations. The system integrates the measurement of essential parameters into a single, user-friendly device. This streamlined approach not only reduces measurement complexity but also improves patient comfort by eliminating the need for multiple devices and cumbersome wires. The design of the system, including its sensors, hardware components, and data processing unit is presented in detail. The device serves a dual purpose. Firstly, it empowers individuals at home by providing them with a single device to monitor their vital signs. Secondly, for hospitals, the device offers a streamlined and less cumbersome way to visualize essential patient parameters, allowing for improved monitoring efficiency.
Simulation and Control Solutions for Accessible Surgical Robotics in Developing Nations K. E. Ch Vidyasagar, Renu Karadula, Mahesh Suraram, Manob Jyoti Saikia 2024 IEEE 20th International Conference on Body Sensor Networks Bsn 2024 Proceedings, 2024 Robotic-assisted medical procedures have grown remarkably since the late 1980s, demonstrating outcomes comparable to or better than laparoscopic surgery, including reduced blood loss, less postoperative pain, improved cosmetic results, and quicker recovery. Surgeons using robotic systems experience less physiological stress compared to traditional open approaches. The incorporation of robotic surgery allows tele-mentoring and telesurgery. Through telesurgery, surgeons can perform operations from a distance, cutting down on travel time and removing geographical restrictions to enhance surgical productivity. In developing nations with a general lack of healthcare professionals and resources, the expansion of robotic procedures will be a true game changer. Challenges hindering this expansion include fragmentation, high costs, and a steep learning curve, limiting access to smaller hospitals and creating disparities in the training of surgeons. For example, the first urologic robotic system in India was installed at AIIMS, New Delhi, in 2006. Yet, India's global contribution to robotic surgery is less than 0.1%, with only 76 systems across 66 centers and over 500 trained surgeons in 2021. To address these issues, we designed a physical prototype and virtual simulation system. The prototype features three control modes: GUI, joystick, and color-based sorting for two serial manipulator arms, offering flexible training for surgeons. It can also be used in rehabilitation, diagnosis, and other procedures. The virtual simulation provides cost-effective, comprehensive training, reducing the need for expensive installations and accelerating the learning curve. This dual approach makes advanced medical training more accessible and affordable, potentially democratizing robotic surgery for all medical practitioners.
Signal to Image Conversion and Convolutional Neural Networks for Physiological Signal Processing: A Review K. E. Ch Vidyasagar, K. Revanth Kumar, G. N. K. Anantha Sai, Munagala Ruchita, Manob Jyoti Saikia IEEE Access, 2024 Physiological signals obtained from electroencephalography (EEG), electromyography (EMG), and electrocardiography (ECG) provide valuable clinical information but pose challenges for analysis due to their high-dimensional nature. Traditional machine learning techniques, relying on hand-crafted features from fixed analysis windows, can lead to the loss of discriminative information. Recent studies have demonstrated the effectiveness of deep convolutional neural networks (CNNs) for robust automated feature learning from raw physiological signals. However, standard CNN architectures require two-dimensional image data as input. This has motivated research into innovative signal-to-image (STI) transformation techniques to convert one-dimensional time series into images preserving spectral, spatial, and temporal characteristics. This paper reviews recent advances in strategies for physiological signal-to-image conversion and their applications using CNNs for automated processing tasks. A systematic analysis of EEG, EMG, and ECG signal transformation and CNN-based analysis techniques spanning diverse applications, including brain-computer interfaces, seizure detection, motor control, sleep stage classification, arrhythmia detection, and more, are presented. Key insights are synthesized regarding the relative merits of different transformation approaches, CNN model architectures, training procedures, and benchmark performance. Current challenges and promising research directions at the intersection of deep learning and physiological signal processing are discussed. This review aims to catalyze continued innovations in effective end-to-end systems for clinically relevant information extraction from multidimensional physiological data using convolutional neural networks by providing a comprehensive overview of state-of-the-art techniques.
Gaze Tracking Control System for Wheelchair and Smart Home Automation K. E. Ch Vidyasagar, Ganji N V Shiva Prasad, Mekala Srimanth Raj, Saniya Mahreeen, Manob Jyoti Saikia 2023 IEEE 19th International Conference on Body Sensor Networks Bsn 2023 Proceedings, 2023 In recent times, eye-controlled interfaces have revolutionized the lives of numerous individuals, particularly those with disabilities or severe motor impairments that hinder their use of alternative computer peripherals. The focus of this research paper is an eye-tracking system that goes beyond enabling independent mobility—it empowers users to control various smart home devices in their surroundings. It is comparatively easier to use than an EMG-controlled wheelchair. Additionally, the system incorporates an audio output feature to cater to the user's daily needs effectively. Our research objective is to design an innovative eye-tracking system with a user-friendly multi-screen interface. Each screen represents a smart home device, including a wheelchair, allowing users to effortlessly navigate and select devices using different eye-blinking patterns. This intuitive interface enhances user control and accessibility. Moreover, the system prioritizes user safety by integrating various sensors. These sensors ensure secure and reliable operation, providing peace of mind for individuals using the wheelchair. Overall, the eye tracking system is equipped with advanced features, offering a reliable and safe solution for individuals with mobility limitations. This work highlights the importance of user-centric design and personalized customization to ensure the system meets the specific needs and preferences of the wheelchair user.
Protein Patterning on Microtextured Polymeric Nanobrush Templates Obtained by Nanosecond Fiber Laser Meenakshi Verma, Abhishek Rana, Koyyana E. Ch. Vidyasagar, Dinesh Kalyanasundaram, Sampa Saha Macromolecular Bioscience, 2022 Micropatterned polymer brushes have attracted attention in several biomedical areas, i.e., tissue engineering, protein microarray, biosensors etc., for precise arrangement of biomolecules. Herein, we report a facile and scalable approach to create microtextured polymer brushes with the ability to generate different type of protein patterns. Nanosecond fibre laser was exploited to generate micropatterns on polyPEGMA (poly(ethylene glycol) methacrylate) brush modified Ti alloy substrate. Surface initiated atom transfer radical polymerisation was employed to grow PolyPEGMA brush (11-87 nm thick) on Ti alloy surface immobilized with initiator having an initiator density (σ*) of 1.5 initiators/nm2 . Polymer brushes were then selectively laser ablated and their presence on non-textured area was confirmed by atomic force microscopy, fluorescence microscopy and X-ray photoelectron spectroscopy. Spatial orientation of biomolecules was first achieved by non-specific protein adsorption on areas ablated by the laser, via physisorption. Further, patterned brushes of polyPEGMA were modified to activated ester that gave rise to protein conjugation specifically on non-laser ablated brush areas. Moreover, the laser ablated brush modified patterned template was also successfully utilized for generating alternate patterns of bacteria. This promising technique can be further extended to create interesting patterns of several biomolecules which are of great interest to biomedical research community. This article is protected by copyright. All rights reserved.
An exploration of frictional and vibrational behaviors of textured deep groove ball bearing in the vicinity of requisite minimum load K. E. Ch. Vidyasagar, R. K. Pandey, Dinesh Kalyanasundaram Friction, 2021 In case of lightly loaded radial ball bearings, failure mechanisms other than fatigue such as smearing of raceways due to increased frictional torque and vibrations often prevail. Hence, attempts have been made herein for reducing the frictional torque and minimizing the vibrations of a radial deep groove ball bearing employing surface textures at the inner race. Nanosecond pulsed laser was used to create texture (involving micro-dimples having different dimple area density) on the inner race of test bearings. Using an in-house developed test rig, frictional torque and vibrational parameters were measured at different speeds and light loads (i.e. in vicinity of 0.01C, where C is dynamic load capacity of radial ball bearing). Significant reduction in frictional torque and overall vibrations were found in the presence of micro-dimples on inner race at light loads irrespective of operating speeds. Even without satisfying the minimum load needed criteria for the satisfactory operation, substantial reduction in smearing marks was found on the races of textured ball bearings in comparison to conventional cases.
A Wearable Hand Exoskeleton with Digital Twin Visualization and Motion Assistance for Rehabilitation Therapy D Suman, HV Chathilla, RP Galenka, B Samudrala, KEC Vidyasagar SoutheastCon 2026, 1-6 , 2026 2026
Vision-Guided Segregation of Biomedical Waste Using AI-Driven Control Architecture KEC Vidyasagar, H Kanduri, VJD Manchikanti, S Yelisetti, BS Edara, ... SoutheastCon 2026, 1-6 , 2026 2026
Cancer Detection Using Artificial Intelligence: A Paradigm in Early Diagnosis: G. Bulusu et al. G Bulusu, KEC Vidyasagar, M Mudigonda, MJ Saikia Archives of Computational Methods in Engineering 32 (4), 2365-2403 , 2025 2025 Citations: 25
Design of Orthosis for Ankle Inversion Injuries JK Talari, M Malini, KEC Vidyasagar International Conference on Biomedical Engineering Science and Technology … , 2025 2025
Organ-Specific Cancer Diagnosis: A Machine Learning-Based GUI Approach B Gayathri, S Sultana, M Malini, KEC Vidyasagar International Conference on Biomedical Engineering Science and Technology … , 2025 2025
Design and Development of Robotic Arm for Tele-Surgical and Diagnostic Applications SR Mekala, RC Rehmatullah, KEC Vidyasagar, BJ Ranger, MJ Saikia International Conference on Biomedical Engineering Science and Technology … , 2025 2025
Gamified Rehabilitation and Physiotherapy Using MediaPipe for Posture and Hand Gesture Recognition KEC Vidyasagar, GNKA Sai, M Ruchita, MJ Saikia 2024 2nd International Conference on Recent Trends in Microelectronics … , 2024 2024 Citations: 3
Portable Multiparameter Biomedical Sensor Fusion for Home Healthcare KEC Vidyasagar, VJD Manchikanti, H Kanduri, MJ Saikia 2024 2nd International Conference on Recent Trends in Microelectronics … , 2024 2024
Simulation and Control Solutions for Accessible Surgical Robotics in Developing Nations KEC Vidyasagar, R Karadula, M Suraram, MJ Saikia 2024 IEEE 20th International Conference on Body Sensor Networks (BSN), 1-4 , 2024 2024 Citations: 2
Signal to image conversion and convolutional neural networks for physiological signal processing: A review KEC Vidyasagar, KR Kumar, GNKA Sai, M Ruchita, MJ Saikia Ieee Access 12, 66726-66764 , 2024 2024 Citations: 69
Enhanced corrosion resistance of CoCrMo by laser-based surface modification KEC Vidyasagar, D Kalyanasundaram Surface Engineering 40 (1), 100-111 , 2024 2024 Citations: 3
Gaze tracking control system for wheelchair and smart home automation KEC Vidyasagar, GNVS Prasad, MS Raj, S Mahreeen, MJ Saikia 2023 IEEE 19th International Conference on Body Sensor Networks (BSN), 1-4 , 2023 2023 Citations: 3
Laser surface texturing of freeform surfaces of articulating components for enhanced tribo-corrosion properties V KE CH IIT Delhi , 2023 2023
Classification of mild and severe adolescent idiopathic scoliosis (AIS) from healthy subjects via a supervised learning model based on electromyogram and ground reaction force … A Sikidar, KEC Vidyasagar, M Gupta, B Garg, D Kalyanasundaram Biocybernetics and Biomedical Engineering 42 (3), 870-887 , 2022 2022 Citations: 6
Protein patterning on microtextured polymeric nanobrush templates obtained by nanosecond fiber laser M Verma, A Rana, KEC Vidyasagar, D Kalyanasundaram, S Saha Macromolecular Bioscience 22 (5), 2100454 , 2022 2022 Citations: 10
Design and Development of Caged Ball Heart Valve Using Solid Works KEC Vidyasagar, R Varma International Journal of Systems Applications, Engineering & Development 16 … , 2022 2022
Tribodynamic studies of textured gearsets lubricated with fresh and MoS2 blended greases N Gupta, N Tandon, RK Pandey, KEC Vidyasagar, D Kalyanasundaram Tribology International 165, 107247 , 2022 2022 Citations: 58
An exploration of frictional and vibrational behaviors of textured deep groove ball bearing in the vicinity of requisite minimum load KEC Vidyasagar, RK Pandey, D Kalyanasundaram Friction 9 (6), 1749-1765 , 2021 2021 Citations: 54
Laser based micro texturing of freeform surfaces of implants using a Stewart platform KEC Vidyasagar, V Aggarwal, SS Sinha, SK Saha, D Kalyanasundaram Precision Engineering 72, 294-303 , 2021 2021 Citations: 9
Improvement of deep groove ball bearing’s performance using a bionic textured inner race KEC Vidyasagar, RK Pandey, D Kalyanasundaram Journal of Bionic Engineering 18 (4), 974-990 , 2021 2021 Citations: 58
MOST CITED SCHOLAR PUBLICATIONS
Signal to image conversion and convolutional neural networks for physiological signal processing: A review KEC Vidyasagar, KR Kumar, GNKA Sai, M Ruchita, MJ Saikia Ieee Access 12, 66726-66764 , 2024 2024 Citations: 69
Tribodynamic studies of textured gearsets lubricated with fresh and MoS2 blended greases N Gupta, N Tandon, RK Pandey, KEC Vidyasagar, D Kalyanasundaram Tribology International 165, 107247 , 2022 2022 Citations: 58
Improvement of deep groove ball bearing’s performance using a bionic textured inner race KEC Vidyasagar, RK Pandey, D Kalyanasundaram Journal of Bionic Engineering 18 (4), 974-990 , 2021 2021 Citations: 58
An exploration of frictional and vibrational behaviors of textured deep groove ball bearing in the vicinity of requisite minimum load KEC Vidyasagar, RK Pandey, D Kalyanasundaram Friction 9 (6), 1749-1765 , 2021 2021 Citations: 54
Optimization of laser parameters for improved corrosion resistance of nitinol KEC Vidyasagar, A Rana, D Kalyanasundaram Materials and Manufacturing Processes 35 (14), 1661-1669 , 2020 2020 Citations: 39
Tribological and vibration studies of textured spur gear pairs under fully flooded and starved lubrication conditions N Gupta, N Tandon, RK Pandey, KEC Vidyasagar, D Kalyanasundaram Tribology Transactions 63 (6), 1103-1120 , 2020 2020 Citations: 37
Cancer Detection Using Artificial Intelligence: A Paradigm in Early Diagnosis: G. Bulusu et al. G Bulusu, KEC Vidyasagar, M Mudigonda, MJ Saikia Archives of Computational Methods in Engineering 32 (4), 2365-2403 , 2025 2025 Citations: 25
Protein patterning on microtextured polymeric nanobrush templates obtained by nanosecond fiber laser M Verma, A Rana, KEC Vidyasagar, D Kalyanasundaram, S Saha Macromolecular Bioscience 22 (5), 2100454 , 2022 2022 Citations: 10
Laser based micro texturing of freeform surfaces of implants using a Stewart platform KEC Vidyasagar, V Aggarwal, SS Sinha, SK Saha, D Kalyanasundaram Precision Engineering 72, 294-303 , 2021 2021 Citations: 9
Classification of mild and severe adolescent idiopathic scoliosis (AIS) from healthy subjects via a supervised learning model based on electromyogram and ground reaction force … A Sikidar, KEC Vidyasagar, M Gupta, B Garg, D Kalyanasundaram Biocybernetics and Biomedical Engineering 42 (3), 870-887 , 2022 2022 Citations: 6
Performance evaluation of contemporary classifiers for automatic detection of epileptic EEG KEC Vidyasagar, M Moghavvemi, T Prabhat 2015 International Conference on Industrial Instrumentation and Control … , 2015 2015 Citations: 5
Gamified Rehabilitation and Physiotherapy Using MediaPipe for Posture and Hand Gesture Recognition KEC Vidyasagar, GNKA Sai, M Ruchita, MJ Saikia 2024 2nd International Conference on Recent Trends in Microelectronics … , 2024 2024 Citations: 3
Enhanced corrosion resistance of CoCrMo by laser-based surface modification KEC Vidyasagar, D Kalyanasundaram Surface Engineering 40 (1), 100-111 , 2024 2024 Citations: 3
Gaze tracking control system for wheelchair and smart home automation KEC Vidyasagar, GNVS Prasad, MS Raj, S Mahreeen, MJ Saikia 2023 IEEE 19th International Conference on Body Sensor Networks (BSN), 1-4 , 2023 2023 Citations: 3
Design and Development of Wireless Intravenous Multidrug Delivery System KEC Vidyasagar, T Phani, S Sivarasu International Journal of Technology And Engineering System (IJTES) 2 (3 … , 2011 2011 Citations: 3
Simulation and Control Solutions for Accessible Surgical Robotics in Developing Nations KEC Vidyasagar, R Karadula, M Suraram, MJ Saikia 2024 IEEE 20th International Conference on Body Sensor Networks (BSN), 1-4 , 2024 2024 Citations: 2
Design and development of caged ball heart valve using solid works KEC Vidyasagar, R Varma Department of Biomedical engineering , 2013 2013 Citations: 1
A Wearable Hand Exoskeleton with Digital Twin Visualization and Motion Assistance for Rehabilitation Therapy D Suman, HV Chathilla, RP Galenka, B Samudrala, KEC Vidyasagar SoutheastCon 2026, 1-6 , 2026 2026
Vision-Guided Segregation of Biomedical Waste Using AI-Driven Control Architecture KEC Vidyasagar, H Kanduri, VJD Manchikanti, S Yelisetti, BS Edara, ... SoutheastCon 2026, 1-6 , 2026 2026
Design of Orthosis for Ankle Inversion Injuries JK Talari, M Malini, KEC Vidyasagar International Conference on Biomedical Engineering Science and Technology … , 2025 2025
