Sivakumar Rajagopal
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Sivakumar Rajagopal has a total of 176 co-authors. Here are the top co-authors by number of shared publications:
Rahul Soangra
Crean College of Health and Behavioral Sciences, Chapman University, Orange, California
7 shared publications- Rahul Soangra
Crean College of Health and Behavioral Sciences, Chapman University, Orange, CA 92866, USA
5 shared publications - Seok-Bum Ko
University of Saskatchewan
5 shared publications Harshit Poddar
School of Electronics Engineering (SENSE), Vellore Institute of Technology, Vellore, India 632014
4 shared publications- Dimiter Velev
University of National and World Economy, Sofia, Bulgaria
3 shared publications Michael Shiraishi
Chapman University, Orange, CA, USA
3 shared publications
Latest Publications
- Open Access
- 31 August 2026
- Published by Elsevier in Results in Optics
- Vol. 24
Numerical modeling and performance optimization of a phase-matched D-shaped optical fiber SPR biosensor for multi-type cancer cell detection
- 31 August 2026
- Published by Elsevier in Results in Optics
- Vol. 24
Open AccessNumerical modeling and performance optimization of a phase-matched D-shaped optical fiber SPR biosensor for multi-type cancer cell detection
- 1 May 2026
- Published by Springer Nature
- p. 133-141
AI-Driven Predictive Maintenance for Green Data Centers: A Federated Learning Approach to Reduce Carbon Footprint
- 1 May 2026
- Published by Springer Nature
- p. 133-141
AI-Driven Predictive Maintenance for Green Data Centers: A Federated Learning Approach to Reduce Carbon Footprint
- 1 May 2026
- Published by Springer Nature
- p. 67-74
Real-Time Healthcare Environment Monitoring Through Deep Learning: A Multi-modal Sensor Fusion Implementation
- 1 May 2026
- Published by Springer Nature
- p. 67-74
Real-Time Healthcare Environment Monitoring Through Deep Learning: A Multi-modal Sensor Fusion Implementation
- Open Access
- 1 February 2026
- Published by Institute of Advanced Engineering and Science in Indonesian Journal of Electrical Engineering and Computer Science
- Vol. 41  (2)
An investigation of different low-power circuits and enhanced energy efficiency in medical applications
This research investigates the application of low-power circuits in medical devices and imaging systems. The primary goal is to address the growing demand for energy-efficient solutions in medical applications. There is an increasing need for energy-efficient solutions due to the development of medical technologies, particularly implanted and battery-operated medical devices. This paper explores the integration of adiabatic logic as a critical enabler for achieving low power consumption in medical applications. The study looks into different low-power circuit designs and technologies that optimize power usage without sacrificing performance. Adiabatic circuits offer a promising substitute for conventional circuitry in low-energy design. The research examines several low-power circuit designs and technologies that maximize power efficiency without compromising functionality. In low-energy design, adiabatic circuits present a possible alternative to traditional circuitry. Adiabatic logic aims to create energy-efficient digital circuits that consume significantly less power than conventional complementary metal-oxide-semiconductor (CMOS) circuits. We accomplish this by recovering and recycling energy that would otherwise be lost as heat and carefully controlling energy flows during switching events. Adiabatic logic is precious in battery-operated and energy-constrained devices.
- 1 February 2026
- Published by Institute of Advanced Engineering and Science in Indonesian Journal of Electrical Engineering and Computer Science
- Vol. 41  (2)
Open AccessAn investigation of different low-power circuits and enhanced energy efficiency in medical applications
This research investigates the application of low-power circuits in medical devices and imaging systems. The primary goal is to address the growing demand for energy-efficient solutions in medical applications. There is an increasing need for energy-efficient solutions due to the development of medical technologies, particularly implanted and battery-operated medical devices. This paper explores the integration of adiabatic logic as a critical enabler for achieving low power consumption in medical applications. The study looks into different low-power circuit designs and technologies that optimize power usage without sacrificing performance. Adiabatic circuits offer a promising substitute for conventional circuitry in low-energy design. The research examines several low-power circuit designs and technologies that maximize power efficiency without compromising functionality. In low-energy design, adiabatic circuits present a possible alternative to traditional circuitry. Adiabatic logic aims to create energy-efficient digital circuits that consume significantly less power than conventional complementary metal-oxide-semiconductor (CMOS) circuits. We accomplish this by recovering and recycling energy that would otherwise be lost as heat and carefully controlling energy flows during switching events. Adiabatic logic is precious in battery-operated and energy-constrained devices.
- 30 December 2025
- Published by Springer Nature
- p. 57-65
Precision Strontium Detection in Water: A Machine Learning Augmented Flame Photometric Approach
- 30 December 2025
- Published by Springer Nature
- p. 57-65
Precision Strontium Detection in Water: A Machine Learning Augmented Flame Photometric Approach
- 30 December 2025
- Published by Springer Nature
- p. 67-78
Comparative Analysis of Random Forest and SVM for EMG-Based Gesture Recognition
- 30 December 2025
- Published by Springer Nature
- p. 67-78
Comparative Analysis of Random Forest and SVM for EMG-Based Gesture Recognition
- 30 December 2025
- Published by Springer Nature
- p. 89-98
Data-Driven Insights from High-Dimensional Time-Series Signals: A Comprehensive Analysis Approach
- 30 December 2025
- Published by Springer Nature
- p. 89-98
Data-Driven Insights from High-Dimensional Time-Series Signals: A Comprehensive Analysis Approach
- 30 December 2025
- Published by Springer Nature
- p. 79-87
Comparative Study of CNN and LSTM Deep Learning Models for EMG Signals for Gesture Recognition
- 30 December 2025
- Published by Springer Nature
- p. 79-87
Comparative Study of CNN and LSTM Deep Learning Models for EMG Signals for Gesture Recognition
- 3 October 2025
- Published by Springer Nature in Signal, Image and Video Processing
- Vol. 19  (14) , 1-9
EEG-based biometric authentication: advancing security through motor imagery and deep learning
- 3 October 2025
- Published by Springer Nature in Signal, Image and Video Processing
- Vol. 19  (14) , 1-9
EEG-based biometric authentication: advancing security through motor imagery and deep learning
- 28 July 2025
- Published by SAGE Publications in Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Vol. 69  (1) , 1553-1558
The Impact of Non-Athletic, Flat-Soled Sneakers on Gait Kinematics: A Comparative Analysis with Socks
This study investigates the kinematic effects of non-athletic, flat-soled sneakers on lower extremity joints during walking. Ten healthy gym-goers (24.4 ± 1.7 years) underwent treadmill gait analysis under two conditions: wearing non-athletic sneakers and walking with only socks. Gait was captured using the Gait Real-time Analysis and Interactive Lab (GRAIL). Dependent variables included cadence, support times, and stride length. Walking with socks significantly increased cadence ( p < .0001) and single support time ( p = .0103), and decreased initial ( p = .018), terminal ( p = .0056), and total double support times ( p = .0092). No significant difference in stride length was observed. These findings suggest non-athletic sneakers may impair proprioception and balance compared to walking in socks. Further research should explore how footwear types influence gait and postural stability.
- 28 July 2025
- Published by SAGE Publications in Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Vol. 69  (1) , 1553-1558
The Impact of Non-Athletic, Flat-Soled Sneakers on Gait Kinematics: A Comparative Analysis with Socks
This study investigates the kinematic effects of non-athletic, flat-soled sneakers on lower extremity joints during walking. Ten healthy gym-goers (24.4 ± 1.7 years) underwent treadmill gait analysis under two conditions: wearing non-athletic sneakers and walking with only socks. Gait was captured using the Gait Real-time Analysis and Interactive Lab (GRAIL). Dependent variables included cadence, support times, and stride length. Walking with socks significantly increased cadence ( p < .0001) and single support time ( p = .0103), and decreased initial ( p = .018), terminal ( p = .0056), and total double support times ( p = .0092). No significant difference in stride length was observed. These findings suggest non-athletic sneakers may impair proprioception and balance compared to walking in socks. Further research should explore how footwear types influence gait and postural stability.