Papers

12

Total Citations

135

H-Index

5

About

Balakrishna Gokaraju is a researcher whose work spans biomedical signal processing, human-machine interfaces, and autonomous robotics systems. He is perhaps best known for his pioneering contributions to surface electromyography (sEMG) signal classification, where his studies on hand gesture recognition and physical action classification using energy and time-domain features have collectively garnered over 80 citations, establishing him as a notable voice in assistive technology research. His 2023 contribution, EMAHA-DB1, introduced a comprehensive multi-channel sEMG dataset capturing 22 activities of daily living across 25 subjects, providing the research community with a valuable benchmark resource for rehabilitation and exoskeleton applications. Gokaraju's work is deeply motivated by real-world impact — helping individuals with limb disabilities and gait disorders regain independence through robot-assisted rehabilitation. Beyond biomedical engineering, he has expanded his research into autonomous indoor robotics, exploring sensor fusion, YOLOv5-based object detection, and collision avoidance frameworks, demonstrating a versatile and applied engineering perspective. His more recent forays into digital twin technology and human-robot collaboration further reflect his ambition to bridge cutting-edge simulation tools with practical manufacturing and rehabilitation contexts.

Research Focus

Key Achievements

5
H-Index
12
Papers
135
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Classification of sEMG signals of hand gestures based on energy features
42 citations · 2021
📈 Most Prolific Year: 2024 (4 Papers)
🤝 Key Collaborators: 36
🏛 Institutions: North Carolina Agricultural and Technical State University, University of West Alabama

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 17 days ago