Soheil Borhani

University of Tennessee at Knoxville, Knoxville College

Papers

Total Citations

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About

Soheil Borhani is a researcher at the forefront of Brain-Machine Interfaces (BMI), with a focused interest in translating neural signals into real-world robotic control. His work centers on developing intuitive, non-invasive systems that bridge the gap between human intention and machine action, particularly for assistive and rehabilitative technologies. Borhani’s major contributions include pioneering a sequence-based control paradigm for robotic arms, enabling more complex, multi-step movements directly from brain activity. He has also advanced the field of social robotics by integrating real-time BMI with gesture control, creating systems where a user’s neural commands can drive a social robot’s actions. This work, detailed in his most-cited paper (10 citations), demonstrates promising results for forward and feedback control consistent with human intent. By proposing novel neurofeedback-based BCI systems, Borhani’s research holds significant promise for enhancing patient care and advancing neurorehabilitation, offering a pathway toward more natural and effective human-machine interaction for individuals with motor impairments.