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Satyam Kumar

5 accepted papers

2026

Characterizing Expectation Mismatch in a Brain-Controlled Upper-Body Rehabilitation Exoskeleton

Satyam Kumar, Kanishka Mitra, Deland Hu Liu, Hussein Alawieh, Frigyes Samuel Racz, Stefano Dalla Gasperina +2
RA-L 2026

Robot-assisted therapy has long promised to advance stroke rehabilitation by delivering intensive and personalized training, yet its clinical impact remains limited. Closing the sensorimotor loop with brain-computer interfaces offers a better strategy than passive mobilization, directly linking user

Cited by 1Source ↗Scholar ↗
2026

Real-Time Decoding of Movement Onset and Offset for Brain-Controlled Rehabilitation Exoskeleton

Kanishka Mitra, Satyam Kumar, Frigyes Samuel Racz, Deland Hu Liu, Ashish Deshpande, José del R. Millán
ICRA 2026poster

Robot-assisted therapy can deliver high-dose, task-specific training after neurologic injury, but most systems act primarily at the limb level - engaging the impaired neural circuits only indirectly - which remains a key barrier to truly contingent, neuroplasticity-targeted rehabilitation. We addres…

Cited by 0Source ↗PDF ↗Scholar ↗
2023

Characterizing the Onset and Offset of Motor Imagery During Passive Arm Movements Induced by an Upper-Body Exoskeleton

Kanishka Mitra, Frigyes Samuel Racz, Satyam Kumar, Ashish D. Deshpande, José Del R. Millán
IROS 2023poster

Two distinct technologies have gained attention lately due to their prospects for motor rehabilitation: robotics and brain-machine interfaces (BMIs). Harnessing their combined efforts is a largely uncharted and promising direction that has immense clinical potential. However, a significant challenge…

Cited by 5Source ↗Scholar ↗
2023

CogniDaVinci: Towards Estimating Mental Workload Modulated by Visual Delays During Telerobotic Surgery - An EEG-based Analysis

Satyam Kumar, Deland H. Liu, Frigyes S. Racz, Manuel Retana, Susheela Sharma, Fumiaki Iwane +5
ICRA 2023poster

Communication latency in any delicate telerobotic operation (such as remote surgery over distance) would impose a significant challenge due to the temporal degradation of visual perception and can substantially affect the outcomes. Less is known, however, about the neurophysiological basis of how op…

Cited by 4Source ↗Scholar ↗
2020

Formulating Divergence Framework for Multiclass Motor Imagery EEG Brain Computer Interface

Satyam Kumar, Tharun Kumar Reddy, Vipul Arora, Laxmidhar Behera
ICASSP 2020accepted

The ubiquitous presence of non-stationarities in the EEG signals significantly perturb the feature distribution thus deteriorating the performance of Brain Computer Interface. In this work, a novel method is proposed based on Joint Approximate Diagonalization (JAD) to optimize stationarity for multi…

Cited by 0Source ↗Scholar ↗