Papers
7
Total Citations
115
H-Index
6
About
Innokentiy Kastalskiy is a leading researcher at the intersection of neural computation, biomechatronics, and biomimetic robotics. His work fundamentally bridges biological signal processing with robotic control, most notably through the development of a Spiking Neural Network (SNN) for sEMG feature extraction (2015, 37 citations), which pioneered a hybrid neural architecture for classifying muscle activity. This foundational work led to his creation of a neuromuscular interface (2018, 13 citations) that fuses EMG, EEG, and kinematic data for intuitive control of external robotic devices, including commercial systems. Kastalskiy’s impact extends to underwater robotics, where his reviews on swimming central pattern generators (2022, 20 citations) and control of movement in animals, simulations, and robots (2023, 20 citations) have become key references for the field. He has also advanced rehabilitation technology, developing myoelectric control systems for lower limb exoskeletons to retrain motion deficiencies (2015, 8 citations). By combining command-proportional control with biological signals, Kastalskiy’s work is driving the next generation of seamless human-robot interaction, from assistive devices to biomorphic swimmers.
Research Focus
Key Achievements
Top Papers
- 1A Spiking Neural Network in sEMG Feature Extraction37 citations · 2015
- 2Toward biomorphic robotics: A review on swimming central pattern generators20 citations · 2022
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- 5A Neuromuscular Interface for Robotic Devices Control13 citations · 2018
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- 7Modeling Biomorphic Robotic Fish Swimming: Simulations and Experiments3 citations · 2022