Koopman-driven real-time sEMG signal decomposition for robotic rehabilitation - uniri-iz-25-116 (2025-2029)

Loss of hand function caused by conditions such as stroke or multiple sclerosis severely limits activities of daily living. Rehabilitation robotics offers effective therapeutic solutions while reducing the need for intensive therapist involvement. Electromyography (EMG)-based robotic rehabilitation provides clear advantages over conventional approaches and open-loop control devices, while soft robotics—drawing inspiration from natural organisms and plants—enables safer and more compliant interaction with the human body.

The proposed research project builds on prior work presented in Koopman-driven grip force prediction through EMG sensing and extends these ideas toward real-time surface electromyography (sEMG) signal decomposition using Koopman operator theory (KOT) and dynamic mode decomposition (DMD). The objective is to identify motor unit (MU) activity and correlate it with grip strength across different grasp types, with a particular focus on real-time implementation. :contentReference[oaicite:0]{index=0}

Koopman operator theory and data-driven DMD provide a powerful framework for decomposing complex EMG dynamics into dominant spatiotemporal components, enabling the extraction of frequency and damping features relevant to neural control. By leveraging these advanced analytical tools, the project seeks to address key limitations of existing methods, particularly in terms of accuracy, interpretability, and real-time applicability.

The project also draws on the principal investigator’s earlier work in soft robotics, including Control of soft robots with inertial dynamics”, which demonstrated the potential of Koopman-based approaches for modeling and control in highly dynamic soft robotic systems. Together, these research directions create a strong foundation for the development of adaptive robotic rehabilitation devices capable of more precise force control and improved responsiveness to patient-specific needs.

Collaborators

Tomislav Bazina
Jelena Srnec Novak
David Liović
Goran Gregov
Igor Mezić (University of California, Santa Barbara, USA)

Main project publications:

Modeling Soft Rehabilitation Actuators: Segmented PRB Formulations with FEM-Based Calibration (Bazina et al., 2026)

UNIRI Project Portal:

Koopman-driven real-time sEMG signal decomposition for robotic rehabilitation

Feb 27, 2026	Call for Papers – MIPRO Robotics 2026
Nov 27, 2025	Launch of the KOT Forum YouTube Channel & Monthly Koopman Seminars

References

2026

Actuators
Modeling Soft Rehabilitation Actuators: Segmented PRB Formulations with FEM-Based Calibration

Tomislav Bazina, David Liović, Jelena Srnec Novak, and Ervin Kamenar

Actuators, 2026

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Soft pneumatic glove actuators for hand rehabilitation require compact, accurate models that can be evaluated in real time. At the same time, high-fidelity finite element (FE) simulations are too slow for iterative design and control. We develop a finite element-based calibration pipeline that combines a dependency-constrained human finger kinematic model with a segmented pseudo-rigid-body (PRB) description of ribbed-bellow soft pneumatic actuators sized to individual fingers. FE models with symmetry and contact generate pressure–pose data for the MCP, PIP, and DIP spans, from which we extract per-segment bending angles and axial elongations, fit simple pressure–kinematics relations, and identify PRB parameters using basin-hopping global optimization. The calibrated PRB reproduces FE flexion–extension trajectories for index and little finger actuators with millimetric accuracy (mean segment positioning errors of approximately 2.3 mm and 0.7 mm), preserves finger-like bending localized in the bellows, and maintains negligible compression of inter-joint links (below 1.2%). The pressure–bend and pressure–elongation maps achieve near-unity adjusted R^2, and the PRB forward kinematics evaluates complete pressure trajectories in less than half a millisecond, compared with several hours for the corresponding FE simulations. This pipeline provides a practical route from detailed FE models to controller-ready reduced-order surrogates for design-space exploration and patient-specific control of soft rehabilitation actuators.
@article{bazina2026modeling, title = {Modeling Soft Rehabilitation Actuators: Segmented PRB Formulations with FEM-Based Calibration}, author = {Bazina, Tomislav and Liovi{\'c}, David and Srnec Novak, Jelena and Kamenar, Ervin}, journal = {Actuators}, year = {2026}, volume = {15}, number = {1}, pages = {22}, keywords = {soft pneumatic actuator (SPA); finger rehabilitation; pseudo-rigid-body (PRB) model; finite element method (FEM); hand kinematics; reduced-order modeling; patient-specific design}, doi = {10.3390/act15010022}, }

Collaborators

Main project publications:

UNIRI Project Portal:

Related news

References

2026