Koopman-Based Model Predictive Control of Functional Electrical Stimulation for Ankle Dorsiflexion and Plantarflexion Assistance
Functional Electrical Stimulation (FES) can be an effective tool to augment paretic muscle function and restore normal ankle function. Our approach incorporates a real-time, data-driven Model Predictive Control (MPC) scheme built upon a Koopman operator theory (KOT) framework. This framework adeptly...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/10929647/ |
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| author | Mayank Singh Noor Hakam Trisha M. Kesar Nitin Sharma |
| author_facet | Mayank Singh Noor Hakam Trisha M. Kesar Nitin Sharma |
| author_sort | Mayank Singh |
| collection | DOAJ |
| description | Functional Electrical Stimulation (FES) can be an effective tool to augment paretic muscle function and restore normal ankle function. Our approach incorporates a real-time, data-driven Model Predictive Control (MPC) scheme built upon a Koopman operator theory (KOT) framework. This framework adeptly captures the complex nonlinear dynamics of ankle motion in a linearized form, enabling the application of linear control approaches for highly nonlinear FES-actuated dynamics. Our method accurately predicts the FES-induced ankle movements, accounting for nonlinear muscle actuation dynamics, including the muscle activation for both plantarflexors and dorsiflexors (Tibialis Anterior (TA)). The linear prediction model derived through KOT allowed the formulation of the MPC problem with linear state space dynamics, enhancing the FES-driven control’s real-time feasibility, precision, and adaptability. We demonstrate the effectiveness and applicability of our approach through comprehensive simulations and experimental trials, including three participants with no disability and a participant with Multiple Sclerosis. Our findings highlight the potential of a KOT-based MPC approach for FES-based gait assistance that offers effective and personalized assistance for individuals with gait impairment conditions. |
| format | Article |
| id | doaj-art-7aee9d993a8245fe9d82916a9630c9fc |
| institution | OA Journals |
| issn | 1534-4320 1558-0210 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj-art-7aee9d993a8245fe9d82916a9630c9fc2025-08-20T01:54:40ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1534-43201558-02102025-01-01331252126210.1109/TNSRE.2025.355193310929647Koopman-Based Model Predictive Control of Functional Electrical Stimulation for Ankle Dorsiflexion and Plantarflexion AssistanceMayank Singh0https://orcid.org/0009-0001-4163-9041Noor Hakam1https://orcid.org/0009-0002-5945-9513Trisha M. Kesar2Nitin Sharma3https://orcid.org/0000-0003-1872-0156Department of Electrical Engineering, North Carolina State University, Raleigh, NC, USAUNC/NC State Lampe Joint Department of Biomedical Engineering, NC State University, Raleigh, NC, USADepartment of Rehabilitation Medicine, Division of Physical Therapy, Emory University School of Medicine, Atlanta, GA, USAUNC/NC State Lampe Joint Department of Biomedical Engineering, NC State University, Raleigh, NC, USAFunctional Electrical Stimulation (FES) can be an effective tool to augment paretic muscle function and restore normal ankle function. Our approach incorporates a real-time, data-driven Model Predictive Control (MPC) scheme built upon a Koopman operator theory (KOT) framework. This framework adeptly captures the complex nonlinear dynamics of ankle motion in a linearized form, enabling the application of linear control approaches for highly nonlinear FES-actuated dynamics. Our method accurately predicts the FES-induced ankle movements, accounting for nonlinear muscle actuation dynamics, including the muscle activation for both plantarflexors and dorsiflexors (Tibialis Anterior (TA)). The linear prediction model derived through KOT allowed the formulation of the MPC problem with linear state space dynamics, enhancing the FES-driven control’s real-time feasibility, precision, and adaptability. We demonstrate the effectiveness and applicability of our approach through comprehensive simulations and experimental trials, including three participants with no disability and a participant with Multiple Sclerosis. Our findings highlight the potential of a KOT-based MPC approach for FES-based gait assistance that offers effective and personalized assistance for individuals with gait impairment conditions.https://ieeexplore.ieee.org/document/10929647/Functional electrical stimulation (FES)extended dynamic mode decomposition (EDMD)model predictive control (MPC)gait assistancenonlinear dynamics |
| spellingShingle | Mayank Singh Noor Hakam Trisha M. Kesar Nitin Sharma Koopman-Based Model Predictive Control of Functional Electrical Stimulation for Ankle Dorsiflexion and Plantarflexion Assistance IEEE Transactions on Neural Systems and Rehabilitation Engineering Functional electrical stimulation (FES) extended dynamic mode decomposition (EDMD) model predictive control (MPC) gait assistance nonlinear dynamics |
| title | Koopman-Based Model Predictive Control of Functional Electrical Stimulation for Ankle Dorsiflexion and Plantarflexion Assistance |
| title_full | Koopman-Based Model Predictive Control of Functional Electrical Stimulation for Ankle Dorsiflexion and Plantarflexion Assistance |
| title_fullStr | Koopman-Based Model Predictive Control of Functional Electrical Stimulation for Ankle Dorsiflexion and Plantarflexion Assistance |
| title_full_unstemmed | Koopman-Based Model Predictive Control of Functional Electrical Stimulation for Ankle Dorsiflexion and Plantarflexion Assistance |
| title_short | Koopman-Based Model Predictive Control of Functional Electrical Stimulation for Ankle Dorsiflexion and Plantarflexion Assistance |
| title_sort | koopman based model predictive control of functional electrical stimulation for ankle dorsiflexion and plantarflexion assistance |
| topic | Functional electrical stimulation (FES) extended dynamic mode decomposition (EDMD) model predictive control (MPC) gait assistance nonlinear dynamics |
| url | https://ieeexplore.ieee.org/document/10929647/ |
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