reinforcement learning

Hidden Brain State-based Internal Evaluation Using Kernel Inverse Reinforcement Learning in Brain-machine Interfaces
Hidden Brain State-based Internal Evaluation Using Kernel Inverse Reinforcement Learning in Brain-machine Interfaces 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Reinforcement learning (RL)-based brain machine interfaces (BMIs) assist paralyzed people in controlling neural prostheses without the need for real limb movement as supervised signals. The design of reward signal significantly… read more

An Efficient Framework for Personalizing EMG-Driven Musculoskeletal Models Based on Reinforcement Learning
An Efficient Framework for Personalizing EMG-Driven Musculoskeletal Models Based on Reinforcement Learning 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
This study aimed to develop a novel framework to quickly personalize electromyography (EMG)-driven musculoskeletal models (MMs) as efferent neural interfaces for upper limb prostheses. Our framework adopts a generic upper-limb… read more
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Closed-Loop Deep Brain Stimulation With Reinforcement Learning and Neural Simulation
Closed-Loop Deep Brain Stimulation With Reinforcement Learning and Neural Simulation 480 270 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

This article presents a significant advancement in the field of deep brain stimulation (DBS) through the development of a closed-loop system that integrates reinforcement learning (RL) and neural simulation techniques.…

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Closed-Loop Deep Brain Stimulation With Reinforcement Learning and Neural Simulation
Closed-Loop Deep Brain Stimulation With Reinforcement Learning and Neural Simulation 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Deep Brain Stimulation (DBS) is effective for movement disorders, particularly Parkinson’s disease (PD). However, a closed-loop DBS system using reinforcement learning (RL) for automatic parameter tuning, offering enhanced energy efficiency… read more

Brain Network Evaluation by Functional-Guided Effective Connectivity Reinforcement Learning Method Indicates Therapeutic Effect for Tinnitus
Brain Network Evaluation by Functional-Guided Effective Connectivity Reinforcement Learning Method Indicates Therapeutic Effect for Tinnitus 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Using functional connectivity (FC) or effective connectivity (EC) alone cannot effectively delineate brain networks based on functional magnetic resonance imaging (fMRI) data, limiting the understanding of the mechanism of tinnitus… read more

Hindsight Experience Replay Improves Reinforcement Learning for Control of a MIMO Musculoskeletal Model of the Human Arm
Author(s)3: Douglas C. Crowder, Robert F. Kirsch, Jessica Abreu
Hindsight Experience Replay Improves Reinforcement Learning for Control of a MIMO Musculoskeletal Model of the Human Arm 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

High-level spinal cord injuries often result in paralysis of all four limbs, leading to decreased patient independence and quality of life. Coordinated functional electrical stimulation (FES) of paralyzed muscles can…

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Clustering Neural Patterns in Kernel Reinforcement Learning Assists Fast Brain Control in Brain-Machine Interfaces

Clustering Neural Patterns in Kernel Reinforcement Learning Assists Fast Brain Control in Brain-Machine Interfaces
Author(s)3: Xiang Zhang, Camilo Libedinsky, Rosa So, Jose C. Principe, Yiwen Wang
Clustering Neural Patterns in Kernel Reinforcement Learning Assists Fast Brain Control in Brain-Machine Interfaces 780 447 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

     Neuroprosthesis enables the brain control on the external devices purely using neural activity for paralyzed people. Supervised learning decoders recalibrate or re-fit the discrepancy between the desired target and…

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