Training data

Improving the Performance of Individually Calibrated SSVEP Classification by Rhythmic Entrainment Source Separation
Improving the Performance of Individually Calibrated SSVEP Classification by Rhythmic Entrainment Source Separation 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Objective: The supervised decoding algorithms of Steady-State Visual Evoked Potentials (SSVEP) have achieved remarkable performance with sufficient training data. However, these methods have typically failed to achieve acceptable performance in… 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

Deep Pinsker and James-Stein Neural Networks for Decoding Motor Intentions from Limited Data
Author(s)3: Marko Angjelichinoski, Mohammadreza Soltani, John Choi, Bijan Pesaran, Vahid Tarokh
Deep Pinsker and James-Stein Neural Networks for Decoding Motor Intentions from Limited Data 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Non-parametric regression has been shown to be useful in extracting relevant features from Local Field Potential (LFP) signals for decoding motor intentions. Yet, in many instances, brain-computer interfaces (BCIs) rely…

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Mining Within-Trial Oscillatory Brain Dynamics to Address the Variability of Optimized Spatial Filters

Mining Within-Trial Oscillatory Brain Dynamics to Address the Variability of Optimized Spatial Filters
Author(s)3: Andreas Meinel, Henrich Kolkhorst, Michael Tangermann
Mining Within-Trial Oscillatory Brain Dynamics to Address the Variability of Optimized Spatial Filters 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

   Data-driven spatial filtering algorithms optimize scores, such as the contrast between two conditions to extract oscillatory brain signal components. Most machine learning approaches for the filter estimation, however, disregard…

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