Classification algorithms

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

Improved Transfer Learning for Detecting Upper-Limb Movement Intention Using Mechanical Sensors in an Exoskeletal Rehabilitation System
Improved Transfer Learning for Detecting Upper-Limb Movement Intention Using Mechanical Sensors in an Exoskeletal Rehabilitation System 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
The objective of this study was to propose a novel strategy for detecting upper-limb motion intentions from mechanical sensor signals using deep and heterogeneous transfer learning techniques. Three sensor types,… read more

An Ensemble Learning Algorithm for Cognitive Evaluation by an Immersive Virtual Reality Supermarket
An Ensemble Learning Algorithm for Cognitive Evaluation by an Immersive Virtual Reality Supermarket 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Early screening for Mild Cognitive Impairment (MCI) is crucial in delaying cognitive deterioration and treating dementia. Conventional neuropsychological tests, commonly used for MCI detection, often lack ecological validity due to… read more

EMG-based Multi-User Hand Gesture Classification via Unsupervised Transfer Learning Using Unknown Calibration Gestures
EMG-based Multi-User Hand Gesture Classification via Unsupervised Transfer Learning Using Unknown Calibration Gestures 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
The poor generalization performance and heavy training burden of the gesture classification model contribute as two main barriers that hinder the commercialization of sEMG-based human-machine interaction (HMI) systems. To overcome… read more

Cross-Comparison of Three Electromyogram Decomposition Algorithms Assessed With Experimental and Simulated Data
Author(s)3: Chenyun Dai, Yejin Li, Anita Christie, Paolo Bonato, Kevin C. McGill, Edward A. Clancy
Cross-Comparison of Three Electromyogram Decomposition Algorithms Assessed With Experimental and Simulated Data 556 235 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Abstract The reliability of clinical and scientific information provided by algorithms that automatically decompose the electromyogram (EMG) depends on the algorithms’ accuracies. We used experimental and simulated data to assess…

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