motor imagery

An Adaptive Hybrid Brain Computer Interface for Hand Function Rehabilitation of Stroke Patients

An Adaptive Hybrid Brain Computer Interface for Hand Function Rehabilitation of Stroke Patients 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Motor imagery (MI) based brain computer interface (BCI) has been extensively studied to improve motor recovery for stroke patients by inducing neuroplasticity. However, due to the lower spatial resolution and… read more

A Temporal-Spectral-based Squeeze-and-Excitation Feature Fusion Network for Motor Imagery EEG Decoding

Author(s)3: Fangang Meng, Jingyu Liu, Lianghui Guo, Yang Li, Yu Liu
A Temporal-Spectral-based Squeeze-and-Excitation Feature Fusion Network for Motor Imagery EEG Decoding 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Motor imagery (MI) electroencephalography (EEG) decoding plays an important role in brain-computer interface (BCI), which enables motor-disabled patients to communicate with the outside world via external devices. Recent deep learning…

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Decoding Finger Tapping with the Affected Hand in Chronic Stroke Patients During Motor Imagery and Execution

Author(s)3: Minji Lee, Ji-Hoon Jeong, Yun-Hee Kim, Seong-Whan Lee
Decoding Finger Tapping with the Affected Hand in Chronic Stroke Patients During Motor Imagery and Execution 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

In stroke rehabilitation, motor imagery based on a brain–computer interface is an extremely useful method to control an external device and utilize neurofeedback. Many studies have reported on the classification…

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Android Feedback-based Training modulates Sensorimotor Rhythms during Motor Imagery

Author(s)3: Christian I. Penaloza, Maryam Alimardani, Shuichi Nishio
Android Feedback-based Training modulates Sensorimotor Rhythms during Motor Imagery 780 411 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

   EEG-based brain computer interface (BCI) systems have demonstrated potential to assist patients with devastating motor paralysis conditions. However, there is great interest in shifting the BCI trend toward applications…

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Open Access Dataset for EEG+NIRS Single-Trial Classification

Open Access Dataset for EEG+NIRS Single-Trial Classification

Author(s)3: Jaeyoung Shin, Alexander von Luhmann, Benjamin Blankertz, Do-Won Kim, Jichai Jeong, Han-Jeong Hwang, Klaus-Robert Müller
Open Access Dataset for EEG+NIRS Single-Trial Classification 780 476 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

       We provide an open access dataset for hybrid brain-computer interfaces (BCIs) using electroencephalography (EEG) and near-infrared spectroscopy (NIRS). For this, we conducted two BCI experiments (left vs. right hand…

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A Stimulus-Independent Hybrid BCI Based on Motor Imagery and Somatosensory Attentional Orientation

A Stimulus-Independent Hybrid BCI Based on Motor Imagery and Somatosensory Attentional Orientation

Author(s)3: Lin Yao, Xinjun Sheng, Dingguo Zhang, Ning Jiang, Natalie Mrachacz-Kersting, Xiangyang Zhu, Dario Farina
A Stimulus-Independent Hybrid BCI Based on Motor Imagery and Somatosensory Attentional Orientation 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

       Distinctive EEG signals from the motor and somatosensory cortex are generated during mental tasks of motor imagery (MI) and somatosensory attentional orientation (SAO). In this study, we hypothesize that…

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