motor imagery

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…

read more

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…

read more

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…

read more
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…

read more
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…

read more

Subscribe for Updates

Join our mailing list to receive the latest news and updates.

Subscribe Now
IEEE Engineering in Medicine & Biology Society Logo

TNSRE serves the community of biomedical engineers and clinical researchers who work at the intersection of neuroscience and physical medicine. We publish novel approaches and technologies for better understanding neural systems, human movement, and the relationships between them, with a focus on assistive devices that improve life for patients, for practicing clinicians, and for everyday use.

IEEE Logo

© Copyright IEEE – All rights reserved. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

Search this website