electroencephalography (EEG)

Learning Invariant Patterns Based on a Convolutional Neural Network and Big Electroencephalography Data for Subject-Independent P300 Brain-Computer Interfaces

Author(s): Wei Gao, Tianyou Yu, Jin-Gang Yu, Zhenghui Gu, Kendi Li, Yong Huang, Yuanqing Li, Zhu Liang Yu
Learning Invariant Patterns Based on a Convolutional Neural Network and Big Electroencephalography Data for Subject-Independent P300 Brain-Computer Interfaces 540 430 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

A brain-computer interface (BCI) measures and analyzes brain activity and converts this activity into computer commands to control external devices. In contrast to traditional BCIs that require a subject-specific calibration…

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Utilizing high-density electroencephalography and motion capture technology to characterize sensorimotor integration while performing complex actions

Author(s): Edward G. Freedman, John J. Foxe, Kevin A. Mazurek, Nicholas Abraham, David Richardson
Utilizing high-density electroencephalography and motion capture technology to characterize sensorimotor integration while performing complex actions 913 548 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Studies of sensorimotor integration often use sensory stimuli that require a simple motor response, such as a reach or a grasp. Recent advances in neural recording techniques, motion capture technologies,…

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Directed Functional Connectivity in Fronto-Centroparietal Circuit Correlates With Motor Adaptation in Gait Training

Directed Functional Connectivity in Fronto-Centroparietal Circuit Correlates With Motor Adaptation in Gait Training

Author(s): Vahab Youssofzadeh, Damiano Zanotto, KongFatt Wong-Lin, Sunil K. Agrawal, Girijesh Prasad
Directed Functional Connectivity in Fronto-Centroparietal Circuit Correlates With Motor Adaptation in Gait Training 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Lower-extremity robotic exoskeletons are used in gait rehabilitation to achieve functional motor recovery. To date, little is known about how gait training and post-training are characterized in brain signals and…

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Using Actual and Imagined Walking Related Desynchronization Features in a BCI

Author(s): Marianne Severens, Monica Perusquia-Hernandez, Bart Nienhuis, Jason Farquhar, Jacques Duysens
Using Actual and Imagined Walking Related Desynchronization Features in a BCI 780 275 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Recently, brain–computer interface (BCI) research has extended to investigate its possible use in motor rehabilitation. Most of these investigations have focused on the upper body. Only few studies consider gait…

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