Transactions on Neural Systems and Rehabilitation Engineering
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Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces
Transfer learning makes use of data or knowledge in one problem to help solve a different, yet related, problem. It is particularly useful in brain-computer interfaces (BCIs), for coping with variations among different subjects and/or tasks. This paper considers offline...
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Posted on 8 MAY 2020
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Compact and Low-Power Neural Spike Compression Using Undercomplete Autoencoders
Implantable microsystems that collect and transmit neural data are becoming very useful entities in the field of neuroscience. Limited by high data rates, on-chip compression is often required to transmit the recorded data without causing power dissipation at levels that...
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Posted on 22 AUG 2019
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Age-Related Changes in Vibro-Tactile EEG Response and Its Implications in BCI Applications: A Comparison Between Older and Younger Populations
The rapid increase in the number of older adults around the world is accelerating research in applications to support age-related conditions, such as brain–computer interface (BCI) applications for post-stroke neurorehabilitation. The signal processing algorithms for electroencephalogram (EEG) and other physiological...
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Posted on 24 APR 2019
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Neurofeedback Control in Parkinsonian Patients Using Electrocorticography Signals Accessed Wirelessly With a Chronic, Fully Implanted Device
Preeya Khanna, Nicole C. Swann, Coralie de Hemptinne, Svjetlana Miocinovic, Andrew Miller, Philip A. Starr, Jose M. Carmena
Parkinson’s disease (PD) is characterized by motor symptoms such as rigidity and bradykinesia that prevent normal movement. Beta band oscillations (13-30 Hz) in neural local field potentials (LFPs) have been associated with these motor symptoms. Here, three PD patients implanted...
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Posted on 2 OCT 2017