Asynchronous decoding of finger movements from ECoG signals using long-range dependencies conditional random fields
Author:
Publisher
IOP Publishing
Subject
Cellular and Molecular Neuroscience,Biomedical Engineering
Link
http://stacks.iop.org/1741-2552/13/i=3/a=036017/pdf
Reference26 articles.
1. A brain–computer interface using electrocorticographic signals in humans
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4. Neural correlates of learning in an electrocorticographic motor-imagery brain-computer interface
5. An electrocorticographic BCI using code-based VEP for control in video applications: a single-subject study
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1. The role of distinct ECoG frequency features in decoding finger movement;Journal of Neural Engineering;2023-11-23
2. ConvNets for Electroencephalographic Decoding of Attempted Arm and Hand Movements of People with Spinal Cord Injury;Advanced Intelligent Systems;2023-09-13
3. Fast and accurate decoding of finger movements from ECoG through Riemannian features and modern machine learning techniques;Journal of Neural Engineering;2022-02-01
4. Accurate Offline Asynchronous Detection of Individual Finger Movement From Intracranial Brain Signals Using a Novel Multiway Approach;IEEE Transactions on Biomedical Engineering;2021-07
5. Electrocorticographic signals classification for brain computer interfaces using stacked-autoencoders;Applications of Machine Learning 2020;2020-08-20
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