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"We convert EMGs into continuous handwriting traces and into discretely decoded font characters. For this purpose, we use Wiener and Kalman filters, and machine learning algorithms." https://t.co/uM3e9gQy5m
Brain–Computer Interface Research
Overview of attention for book
Table of Contents
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Altmetric BadgeBook Overview
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Altmetric BadgeChapter 1 Introduction
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Altmetric BadgeChapter 2 Generating Handwriting from Multichannel Electromyographic Activity
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Altmetric BadgeChapter 3 Neural Decoding of Upper Limb Movements Using Electroencephalography
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Altmetric BadgeChapter 4 Restoring Functional Reach-to-Grasp in a Person with Chronic Tetraplegia Using Implanted Functional Electrical Stimulation and Intracortical Brain-Computer Interfaces
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Altmetric BadgeChapter 5 Towards Speech Synthesis from Intracranial Signals
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Altmetric BadgeChapter 6 Neural Decoding of Attentional Selection in Multi-speaker Environments Without Access to Clean Sources
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Altmetric BadgeChapter 7 Goal-Directed BCI Feedback Using Cortical Microstimulation
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Altmetric BadgeChapter 8 Neuromotor Recovery Based on BCI, FES, Virtual Reality and Augmented Feedback for Upper Limbs
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Altmetric BadgeChapter 9 A Dynamic Window SSVEP-Based Brain-Computer Interface System Using a Spatio-temporal Equalizer
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Altmetric BadgeChapter 10 Highlights and Interviews with Winners