Surface EMG-based Sketching Recognition Using Two Analysis Windows and Gene Expression Programming. - Wikidata - awgldk - TriplyDB

Surface EMG-based Sketching Recognition Using Two Analysis Windows and Gene Expression Programming.

Surface EMG-based Sketching Recognition Using Two Analysis Windows and Gene Expression Programming.

http://www.wikidata.org/entity/Q37340344

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A Brain-Machine Interface Based on ERD/ERS for an Upper-Limb Exoskeleton Control.A Novel Hybrid Model for Drawing Trace Reconstruction from Multichannel Surface Electromyographic Activity.

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Surface EMG-based Sketching Recognition Using Two Analysis Windows and Gene Expression Programming.

http://www.wikidata.org/entity/Q37340344

description

article científic

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article scientifique

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articolo scientifico

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artigo científico

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bilimsel makale

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scientific article published on 14 October 2016

@en

vedecký článok

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vetenskaplig artikel

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videnskabelig artikel

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vědecký článek

@cs

name

Surface EMG-based Sketching Re ...... d Gene Expression Programming.

@en

Surface EMG-based Sketching Re ...... d Gene Expression Programming.

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type

label

Surface EMG-based Sketching Re ...... d Gene Expression Programming.

@en

Surface EMG-based Sketching Re ...... d Gene Expression Programming.

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prefLabel

Surface EMG-based Sketching Re ...... d Gene Expression Programming.

@en

Surface EMG-based Sketching Re ...... d Gene Expression Programming.

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FNINS.2016.00445

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Frontiers in Neuroscience

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Surface EMG-based Sketching Re ...... d Gene Expression Programming.

@en

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Yumiao Chen

http://www.w3.org/2001/XMLSchema#string

Zhongliang Yang

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P2860

Dual Window Pattern Recognition Classifier for Improved Partial-Hand Prosthesis Control.

Recognition of handwriting from electromyography

An upper-limb power-assist exoskeleton using proportional myoelectric control.

System training and assessment in simultaneous proportional myoelectric prosthesis control.

A state-based, proportional myoelectric control method: online validation and comparison with the clinical state-of-the-art

Decoding subtle forearm flexions using fractal features of surface electromyogram from single and multiple sensors.

Determining the optimal window length for pattern recognition-based myoelectric control: balancing the competing effects of classification error and controller delay.

A dynamical model improves reconstruction of handwriting from multichannel electromyographic recordings.

Time-dependent statistical and correlation properties of neural signals during handwriting.

Automated Freehand Sketch Segmentation Using Radial Basis Functions.

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445

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scholarly article

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10.3389/FNINS.2016.00445

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10

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2016-10-14T00:00:00Z

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27790083

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5064664

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