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Advances in Motor Neuroprostheses

Overview of attention for book
Cover of 'Advances in Motor Neuroprostheses'

Table of Contents

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    Book Overview
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    Chapter 1 Application of Reinforcement and Deep Learning Techniques in Brain–Machine Interfaces
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    Chapter 2 Subject-Specific Muscle Activation Patterns in Athletic and Orthopedic Populations: Considerations for Using Surface Electromyography in Assistive and Biofeedback Device Applications
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    Chapter 3 Kineto-Dynamic Modeling of Human Upper Limb for Robotic Manipulators and Assistive Applications
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    Chapter 4 Learning from the Human Hand: Force Control and Perception Using a Soft-Synergy Prosthetic Hand and Noninvasive Haptic Feedback
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    Chapter 5 Design of a Soft Glove-Based Robotic Hand Exoskeleton with Embedded Synergies
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    Chapter 6 Model Predictive Control-Based Knee Actuator Allocation During a Standing-Up Motion with a Powered Exoskeleton and Functional Electrical Stimulation
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    Chapter 7 Deep Brain Stimulation for Gait and Postural Disturbances in Parkinson’s Disease
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    Chapter 8 Cognitive and Physiological Intent for the Adaptation of Motor Prostheses
Attention for Chapter 4: Learning from the Human Hand: Force Control and Perception Using a Soft-Synergy Prosthetic Hand and Noninvasive Haptic Feedback
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Citations

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Chapter title
Learning from the Human Hand: Force Control and Perception Using a Soft-Synergy Prosthetic Hand and Noninvasive Haptic Feedback
Chapter number 4
Book title
Advances in Motor Neuroprostheses
Published by
Springer, Cham, January 2020
DOI 10.1007/978-3-030-38740-2_4
Book ISBNs
978-3-03-038739-6, 978-3-03-038740-2
Authors

Qiushi Fu, Marco Santello, Fu, Qiushi, Santello, Marco

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Researcher 1 25%
Unknown 1 25%
Readers by discipline Count As %
Engineering 2 50%
Computer Science 1 25%
Unknown 1 25%

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