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Intention Detection EMG-based Algorithms for Upper-Limb Assistive Exoskeleton Control

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Academic year: 2021

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Table of Contents

Introduction ...4

1.1 Thesis Overview ... 6

NESM Exoskeleton ... 8

Setup of the Study ... 9

The Muscular System ... 11

2.1 Muscles Physiology ... 12

2.2 Surface EMG Signal ... 16

2.3 Upper-Limb Muscles and Sensor Placement ... 19

Shoulder Muscles ...20

Arm Muscles ... 21

Forearm Muscles ... 22

Myoelectric Control ... 25

3.1 Raw EMG signal ... 26

3.2 Time Domain Features Extraction ... 29

3.3 Classification Algorithms ... 32

Pattern Recognition Algorithms ... 32

Non-Pattern Recognition Algorithms ... 35

Gaussian Mixture Model ... 37

4.1 GMM Training Procedure ... 40

4.2 Test Session ...42

Support Vector Machines ... 45

5.1 Linear Classifiers ... 46

Separable Classes ... 46

Non-separable Classes ... 49

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5.2 Nonlinear Classifier ...50

5.3 The Classification Procedure ... 52

Training ... 52

Test ... 54

Results ... 56

6.1 Onset Detection ...56

Time Window Parameters ... 57

Detector Types ... 58

Features and Muscles Selection ... 61

6.2 Direction Decoding ... 64

Time window length ...65

Input types ...67

Training Data Sets ... 68

Real Time Implementation ... 70

7.1 Training ... 70

7.2 Test ... 71

Conclusions and Future Works ... 73

References ... 76

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