Черешнев Роман Игоревич Система управления человеческой походкой методами машинного обучения, подходящая для роботизированных протезов в случае двойной трансфеморальной ампутации

brief description

Черешнев Роман Игоревич Система управления человеческой походкой методами машинного обучения, подходящая для роботизированных протезов в случае двойной трансфеморальной ампутации
ОГЛАВЛЕНИЕ ДИССЕРТАЦИИ
кандидат наук Черешнев Роман Игоревич
Contents

1 Introduction

1.1 The relevance of research

1.2 Aims and objectives of research

1.3 Current approaches

1.4 Importance of work

1.5 Novelty and summary of the Author's main results

1.6 Publications

2 Literature review

2.1 Overview of the history of HAR

2.1.1 Machine learning in HAR

2.1.2 Seeking the best classifiers for HAR

2.1.3 Ensemble methods for HAR

2.1.4 Era of Smartphones

2.2 Review of HAR datasets

2.3 Literature review of methods for human gait inference

2.4 Review of prosthetic leg controllers

2.4.1 High-level controller

2.4.2 Mid-level controllers

2.4.2.1 Phase-based approach

2.4.2.2 Non phase-based approach

3 Overview of the Gain system

3.1 Gain system design principles and objectives

3.2 Main results

4 HuGaDB: A human gait database for gait inference

4.1 Motivation and design goals

4.2 Sensor network topology

4.3 Data acquisition programs

4.4 Participants

4.5 Data format

4.6 HuGaDB issues

4.7 Noise

4.8 Conclusions

4.9 Availability

5 Gain high-level controller

5.1 RapidHARe classification method

5.2 Activity mode recognition using RapidHARe

5.2.1 Continuous activity recognition

5.2.2 Directional features

5.2.3 State-of-the-art methods

5.2.4 Comparison to the state-of-the-art methods

5.3 The high-level controller for Gain

5.3.1 Sitting-standing module

5.3.2 Sitting-down module

5.3.3 Standing-up module

5.3.4 The controller algorithm

5.3.5 Experimental evaluation of the high-level controller in Gain

5.3.6 Implementation details

5.4 Conclusions

6 Gait mid-level controller

6.1 LSTM

6.2 Feature extraction methods

6.3 Gait inference results

6.4 Variance in different phases

6.5 inference error around activity change

6.6 Gait inference results for one leg

6.7 Conclusions

7 Conclusions

7.1 Main results of this thesis

Acknowledgments

List of abbreviations and conventions

Bibliography

List of figures

List of tables

Appendix A. Gain system inference visualization