Human Locomotion Recognition, STS Transition Phase Estimation and Gait Phase Recognition of Level-ground Walking Using Wearable IMU Sensors
웨어러블 IMU 센서를 이용한 수평 지면 보행의 인간 운동 분류, STS 전환 단계 추정 및 보행 단계 인식
- 주제어 (키워드) Intention recognition , SiSt/StSi transition phase estimation , gait phase recognition , Inertial measurement unit (IMU) , Multi-layer perceptron (MLP) , gait events; 의도 인식 , SiSt/StSi 전이 위상 추정 , 보행 위상 인식 , 관성 측정 장치(IMU) , 다층 퍼셉트론(MLP) , 보행 이벤트
- 발행기관 서강대학교 일반대학원
- 지도교수 정석환
- 발행년도 2024
- 학위수여년월 2024. 8
- 학위명 석사
- 학과 및 전공 일반대학원 기계공학과
- 실제 URI http://www.dcollection.net/handler/sogang/000000079244
- UCI I804:11029-000000079244
- 본문언어 영어
- 저작권 서강대학교 논문은 저작권 보호를 받습니다.
목차
I Introduction 1
A Research Background 1
B Related Works 4
C Research Purpose 5
D Thesis Outline 6
II Methodology 8
A Experiment Protocol and Data Collection 8
a Participants Information 8
b IMU Placement and Orientations 9
c Data Acquisition Protocols 13
B Data Preprocessing 15
a Start/end Point Detection Algorithm for SiSt/StSi Transitions 16
b Trimming and Labeling of Transition Phases 18
c Gait Event Detection Algorithm for Level Ground Walking 22
d Walking Data Trimming and Labeling of Gait Phases 25
C Input Feature Selection and Dataset Preparation 27
a Input Features for Locomotion mode Classification 28
b Input Features for SiSt/StSi Transition Phase Estimation 29
c Input Features for Gait Phase Recognition of Level-ground Walking 31
III Model Parameters and Training 33
A Proposed Neural Network Algorithm 33
a Locomotion Mode Classification 33
b SiSt/StSi Transition Phase Estimation 33
c Gait Phase Recognition of Level-ground Walking 34
IV Results and Discussion 36
A Locomotion Mode Classification Model Results 36
B SiSt and StSi Transition Phase Estimation Model Results 37
C Results of the Gait Phase Recognition of Level-ground Walking 39
V Conclusion and Future Work 50
References 62
