EEG-based Brain-Machine Interface (BMI) using machine learning to control upper limb robotic arm for rehabilitation = 재활 치료 목적의 뇌파를 통한 로봇 팔 제어를 위한 머신 러닝 기반 뇌-기계 인터페이스 시스템 개발

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Recently, research on brain computer interface (BCI) for rehabilitation of stroke patients has become popular. Rehabilitation reflecting patient’s motor intention is more effective for motor recovery compared to passive robot-assisted or therapist based rehabilitation. If the command sent to the robot reflects patient’s motor intention, muscle movement and brain’s motor circuit would become more synchronized, resulting in enhanced neural plasticity. Thus, this study examines the possibility of decoding motor intention during and without movement along with classification of various activities of daily life (ADL) for rehabilitation.
Advisors
Jeong, Jaeseungresearcher정재승researcher
Description
한국과학기술원 :바이오및뇌공학과,
Publisher
한국과학기술원
Issue Date
2020
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 바이오및뇌공학과, 2020.8,[i, 25 p. :]

Keywords

Stroke▼aBrain computer interface▼amotor intention▼aactivities of daily life▼aneural plasticity; 뇌졸중▼a뇌-로봇 융합 기술▼a운동 의지▼a재활 동작 분류▼a신경 가소성

URI
http://hdl.handle.net/10203/284925
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=925084&flag=dissertation
Appears in Collection
BiS-Theses_Master(석사논문)
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