外骨骼機器分析與應用

This course provides an integrated introduction to biosignal analysis, human movement biomechanics, exoskeleton technologies, and AI-assisted biomedical image processing. Through a combination of lectures, hands-on laboratory sessions, software development exercises, and online modules, students will gain both conceptual understanding and practical engineering skills. Early modules focus on surface electromyography (sEMG), including instrumentation amplifier design, dual-power supply circuits, and signal acquisition principles. Students then apply these foundations to exoskeleton analysis, exploring positive exoskeleton concepts, muscular performance, and the role of EMG in movement assessment. Mid-semester, students build their own sEMG measurement circuits and complete project-based evaluations. The course further expands into powered exoskeleton systems—such as Keeogo—covering hardware donning, software operation, and their clinical and assistive applications. Students also receive training in motion capture system operation to analyze human movement objectively. In the final phase, the course introduces AI-assisted biomedical image data analysis and exoskeleton mechanical design, leading to final reports and a summative exam. Overall, the course emphasizes the integration of biosignals, biomechanics, electromechanical systems, and computational analysis—a foundation essential for modern biomedical engineering.

Prerequisites or Required Background Students taking this course are expected to have: Basic knowledge of electronics and circuit theory, including operational amplifiers and signal conditioning. Fundamental understanding of human physiology, particularly muscle structure and neuromuscular function. Introductory programming skills, preferably in Python or a similar language. General familiarity with biomedical engineering concepts, such as biosignals and measurement systems. Ability to operate a personal laptop for coding, data analysis, and hands-on exercises.

By the end of the course, students will be able to: sEMG & Circuit Design 1.Explain the physiological principles of surface electromyography and its applications. 2.Design and implement sEMG measurement circuits using instrumentation amplifiers and dual-power supply configurations. 3.Acquire, filter, and process EMG signals for movement and performance analysis. 4.Develop Python-based interfaces for sEMG data visualization and feature extraction. Biomechanics & Exoskeletons 1.Describe skeletal muscle biomechanics and EMG-based performance assessment. 2.Explain the concepts of positive exoskeletons and their functional roles. 3.Perform mechanical and functional analysis of exoskeleton systems. 4.Understand the structure, donning procedure, and software operation of powered exoskeletons such as Keeogo. Motion Capture & Movement Analysis 1.Operate a motion capture system and extract basic kinematic information. 2.Integrate motion capture data with EMG to interpret human movement patterns. 3.AI-Assisted Image Analysis 4.Apply AI tools and computational pipelines to analyze biomedical images. 5.Understand the workflow for AI-enabled biomedical image data processing and interpretation. Project Execution & Communication 1.Build and validate a functional sEMG data acquisition module as part of the midterm project. 2.Prepare technical reports, present experimental findings, and justify engineering design decisions. 3.Demonstrate the ability to integrate biosignal processing, biomechanics, and exoskeleton technologies into a coherent biomedical engineering framework.

Midterm Report – 30% Final Project – 40% Class Participation and Assignments – 30%

The instructor will prepare lecture slides for each class session based on the weekly topics.

地點

Instructor’s Office, Room B208, Laboratory Building

時間

Every Thursday, 1:00–3:00 PM

聯絡方式

E-mail: sunbow@nycu.edu.tw