Biomechatronics
本课程融合机械、电子、控制与生物医学知识，研究人体与机电系统的交互与协同。学生学习执行器、传感器、人机接口、肌电控制、外骨骼与假肢设计原理，掌握运动意图识别、闭环控制与触觉反馈等关键技术。课程结合康复机器人、智能假肢、手术机器人等前沿案例，培养学生在医疗机器人与神经工程领域的系统集成与创新能力。
This course integrates mechanical, electronic, control, and biomedical knowledge to study interactions between the human body and mechatronic systems. Students learn actuators, sensors, human-machine interfaces, EMG control, exoskeleton, and prosthetic design, with motion intent recognition, closed-loop control, and haptic feedback. Cases include rehabilitation robots, smart prosthetics, and surgical robots, building system integration and innovation skills.
学生使用表面肌电传感器采集前臂肌肉信号，通过特征提取与机器学习分类识别握拳、捏取、张开等手势意图，驱动3D打印仿生手执行对应动作，完成实时控制演示与系统性能评估报告。
Using surface EMG sensors on the forearm, students extract features and apply machine learning to classify gestures such as fist, pinch, and open. The recognized intent drives a 3D-printed bionic hand to execute actions in real time. Students deliver a live demo and a performance evaluation report.