1
课程详述
COURSE SPECIFICATION
以下课程信息可能根据实际授课需要或在课程检讨之后产生变动。如对课程有任何疑问，请
联系授课教师。
The course information as follows may be subject to change, either during the session because of unforeseen
circumstances, or following review of the course at the end of the session. Queries about the course should be
directed to the course instructor.
1.
课程名称 Course Title
神经工程与脑机接口 Neural Engineering and Brain-computer Interface
2.
授课院系
Originating Department
生物医学工程系 Biomedical Engineering
3.
课程编号
Course Code
BMEB333
4.
课程学分 Credit Value
3
5.
课程类别
Course Type
专业核心课 Major Core Courses
6.
授课学期
Semester
秋季 Fall
7.
授课语言
Teaching Language
英文 English
8.
授课教师、所属学系、联系方
式（如属团队授课，请列明其
他授课教师）
Instructor(s), Affiliation&
Contact
（For team teaching, please list
allinstructors）
肖凯，xiaok3@sustech.edu.cn
9.
实验员/助教、所属学系、联系
方式
Tutor/TA(s), Contact
待公布 To be announced
10.
选课人数限额(可不填)
Maximum Enrolment
（Optional）
2
11.
授课方式
Delivery Method
讲授
Lectures
习题/辅导/讨论
Tutorials
实验/实习
Lab/Practical
其它(请具体注明)
Other（Pleasespecify）
总学时
Total
学时数
Credit Hours
48
48
12.
先修课程、其它学习要求
Pre-requisites or Other
Academic Requirements
MA107A
13.
后续课程、其它学习规划
Courses for which this course
is a pre-requisite
无 None
14.
其它要求修读本课程的学系
Cross-listing Dept.
无 None
教学大纲及教学日历 SYLLABUS
15.
教学目标 Course Objectives
神经工程与脑机接口是生物医学工程的重要研究方向之一。本课程首先介绍人体神经系统及相应效应器的结构与功能，并
通过相应的案例展示其独特的应用意义，然后介绍神经系统传感技术的工作原理，学习神经电生理、功能近红外成像、功
能核磁共振、脑磁图等神经信号的采集方法，以及经颅磁刺激、经颅直流电刺激等神经刺激与调控方法；课程进一步介绍
神经系统生理信号采集的硬件系统、信号获取方法与理论，介绍脑机接口系统框架，典型应用与范式，并结合具体的应用
案例给出神经信号的常见处理算法；最后，课程介绍神经工程领域前沿研究并对其未来发展方向进行开放式讨论。
Neural engineering and brain-computer interface is one of the important research directions in biomedical engineering.
This course will firstly introduce the structure and function of the human nervous system and corresponding effectors,
and demonstrate their unique application significance through corresponding cases. Then, the acquisition methods of
neural signals such as neurophysiology, functional near-infrared imaging, functional magnetic resonance imaging, and
magnetoencephalography, as well as neurostimulation and regulation methods such as transcranial magnetic
stimulation and transcranial direct current stimulation, and the working principles of the corresponding sensors are
introduced. The course further introduces the hardware system, signal acquisition method and theory of physiological
signal acquisition of neuromuscular system, and gives common processing algorithms for neural signals in combination
with specific application cases; finally, the course introduces the frontier research in the field of neuro-engineering and
its future development direction Have an open discussion.
16.
预达学习成果 Learning Outcomes
通过学习，本课程预期达到下列学习成果：
1. 了解人体神经系统；
2. 熟悉神经信号获取与调控技术；
3. 了解神经接口技术发展历史与前沿动态；
4. 掌握神经系统典型传感器的原理、硬件系统、神经信号采集方法与理论；
5. 学习脑机接口实验范式与实验设计方法；
6. 掌握神经信号的常见处理算法；
7. 了解神经工程学的前沿动态。
After one semester of course study, we plan to achieve the following goal:
1. Understand the human nervous system;
2. Familiar with neural signal acquisition and regulation technology;
3
3. Understand the development history and frontier trends of neural interface technology;
4. Master the sensor technology, hardware systems, signal acquisition methods and theory of neural signals;
5. Learning BCI paradigms and experimental design methods;
6. Master the common processing algorithms of neural signals;
7. Understand the cutting-edge advances of neuro-engineering.
17.
课程内容及教学日历 （如授课语言以英文为主，则课程内容介绍可以用英文；如团队教学或模块教学，教学日历须注明
主讲人）
Course Contents (in Parts/Chapters/Sections/Weeks. Please notify name of instructor for course section(s), if
this is a team teaching or module course.)
Section 1 神经工程概述（2 学时）
Section 1 General introduction to neural engineering
Section 2 人体神经系统概要（4 学时）
扼要介绍人体神经系统基本结构与功能。
Section 2 Fundamentals of neural system
Briefly introduce the basic structure and function of the human neural system.
Section 3 神经系统传感技术 （6 学时）
介绍电生理监测的手段及传感原理。
Section 3 Sensing technologies of neural system
Introduce methods and sensing principle of electrophysiological monitoring.
Section 4 神经信号采集方法理论和仪器系统（6 学时）
介绍神经信号采集方法、理论及仪器系统：脑电、心电、肌点、近红外光谱、功能核磁共振成像等神经系统监测手段。
Section 4 Techniques of neural signal acquisition
Introduction to neural signal acquisition techniques (EEG, ECG, EMG, fMRI, NIRs and other neurological monitoring
methods).
Section 5 神经系统调控技术（6 学时）
介绍神经系统刺激与调控技术。
Section 5 Neural regulation technologies
Introduction to neural stimulation and modulation techniques (e.g., TMS, tDCS).
Section 6 脑机接口概述（2 学时）
介绍脑机接口系统框架和典型应用。
Section 6 Introduction to BCI
Introduction to the framework and classical applications of BCI.
Section 7 脑机接口实验范式（4 学时）
介绍脑机接口实验范式：事件相关电位、稳态视觉诱发电位、运动想象。
Section 7 Paradigms of BCI
Introduction to BCI paradigms (e.g., ERP, SSVEP, MI).
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Section 8 神经信号处理方法 1（6 学时）
介绍卷积、傅里叶变换、时频分析等神经信号的查看分析方法。
Section 8 Data processing of neural signals – Part 1
Introduces methods for viewing and analyzing neural signals such as convolution, Fourier transform, and time-
frequency analysis.
Section 9 神经信号处理方法 2（6 学时）
介绍 FIR/IIR 滤波器及其设计方法、小波变换、独立成分分析等神经信号的常用处理算法。
Section 9 Data processing of neural signals – Part 2
Introduce common processing algorithms for neural signals such as FIR/IIR filters and their design methods, adaptive
filtering, independent component analysis, etc.
Section 10 神经信号处理方法 3（4 学时）
介绍神经信号处理中的统计学方法。
Section 10 Data processing of neural signals – Part 3
An introduction to statistical methods in neural signal processing.
Section 11 神经工程与脑机接口前沿讨论（2 学时）
针对神经工程领域前沿思想与技术展开交流讨论。
Section 11 Frontiers in Neuro-engineering and BCI
Open discussion on cutting-edge ideas and technologies of neural engineering.
18.
教材及其它参考资料 Textbook and Supplementary Readings
Textbook
None
Supplementary Readings
1. Neural Engineering, He
2. Neuroengineering, DiLorenzo
3. Principles of Neural Science, Kandel
4. Biological Psychology, Kalat
5. Cognitive Neuroscience: the biology of the mind, by Herreras E B.
6. Brain-computer interfaces: Revolutionizing human-computer interaction, by Graimann, B., Allison, B. Z., &
Pfurtscheller, G.
课程评估 ASSESSMENT
19.
评估形式
Type of
Assessment
评估时间
Time
占考试总成绩百分比
% of final
score
违纪处罚
Penalty
备注
Notes
出勤 Attendance
5%
课堂表现
Class
Performance
小测验
Quiz
课程项目 Projects
30%
平时作业
Assignments
25%