摘要
该文结合光电检测、信号处理、机器学习等技术,设计了一款“脉搏信号检测、分析及识别”实验系统,并给出了相关实验项目的要求和内容,以适应生物医学实验系统对专业特色和属性的要求。该实验系统由信号采集终端采集脉搏信号并传送给上位机处理、分析,提取特征后用神经网络进行识别。系统设计有GUI交互界面,友好方便。该实验系统真正实现了工程技术与医学应用的结合,不但巩固了学生的知识和技能,而且还促使学生以所学为基础递进式地向信号的高级处理、识别方向拓展,对强化学生的自学能力有很好的作用。
By using technologies of photoelectric detection,signal processing and machine learning,the experiment system of pulse signal detection,analysis,and recognition is designed to meet the need for more professional experiment systems in biomedical engineering major teaching.The experimental system collects pulse signals from the signal acquisition terminal and transmits them to a computer for processing and analyzing.After extracting features,the neural network is used to identify the pulse signals.The system has GUI interactive interface and is easy and convenient to use.The experiment system combines the engineering and medical applications,helps students to consolidate knowledge and skills,encourages students to explore advanced processing and recognition studies,and strengthens students'self-study ability.
作者
范迪
王光彩
陈之坤
房佳月圆
吕常智
FAN Di;WANG Guangcai;CHEN Zhikun;FANG Jiayueyuan;LU Changzhi(College of Electronic and Information Engineering,Shandong University of Science and Technology,Qingdao 266590,China)
出处
《实验科学与技术》
2019年第4期59-63,共5页
Experiment Science and Technology
基金
教育部产学合作协同育人项目(201702111012)
教育部产学合作协同育人项目(201702185063)
教育部产学合作协同育人项目(201701065008)
山东省研究生导师指导能力提升项目(SDYY17030)
山东科技大学研究生教育计划项目(KDYC14025)
关键词
生物医学工程
脉搏信号
实验系统
分析与识别
神经网络
biomedical engineering
human pulse signal
experimental system
analysis and recognition
neural network
