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所在平台: Udemy |
课程主页: https://www.udemy.com/course/biomedical-signal-processing/
课程评论：没有评论
课程名称：生物医学信号处理 概述：生物医学信号处理是一个关键领域，结合了工程学、生物学和医学的原则，以解释和分析生理信号。这些信号可能包括电信号、机械信号或光学数据，这些数据源自生物系统，对于诊断、监测和治疗各种医疗状况至关重要。生物医学信号处理是一个动态且重要的领域，利用先进的计算技术来提高医疗保健结果。通过将原始生理数据转化为可操作的见解，它在提升我们有效诊断、监测和治疗患者的能力方面发挥着关键作用。 在本课程中，学习者将探索信号处理的基本概念，如采样定理及基于DIT和DIF算法的DFT-FFT计算，这些内容在第一章中介绍。第二章将学习无限冲动响应滤波器的设计概念，包括数字巴特沃斯滤波器和切比雪夫滤波器、双线性变换方法以及冲动不变方法。第三章涉及有限冲动响应滤波器的设计和不同类型窗函数的应用，介绍同步平均和移动平均的 FIR 滤波器的使用。第四章重点分析心电图（ECG），使用各种信号处理方法如P波检测、QRS复合波检测（采用模板匹配技术）以及心率变异性分析。 通过本课程的学习，学员将掌握生物医学信号处理的基础知识，提升在医疗领域的应用能力。
Biomedical signal processing is a crucial field that merges principles of engineering, biology, and medicine to interpret and analyse physiological signals. These signals, which can include electrical, mechanical, or optical data, are derived from biological systems and are essential for diagnosing, monitoring, and treating various medical conditions. Biomedical signal processing is a dynamic and essential field that leverages advanced computational techniques to improve healthcare outcomes. By transforming raw physiological data into actionable insights, it plays a pivotal role in enhancing our ability to diagnose, monitor, and treat patients effectively. In this course, learners will explore the basic concepts of signal processing such as sampling theorem, DFT-FFT computations using DIT and DIF algorithms in chapter1. The design of Infinite impulse response filter concepts such as digital Butterworth and Chebyshev filters, bilinear transformation method and impulse invariant methods will be studied in chapter2. The chapter 3 deals with design of Finite impulse response filters with different types of windowing concepts. Synchronized averaging and moving averaging using FIR filters will be dealt in this chapter. The chapter 4 focussed on analysis of ECG using various signal processing methods such as P-wave detection, QRS complex detection using template matching techniques and Heart rate variability.
