Semester : Semester I 2010/2011 __________________________________________________________________ Lecturer : Malarvili A/P Bala Krishnan __________________________________________________________________ Synopsis :

Manual analyses of biomedical signals has many limitations and very subjective. Therefore, computer analysis of these signals is essential since it can provide accurate diagnosis as well as quantitative measurement. Hence, this course presents methods of processing the biomedical signals. The course will discuss the fundamental and current approach of biomedical signal processing. Among biomedical signal processing topics covered in this course are: Fourier analysis, Fourier transform, data acquisition, digital filter design and discrete Fourier transform. Furthermore, few current approaches on biomedical signal processing techniques were also introduced: instantaneous energy and frequency, short-time Fourier transform wavelet transform and time-frequency analysis.

__________________________________________________________________ This work, SCJ2013 Data Structure and Algorithm by Malarvili A/P Bala Krishnan is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License
Lesson 1

Physiological Origin Of Biomedical Signal

Biomedical signals, action potential, electromyogram(EMG), electrocardiogram (ECG), anatomy and conduction system of heart, bipolar and unipolar limb leads, unipolar chest leads, characteristic of ECG and arrhythmia.

Lesson 2

Physiological Origin Of Biomedical Signal Part 2

Biomedical signals, action potential, electromyogram(EMG), electrocardiogram (ECG), anatomy and conduction system of heart, bipolar and unipolar limb leads, unipolar chest leads, characteristic of ECG and arrhythmia.

Lesson 3

Signal Acquisition

The process of converting continuous-time signal (analog) into discrete-time signal (digital) and its reverse process.

Lesson 4

Discrete-Time And System (A Review)

The review for Discrete-Time and system.

Lesson 5

Z-Transform

Introduction to Z-Transform, definition, example, solution for difference equation and transfer function, inverse Z-Transform, relationship between the Z-Transform and Fourier Transform.

Lesson 6

Digital Filter Design

• An ideal digital filter, general types of digital filter, ideal filters, filter specifications, filter tool in Matlab, and filter used in ECG.

Lesson 7

ECG Analysis 1 : QRS Detection

• ECG signal characteristics, and QRS detection algorithm.

Lesson 8

ECG Analysis 2 : Qt Dispersion Algorithm As A Predictor Of Sudden Cardiac Death

• Myocardial ischemia and infarction, QT dispersion(QTd), research methodology, hardware circuitry, ECG Circuit, data acquisition, waveform recognition, T end Detection, T wave, duration measurement, and result - 12 lead analysis.

Lesson 9

ECG Analysis 3 : Heart Rate Variability

• Heart rate variability, band-pass filtering, QRS waves detection algorithms, outliers removal, resampling, detrending, analysis of heart rate variability(HRV), time-domain analysis, and frequency domain analysis.

Lesson 10

EEG Processing

• Electroencephalogram (EEG), brain lobes, recording of EEG, 10-20 system, sensor placement, and EEG signal.

Lesson 11

EEG Analysis 1 : Newborn Seizure Detection

• Identification of seizure, time approach, and frequency approach.

Lesson 12

Wavelet

• Introduction to wavelet.