| Sl. No. | Units | |||
| 1. | Biomedical Signals: -Genesis of bioelectric potential, ECG, EEG, and EMG -Measurement of ECG, EEG and EMG -Overview of analog signal analysis: time and frequency domain representation of signal -Fourier series and Fourier transform -Correlation, convolution and filtering -Random signal-correlation and spectral representation |
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| 2. | Digitization of Signal: -Sampling theorem, quantization, quantizing effects -A/D conversion, aliasing artifacts in biomedical signals |
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| 3. | Discrete transforms: -Discrete time Fourier transform, DFT and FFT -Z-transform and properties |
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| 4. | Digital filters: -FIR and IIR filter -Biomedical applications of digital filtering- removal of power line interference from ECG data, reducing ECG artifact from EMG data. -ECG preprocessing, wave form recognition, morphological studies and rhythm analysis -Automated diagnosis based on decision theory -Optimal and adaptive filtering theory |
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| 5. | Event Detection: -Detection of events and waves in ECG -Correlation analysis of EEG channels for EEG rhythm detection -Matched filter for detection of EEG spikes |
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| Assignments |
Experiments are based on acquisition of real-time biomedical signals e.g. ECG and EMG using surface electrodes; extraction of features from the signals e.g. QRS detection, R-R interval, etc. in the ECG signal; biomedical filter designs; analysis of biomedical signals for disease identification; hardware prototype designs for biomedical signal acquisition/ processing and analysis. |
| Laboratory |
Signal representations; convolution and filtering; Filter Design for Biomedical applications: FIR and IIR Moving Average filters; Synchronized Averaging filter; Derivative based filters; Weiner filter; Butterworth filter, etc. Detection of Events in ECG waveform: QRS detection, P-wave detection, etc.; Biomedical Signal Analysis. All the experiments are implemented using MATLAB toolboxes. |
| Text Book |
| 1. Rangaraj M. Rangayyan. Biomedical Signal Analysis- A Case-Study Approach Wiley Interscience, 2002. |
| Reference Books |
| 1. W.J. Tompkins. Biomedical Digital Signal Processing: C language examples and laboratory experiment for IBM PC Prentice Hall. 2. R. S. Khandpur. Handbook of Biomedical Instrumentation, McGraw Hill Education, 3rd edition, 2014. 3. J.G. Proakis and D. G. Manolakis Digital Signal Processing: Principles, Algorithms and Application Prentice Hall, 1995. |