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Reg. No.......................... Name.............................. M. TECH DEGREE EXAMINATION Second Semester Branch: Applied Electronics & Instrumentation Specialization: Signal Processing MAESP 205-2 BIOMEDICAL SIGNAL PROCESSING (Elective III) (2011 Admission onwards) MODEL QUESTION PAPER Time: Three Hours Maximum marks: 100 Answer all questions. Each complete question carries 25 marks 1. a) Define the following terms: i) Deterministic signal ii) Joint probability iii) correlation iv) ergodicity v) stationarity (10) b) Discuss the electric activity of the heart. What is the significance of the Einthoven’s triangle? (10) c) Write a note on spectral estimation in biomedical signals. (5) OR 2. a) Enumerate the origin of biopotentials with example (6) b) Explain the use of computers in analysis of biomedical signals. (10) c) Explain how time frequency analysis is helpful in biomedical signal processing. (9) 3. a) List out a few physiological interferences that may be encountered while acquiring a signal of interest (5) b) Design an optimal filter to remove noise from a signal, given that the signal and noise processes are independent, stationary, random processes. (10) c) Comment on ICA. How is it applicable for cocktail party like problem as applied to EEG signals. (10) OR 4. a) Explain the principles of Adaptive noise canceller with an example. (15) b) Given a biomedical signal, identify discrete signal epochs and correlate them with events in the related physiological processes. (10) 5. a). Propose an algorithm to detect QRS complexes in an ongoing ECG signal. (15) b) After applying the AZTEC algorithm to a signal, the saved data array is {2, 50, -4, 30, -6, 50, -6, 30, -4, 50, 2, 50}. (i) Draw the waveform that AZTEC would reconstruct from these data. (ii) What is the amount of data reduction? (iii) What is the peak-to-peak amplitude of a signal reconstructed from these data? (10) OR 6. a) Give an account of the salient ECG parameters and their intervals (7) b) The table below shows a set of 20 data points of an ECG sampled with an 8-bit analog-todigital converter. Number Frequency of occurrence -10 2 0 10 10 3 20 4 60 1 Huffman code (i) Draw a Huffman binary tree including the probabilities of occurrence for this set of data (ii) From the binary tree, assign appropriate Huffman codes to the numbers in the data array. (10) c) What are the methods for the analysis of heart rate variability 7. a) Write down the classification of EEG rhythms based on the frequency bands (8) (8) b) Mention the types of artefacts interfering with the EEG acquisition and the method by which they are processed. (9) c) Write a note on Joint Time-frequency analysis of biomedical signals. (8) OR 8. a) Propose a method to detect the presence of the α rhythm in an EEG channel. How is it extended to detect the presence of the same rhythm simultaneously in two channels? (10) b) With a suitable algorithm, substantiate the adaptive segmentation of EEG signals. (10) c) Highlight the applications of EEG. (5)