Introduction to Biomedical Signals: The nature of Biomedical Signals, Examples of Biomedical Signals, Objectives and difficulties in Biomedical analysis.
Electrocardiography: Basic electrocardiography, ECG lead systems, ECG signal characteristics.
Signal Conversion :Simple signal conversion systems, Conversion requirements for biomedical signals, Signal conversion circuits (Text-1)
Signal Averaging: Basics of signal averaging, signal averaging as a digital filter, a typical averager, software for signal averaging, limitations of signal averaging.
Adaptive Noise Cancelling: Principal noise canceller model, 60-Hzadaptive cancelling using a sine wave model, other applications of adaptive filtering (Text-1)
Data Compression Techniques: Turning point algorithm, AZTEC algorithm, Fan algorithm, Huffman coding, data reduction algorithms The Fourier transform, Correlation, Convolution, Power spectrum estimation, Frequency domain analysis of the ECG (Text-1)
Cardiological signal processing: Basic Electrocardiography, ECG data acquisition, ECG lead system, ECG signal characteristics (parameters and their estimation), Analog filters, ECG amplifier, and QRS detector, Power spectrum of the ECG, Bandpass filtering techniques, Differentiation techniques, Template matching techniques, A QRS detection algorithm, Realtime ECG processing algorithm, ECG interpretation, ST segment analyzer, Portable arrhythmia monitor. (Text -2)
Neurological signal processing: The brain and its potentials, The electrophysiological origin of brain waves, The EEG signal and its characteristics (EEG rhythms, waves, and transients), Correlation.
Analysis of EEG channels: Detection of EEG rhythms, Template matching for EEG, spike and wave detection (Text-2).