The biomedical signal processing course provides an application-intensive approach to biomedical signal processing and application of mathematical tools. Topics include technologies for signal acquisition such as MRI, EEG, ECG, and sonar, architecture of bio-sensors and design, signals and systems theory, Fourier analysis, sampling theorem, discrete signal processing, noise characteristics of biosignals such as biologic, sensor, electronics and digital processing noise, linear and adaptive filtering, wavelet transforms, denoising, compression, classification and feature extraction applications, practical considerations in medical device design as relates to signal processing such as scalability, robustness, testability, algorithm complexity and regulatory issues.