Biomedical Signal Processing Fundamentals
( 25 Modules )

Module #1
Introduction to Biomedical Signal Processing
Overview of biomedical signal processing, importance, and applications

Module #2
Biological Systems and Signals
Physiological systems, signal types, and characteristics

Module #3
Sampling and Quantization
Sampling theorem, aliasing, and quantization of biomedical signals

Module #4
Time Domain Analysis of Biomedical Signals
Time domain analysis techniques, signal averaging, and filtering

Module #5
Frequency Domain Analysis of Biomedical Signals
Fourier transform, power spectral density, and frequency domain analysis

Module #6
Filtering of Biomedical Signals
Filter types, design, and implementation in biomedical signal processing

Module #7
Artifact Removal and Noise Reduction
Noise sources, types, and removal techniques in biomedical signals

Module #8
Biopotential Signals:ECG and EMG
Physiological significance, acquisition, and analysis of ECG and EMG signals

Module #9
Biopotential Signals:EEG and ERG
Physiological significance, acquisition, and analysis of EEG and ERG signals

Module #10
Blood Pressure and Blood Flow Signals
Physiological significance, acquisition, and analysis of blood pressure and blood flow signals

Module #11
Respiratory Signals
Physiological significance, acquisition, and analysis of respiratory signals

Module #12
Image Processing Fundamentals
Introduction to image processing, image types, and processing techniques

Module #13
Image Filtering and Enhancement
Image filtering, noise reduction, and enhancement techniques

Module #14
Image Segmentation and Feature Extraction
Image segmentation, feature extraction, and representation techniques

Module #15
Biomedical Image Analysis:MRI and CT
Biomedical image analysis, MRI, and CT image processing

Module #16
Biomedical Image Analysis:Ultrasound and PET
Biomedical image analysis, ultrasound, and PET image processing

Module #17
Machine Learning Fundamentals for Biomedical Signal Processing
Introduction to machine learning, supervised and unsupervised learning

Module #18
Machine Learning for Biomedical Signal Classification
Machine learning techniques for biomedical signal classification

Module #19
Deep Learning for Biomedical Signal Processing
Deep learning techniques for biomedical signal processing and analysis

Module #20
Signal Compression and Transmission
Signal compression techniques, transmission, and storage

Module #21
Biomedical Signal Processing Applications
Applications of biomedical signal processing in healthcare and medicine

Module #22
Clinical Trials and Experiment Design
Designing clinical trials, experiment design, and data analysis

Module #23
Ethics and Regulations in Biomedical Signal Processing
Ethical considerations, regulations, and standards in biomedical signal processing

Module #24
Future Trends and Emerging Areas
Emerging areas, future trends, and research directions in biomedical signal processing

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Biomedical Signal Processing Fundamentals career

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Biomedical Signal Processing Fundamentals ( 25 Modules )

Biomedical Signal Processing Fundamentals
( 25 Modules )