Biomedical Signal Processing
( 24 Modules )

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

Module #2
Physiological Signal Acquisition
Methods of signal acquisition, sensors, and measurement techniques

Module #3
Signal Processing Fundamentals
Review of signal processing concepts, including Fourier transform, filtering, and convolution

Module #4
Time Domain Analysis
Time domain signal analysis, including feature extraction and statistical analysis

Module #5
Frequency Domain Analysis
Frequency domain signal analysis, including spectral analysis and filter design

Module #6
ECG Signal Processing
Processing of electrocardiogram (ECG) signals, including filtering, feature extraction, and arrhythmia detection

Module #7
EEG Signal Processing
Processing of electroencephalogram (EEG) signals, including filtering, feature extraction, and seizure detection

Module #8
EMG Signal Processing
Processing of electromyogram (EMG) signals, including filtering, feature extraction, and muscle activity analysis

Module #9
Signal Filtering Techniques
Digital filtering techniques, including FIR and IIR filters, and their applications in biomedical signal processing

Module #10
Noise Reduction and Artifact Removal
Methods for noise reduction and artifact removal in biomedical signals

Module #11
Signal Compression and Encoding
Methods for compressing and encoding biomedical signals, including lossy and lossless compression

Module #12
Feature Extraction and Selection
Methods for feature extraction and selection from biomedical signals, including time, frequency, and time-frequency domain features

Module #13
Classification and Pattern Recognition
Introduction to classification and pattern recognition techniques, including supervised and unsupervised learning

Module #14
Machine Learning in Biomedical Signal Processing
Applications of machine learning in biomedical signal processing, including deep learning and neural networks

Module #15
Imaging and Biomedical Signal Processing
Applications of signal processing in medical imaging, including MRI, CT, and ultrasound

Module #16
Physiological Modeling and Simulation
Physiological modeling and simulation techniques, including compartmental models and system identification

Module #17
Signal Processing for Medical Diagnosis
Applications of signal processing in medical diagnosis, including disease diagnosis and patient monitoring

Module #18
Signal Processing for Prosthetics and Rehabilitation
Applications of signal processing in prosthetics and rehabilitation, including neural prosthetics and wearable devices

Module #19
Signal Processing for Brain-Computer Interfaces
Applications of signal processing in brain-computer interfaces, including EEG-based and neural prosthetic interfaces

Module #20
Signal Processing for Wearable Devices
Applications of signal processing in wearable devices, including fitness tracking and health monitoring

Module #21
Signal Processing for Telemedicine and Remote Monitoring
Applications of signal processing in telemedicine and remote monitoring, including signal transmission and compression

Module #22
Signal Processing for Medical Imaging Analysis
Applications of signal processing in medical imaging analysis, including image segmentation and feature extraction

Module #23
Case Studies in Biomedical Signal Processing
Real-world applications and case studies in biomedical signal processing

Module #24
Course Wrap-Up & Conclusion
Planning next steps in Biomedical Signal Processing career

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Biomedical Signal Processing ( 24 Modules )

Biomedical Signal Processing
( 24 Modules )