"Hands on Project-Based Approach for Biomedical Signal Analysis using MATLAB"
Biomedical signal analysis is a scientific discipline as well as technology frontier, with immense applications. It is a growing research field where many revolutionary ideas and efficient algorithms have been developed over the past few decades. This FDP will provide an opportunity to highlight recent trends and developments in the field of Biomedical signal processing. It will further give impetus to the participants towards bringing out newer and efficient techniques. Expert invited speakers from both industry and academia with their vast research experience in various fields will arouse the participants for the development of Biomedical signal processing. Hands-on exercises with MATLAB software will open the door for programming in Biomedical signal processing. |
|
| The objectives of this Faculty Development Programme are to |
|
| • | Learn basic signal processing concepts for convolution and peak detection, heart rate detection and others. |
| • | Understand and analyze the frequency domain concepts of ECG, EEG, EMG, PCG and PPG signals. |
| • | Design and implementation of a matched filter to detect spike-and-wave complexes in EEG signals. |
| • | Design and implementation of a matched filter to detect spike-and-wave complexes in EEG signals. |
In India, the UG and PG programmes of Electronics and communication engineering offer various advanced courses in the field of Biomedical signal processing. Biomedical signal processing is a very potential area of study where students can be guided to take up projects both at UG and PG level.Hence hands-on training to the ECE faculty of engineering colleges will make them competent to guide students on good projects/Mini- projects/dissertations. |
|
| Benefits to the faculty: |
|
| • | Faculty will get trained in the area of Biomedical signal processing. |
| • | Faculty will start guiding meaningful projects to UG and PG students. |
| FDP Course contents: |
|
| • | Biomedical signals- signal processing techniques. |
| • | Modern ECG signal processing. |
| • | Classification of Biomedical Signals. |
| • | Estimation of the PSD. |
| • | Time-varying Analysis of Heart-rate Variability. |
| • | Principal Component Analysis and Independent Component Analysis. |
| • | Analysis of ECG, EEG & PPG signals using MATLAB. |