Advanced Methods in Biomedical Signal Processing and Analysis

<p>1. Feature engineering<br>2. Heart rate variability<br>3. Understanding the suitabillity of parametric modeling techniques in detecting the changes in the HRV signals acquired from cannabis consuming and nonconsuming Indian paddy-field workers<br>4. Patient-specific ECG beat classification using EMD and deep learning-based technique<br>5. Empirical wavelet transform and deep learning-based technique for ECG beat classification<br>6. Development of an Internet-of-Things (IoT)-based pill monitoring device for geriatric patients<br>7. Biomedical robotics<br>8. Combating COVID-19 by implying machine learning predictions and projections<br>9. Deep learning methods for analysis of neural signals: From conventional neural network to graph neural network<br>10. Improved extraction of the extreme thermal regions of breast IR images<br>11. New metrics to asses the subtle changes of the heart's electromagnetic field<br>12. The role of optimal and modified lead systems in electrocardiogram<br>13. Adaptive rate EEG processing and machine learning-based efficient recognition of epilepsy<br>14. Multimodal microscopy: A novel low-cost microscope designed for food and biological applications</p>