Biomedical Signal Processing: Innovation and Applications (Paperback)

Chapter 1. Multi-CLASS fNIRS Classification of Motor Execution Tasks with Application to Brain Computer Interfaces.- Chapter 2. A Comparative Study of End-to-End Discriminative Deep Learning Models for Knee Joint Kinematic Time Series Classification.- Chapter 3. Nonlinear Smoothing of Data with Random Gaps and Outliers (DRAGO) Improves Estimation of Circadian Rhythm.- Chapter 4. Wearable Smart Garment Devices for Passive Biomedical Monitoring.- Chapter 5. Spatial Distribution of Seismocardiographic Signals.- Chapter 6. Noninvasive Vascular Blood Sound Monitoring Through Flexible Pvdf Microphone.- Chapter 7. Fast Automatic Artifact Annotator for EEG Signals Using Deep Learning.- Chapter 8. Objective evaluation metrics for automatic classification of EEG events.