Full Description
Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare.
Contents
1. Types and characteristics of biomedical signals2. Time-domain processing of biomedical signals3. Spectral-domain analysis of biomedical signals4. Wavelet analysis of biomedical signals5. Time-frequency analysis of biomedical signals6. Sparse and compressive sensing techniques for biomedical signals7. Machine learning for interpreting biomedical signals8. Wearables and Internet of Things for connected healthcare
