Biomedical signal analysis for connected healthcare 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. Provides comprehensive coverage of biomedical engineering technologies and healthcare applications of various physiological signals Covers vital signals including ECG EEG EMG and body sounds Includes case studies and MATLAB code for selected applications