Abstract: Electrocardiogram (ECG) and Phonocardiogram (PCG) signals embed key information about subject physiological status. Physicians use such information to diagnose the general physiological status of the patient and also to diagnose incoming pathologies. The automatic extraction of such information enables the implementation of systems that could monitor subjects and infer about some physiological and pathological condition, so that efficient prevention strategies could be enabled. ECG and PCG features extraction is a set of Digital Signal Processing-based (DSP-based) application-specific algorithms (ASA) to execute crisp measurements to be inputted to a fuzzy logic engine that infers about a physiological and/or pathological status of the subject. Fuzzy logic engine is a data driven inferential process, so most of the design efforts need to be addressed to the features extraction process and to the rule set and membership functions definition and tuning. Low level and high level signal features can be extracted, so that a very effective inference could be applied at fuzzy logic engine level. Heart rate variability (HRV) is one of the high level signal features that embeds veri significant information about physiological and pathological condition of the subject.

Brief Biography of the Speaker:
Prof. Mario Malcangireceived his undergraduate and graduate degrees inElectronic Engineering and Computer Sciencefrom the Politecnico di Milano in 1981. He ismember of the International Neural NetworkSociety and among the founders of theEngineering Applications of Neural NetworksSpecial Interest Group (SIG). His research is inthe areas of multimedia communications, digitalsignal processing, embedded/real-timesystems, biometrics, and biomedical. His research efforts are mainly targetedat speech- and audio-information processing,with special attention to applying soft-computing methodologies (neuralnetworks and fuzzy logic) to speech synthesis, speech recognition, andspeaker identification for implementation on deeply embedded systems. Heteaches digital signal processing and digital audio processing at the UniversitadegliStudi di Milano. He has published several papers on topics in digitalaudio and speech processing.