Notes of Biomedical signal processing

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1 BIOMEDICAL SIGNALS Mainly deterministic and mainly stochastic Biological systems are always characterized by a degree of uncertainty = biological systems that are strictly deterministic or stochastic do not generally exist, instead they are mainly deterministic (as ECG and ABP) or mainly stochastic (as EEG). The procedure to process and analyse mainly deterministic and mainly stochastic signals can be learned for a specific signal and then it can be applied to any other signal or image from the same category. General characteristics > High complexity > Dynamical behaviour > Adaptive (due to physiological regulation, sympathetic and parasympathetic arousal) > High variability both inter-individuals and intra- individual > Predictable (but not in an absolute sense = its general morphology is predictable if the signal is almost periodic and mostly deterministic (as ECG), but there is always the stochastic component that isn’t predictable (stochastic signals, as EEG, are not predictable at all) > Interactions among systems (physical, chemical, metabolic, etc.) > Signals corrupted by the presence of noise Variability and complexity The intra-individual variability is caused by non-stationarity of the process. In analysing a biomedical signal, we assume it to be stationary and ergodic (weak sense), however this is actually not the case on the long period: ➔ patient status and environmental influences can change. ➔ all biological systems are close to periodicity an d close to stationarity, but none has those characteristics in strict sense That is due to Complexity of the biological system, and specifically to the mechanisms that act: ➔ Physiological adaptability in response to a great variety of stimuli and circumstances ➔ Pathological internal autoregulation mechanisms…