Physiological signals are widely used to perform medical assessment for monitoring an extensive range of pathologies, usually related to cardio-vascular diseases. Among these, both PhotoPlethysmoGraphy (PPG) and Electrocardiography (ECG) signals are those more employed. PPG signals are an emerging non-invasive measurement technique used to study blood volume pulsations through the detection and analysis of the back-scattered optical radiation coming from the skin. ECG is the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin. In the present paper we propose a physiological ECG/PPG “combo” pipeline using an innovative bio-inspired nonlinear system based on a reaction-diffusion mathematical model, implemented by means of the Cellular Neural Network (CNN) methodology, to filter PPG signal by assigning a recognition score to the waveforms in the time series. The resulting “clean” PPG signal exempts from distortion and artifacts is used to validate for diagnostic purpose an EGC signal simultaneously detected for a same patient. The multisite combo PPG-ECG system proposed in this work overpasses the limitations of the state of the art in this field providing a reliable system for assessing the above-mentioned physiological parameters and their monitoring over time for robust medical assessment. The proposed system has been validated and the results confirmed the robustness of the proposed approach.

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Since the Human Genome Project completed in 2000, the sequencing of the first genome, massive progress has been made by medical science in the early diagnosis and personalized therapies based on nucleic acids (NA) analysis. To allow the extensive use of these molecular methods in medical practice, scientific research is nowadays strongly focusing on the development of new miniaturized and easy-to-use technologies and devices allowing fast and low cost NA analysis in decentralized environments. It is now the era of so-called genetic "Point-of-Care" (PoC). These systems must integrate and automate all steps necessary for molecular analysis such as sample preparation (extraction and purification of NA) and detection based on PCR (Polymerase Chain Reaction) technology in order to perform, by unskilled personnel, in vitro genetic analysis near the patient (in hospital, in the physician office, clinic, or home), with rapid answers and low cost. In this review, the recent advances in genetic PoC technologies are discussed, including the extraction and PCR amplification chemistry suitable for PoC use and the new frontiers of research in this field.

The realization of an innovative label- and PCR-free silicon nanowires (NWs) optical biosensor for direct genome detection is demonstrated. The system is based on the cooperative hybridization to selectively capture DNA and on the optical emission of quantum confined carriers in Si NWs whose quenching is used as detection mechanism. The Si NWs platform was tested with Hepatitis B virus (HBV) complete genome and it was able to reach a Limit of Detection (LoD) of 2 copies/reaction for the synthetic genome and 20 copies/reaction for the genome extracted from human blood. These results are even better than those obtained with the gold standard real-time PCR method in the genome analysis. The Si NWs sensor showed high sensitivity and specificity, easy detection method, and low manufacturing cost fully compatible with standard silicon process technology. All these points are key factors for the future development of a new class of genetic point-of-care devices that are reliable, fast, low cost, and easy to use for self-testing including in the developing countries.