Stmicroelectronics S.r.l.

Distretto Tecnologico Sicilia Micro E Nano Sistemi S.c.a.r.l.

Sabrina Conoci

Francesco Rundo

Salvatore Petralia

Piero Fallica

Salvatore Sortino

Paolo Ferrari

Massimo Cataldo Mazzillo

Sebastiano Battiato

Maria Eloisa Castagna

Massimo Orazio Spata

Vincenzo Perciavalle

Rosalba Parenti

Francesca Trenta

Agostino Pirovano

Giuseppe Luigi Banna

Riccardo Sotgiu

Dario Russo

Concetto Spampinato

Giancarlo Asnaghi

In an embodiment, PhotoPlethysmoGraphy (PPG) signals are processed by detecting peaks and valleys in the PPG signal, segmenting the PPG signal to provide a time series of PPG waveforms located between two subsequent valleys in the PPG signal, applying to the waveforms in the time series pattern recognition with respect to a reference PPG waveform pattern produced based on a mathematical model of the PPG signal by assigning to the waveforms in the time series a recognition score. A resulting PPG signal is produced by retaining the waveforms in the time series having an assigned recognition score reaching a recognition threshold, and discarding the waveforms in the time series having an assigned recognition score failing to reach the recognition threshold.

Processing of electrophysiological signals

Blood pressure signals are reconstructed from PhotoPlethysmoGraphy (PPG) signals by: receiving PPG signals including systolic, diastolic and dicrotic phases; and determining first and second derivatives of the PPG signals and: a first set of values indicative of lengths of the signal paths of the PPG signal, the first derivative and the second derivative thereof in the systolic, diastolic and dicrotic phases; a second set of values indicative of relative durations of the PPG signal and the first and second derivatives thereof in the systolic, diastolic and dicrotic phases; and a third set of values indicative of the time separation of peaks and/or valleys in subsequent waveforms of the PPG signal. Reconstruction also includes applying artificial neural network processing to the first, second and third set of values. The artificial neural network processing includes artificial neural network training as a function of blood pressure signals to produce reconstructed blood pressure signals.

In an embodiment, a method of processing an electrophysiological signal includes collecting the electrophysiological signal that is indicative of a level of attention of a human; filtering the electrophysiological signal via joint low-pass and high-pass filtering using a set of filtering parameters including low-pass filters parameters and high-pass filters parameters having a set of low-pass cut-off frequencies and a set of high-pass cut-off frequencies respectively. The method further includes applying artificial neural network processing to the filtered electrophysiological signal to extract therefrom a set of features of the electrophysiological signal. The method further includes applying classifier processing to the set of features extracted from the filtered electrophysiological signal and producing a classification signal indicative of the level of attention of the human. The method further includes generating a trigger signal to trigger a user circuit based on the classification signal.

Electrophysiological signal processing method, corresponding system, computer program product and vehicle

An embodiment method comprises collecting at least one electrophysiological signal of a human over a limited time duration, and computing a set of electrophysiological signal features. The computing comprises at least one of: providing at least one reference electrophysiological signal and applying dynamic time warping processing to the at least one collected and at least one reference electrophysiological signals, applying stacked-auto-encoder artificial neural network processing to the collected electrophysiological signal, or filtering the electrophysiological signal collected via joint low-pass and high-pass filtering. The method further comprises applying pattern recognition processing to the computed set of features, producing a virtual key signal indicative of an identity of the human, and applying the virtual key signal to a user circuit to switch it between a first state and a second state as a result of the virtual key signal matching an authorized key signal stored in the user circuit.

Method of processing electrophysiological signals to compute a virtual vehicle key, corresponding device, vehicle and computer program product

A time series of face images of a human during a human activity are captured. A first artificial neural network (ANN) processing pipeline processes the captured time series of face images to provide a first attention level indicator signal. An electrophysiological signal indicative of the level of attention of the human during the activity is also captured. A second ANN processing pipeline processes the sensed electrophysiological signal to providing a second attention level indicator signal. A risk indicator signal is then generated based on at least one of the first attention level indicator and second attention level indicator. A user circuit is then triggered as a result of the risk indicator reaching or failing to reach at least one attention level threshold.

Method of processing signals indicative of a level of attention of a human individual, corresponding system, vehicle and computer program product

A method includes receiving a video signal that comprises a time series of images of a face of a human, wherein the images in the time series of images comprise a set of landmark points in the face, applying tracking processing to the video signal to reveal variations over time of at least one image parameter at the set of landmark points in the human face, generating a set of variation signals indicative of variations revealed at respective landmark points in the set of landmark points, applying processing to the set of variation signals, the processing comprising artificial neural network processing to produce a reconstructed PhotoPletysmoGraphy (PPG) signal, and estimating a heart rate variability of a variable heart rate of the human as a function of the reconstructed PPG signal.

Image processing method and corresponding system

A method includes receiving a time series of slice images of medical imaging. The images have a region of interest located at a lung lesion. The method also includes tracking over at least one subset of slice images in a time series of slice images variations over time of at least one image parameter at the set of points in the region of interest. Classifier processing is applied to set of signals indicative of tracked time variations of the at least one image parameter at respective points in the set of points. A classification signal is indicative of the tracked time variations of the at least one image parameter reaching or failing to reach at least one classification threshold.

A method of processing electrophysiological signals includes: receiving, over a limited time duration, sample electrocardiography (ECG) signals indicative of heart pulsatile activity occurring with a variable heart rate, wherein receiving the sample ECG signals is discontinued at an expiry of the limited time duration; receiving photoplethysmography (PPG) signals indicative of the heart pulsatile activity; determining a correlation between the sample ECG signals and the PPG signals; determining reconstructed ECG signals from the PPG signals as a function of the correlation between the sample ECG signals and the PPG signals; and estimating a heart rate variability of the variable heart rate as a function of the reconstructed ECG signals.

Method of processing electrophysiological signals and corresponding system, vehicle, and computer program product

A microreactor includes: a substrate () made of semiconductor material; a plurality of wells () separated by walls () in the substrate (); a dielectric structure () coating at least the top of the walls (); a cap (), bonded to the substrate () and defining a chamber () above the wells (); and a biasing structure (), configured for setting up a voltage (VB) between the substrate () and the chamber ().

Microreactor and method for loading a liquid

A microfluidic device, comprising: a semiconductor body, having a first side and a second side, opposite to one another in a first direction; and at least one well, configured for containing a fluid, extending in the semiconductor body starting from the first side and being delimited at the bottom by a bottom surface. The microfluidic device further comprises a stirring structure integrated in the well at the bottom surface, the stirring structure including a first stirring portion coupled to the semiconductor body and provided with at least one first suspended beam configured for being moved in a second direction so as to generate, in use, agitation of the fluid present in said well.

Microfluidic device with integrated stirring structure and manufacturing method thereof

A cartridge for an optical analysis, including a supporting body, having a first face and a second face opposite to one another; a plurality of wells adapted to receive a biological solution to be analyzed, the wells extending in the supporting body on the first face; at least one biocompatible layer extending inside each well; an anti-reflection layer extending on the first face outside the wells; and a reflection layer extending inside each well. Methods of using same are also provided.

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Tremestieri Etneo, Italy

Sabrina Conoci