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    Processing of electrophysiological signals
    21.
    发明授权
    Processing of electrophysiological signals 有权

    公开(公告)号：US11229404B2

    公开(公告)日：2022-01-25

    申请号：US16195114

    申请日：2018-11-19

    Applicant: STMicroelectronics S.r.l.

    Inventor： Francesco Rundo ,  Sabrina Conoci ,  Piero Fallica ,  Rosalba Parenti ,  Vincenzo Perciavalle

    IPC: A61B5/00 ,  A61B5/021 ,  A61B5/026 ,  A61B5/18 ,  A61B5/16 ,  G06N3/08 ,  A61B5/024 ,  G16H10/40

    Abstract: 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.

    METHOD OF PROCESSING ELECTROPHYSIOLOGICAL SIGNALS TO COMPUTE A VIRTUAL VEHICLE KEY, CORRESPONDING DEVICE, VEHICLE AND COMPUTER PROGRAM PRODUCT
    23.
    发明申请
    METHOD OF PROCESSING ELECTROPHYSIOLOGICAL SIGNALS TO COMPUTE A VIRTUAL VEHICLE KEY, CORRESPONDING DEVICE, VEHICLE AND COMPUTER PROGRAM PRODUCT 有权

    公开(公告)号：US20210068739A1

    公开(公告)日：2021-03-11

    申请号：US17009503

    申请日：2020-09-01

    Applicant: STMicroelectronics S.r.l.

    Inventor： Francesco Rundo ,  Sabrina Conoci ,  Concetto Spampinato

    IPC: A61B5/18 ,  A61B5/00 ,  A61B5/117 ,  A61B5/024 ,  G06N3/04 ,  G06F21/32

    Abstract: 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 AND CORRESPONDING SYSTEM, VEHICLE, AND COMPUTER PROGRAM PRODUCT
    24.
    发明申请
    METHOD OF PROCESSING ELECTROPHYSIOLOGICAL SIGNALS AND CORRESPONDING SYSTEM, VEHICLE, AND COMPUTER PROGRAM PRODUCT 审中-公开

    公开(公告)号：US20190117096A1

    公开(公告)日：2019-04-25

    申请号：US16167817

    申请日：2018-10-23

    Applicant: STMicroelectronics S.r.l.

    Inventor： Francesco Rundo ,  Sabrina Conoci ,  Piero Fallica

    IPC: A61B5/024 ,  A61B5/04 ,  B60W40/08

    Abstract: 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.

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