REAL-TIME CORRECTIVE ACTIONS FOR OXYGEN SATURATION PREDICTIONS

    公开(公告)号:US20240347198A1

    公开(公告)日:2024-10-17

    申请号:US18626077

    申请日:2024-04-03

    Applicant: Covidien LP

    CPC classification number: G16H50/20 A61B5/14542

    Abstract: In some examples, a computing system tracks, across a plurality of predictions, prediction performance of a first oxygen saturation prediction model used by one or more patient monitoring devices by comparing a respective prediction made by the first oxygen saturation prediction model to a corresponding ground truth. The computing system determines whether the prediction performance of the first oxygen saturation prediction model meets a performance metric, wherein the performance metric includes an accuracy level, a specificity level, a sensitivity level, or any combination thereof. The computing system may, in response to determining that the prediction performance of the first oxygen saturation prediction model does not meet the performance metric, cause the one or more patient monitoring devices to switch to a second oxygen saturation prediction model to predict future oxygen saturation levels of one or more patients.

    BLOOD PRESSURE AND AUTOREGULATION MONITORING
    33.
    发明公开

    公开(公告)号:US20240197265A1

    公开(公告)日:2024-06-20

    申请号:US18417850

    申请日:2024-01-19

    Applicant: COVIDIEN LP

    CPC classification number: A61B5/7278 A61B5/021 A61B5/7203 A61B5/7257

    Abstract: In some examples, a method includes receiving a signal indicative of a blood pressure of a patient and identifying at least one first portion of the signal comprising a first characteristic of the signal exceeding a first threshold. The method also includes identifying at least one first portion of the signal comprising a second characteristic of the signal exceeding a second threshold, the first characteristic being different than the second characteristic. The method further includes determining a filtered signal indicative of the blood pressure of the patient by excluding the at least one first portion and the at least one second portion from the signal. The method includes determining a set of mean arterial pressure values based on the filtered signal and determining an autoregulation status of the patient based on the set of mean arterial pressure values.

    OXYGEN SATURATION MONITORING USING ARTIFICIAL INTELLIGENCE

    公开(公告)号:US20230263478A1

    公开(公告)日:2023-08-24

    申请号:US18161936

    申请日:2023-01-31

    Applicant: Covidien LP

    CPC classification number: A61B5/7267 A61B5/7275 A61B5/14542 A61B5/1495

    Abstract: In some examples, a system includes processing circuitry configured to determine that an oxygen saturation level of a patient is at or below a desaturation threshold, and, in response, determine whether the oxygen saturation level is at or below the desaturation threshold at the end of a calculation period. The processing circuitry may, in response to determining that the oxygen saturation level of the patient is at or below the desaturation threshold at the end of the calculation period, predict, using an oxygen saturation prediction model, whether the oxygen saturation level of the patient will increase above the desaturation threshold by the end of a predefined time period. In response to predicting that the oxygen saturation level of the patient will increase above the desaturation threshold by the end of the predefined time period, the processing circuitry refrains from outputting an indication of the patient experiencing an oxygen desaturation event.

    HEART RATE VARIABILITY DETERMINATION

    公开(公告)号:US20230099028A1

    公开(公告)日:2023-03-30

    申请号:US17822284

    申请日:2022-08-25

    Applicant: Covidien LP

    Abstract: An example device for determining heart rate variability (HRV) includes a memory configured to store a sensed pulse rate signal indicative of one or more sensed pulse rates and processor circuitry. The processor circuitry is configured to receive the sensed pulse rate signal and determine that a pulse rate of the sensed pulse rate signal, within a predetermined time period, is erroneous. The processor circuitry is configured to process the erroneous pulse rate to create a modified sensed pulse rate signal. The processor circuitry is configured to determine an HRV value based on the modified pulse rate signal over the predetermined time period and output information indicative of the determined HRV value.

    Blood pressure and autoregulation monitoring

    公开(公告)号:US11478200B2

    公开(公告)日:2022-10-25

    申请号:US16218160

    申请日:2018-12-12

    Applicant: Covidien LP

    Abstract: In some examples, a method includes receiving a signal indicative of a blood pressure of a patient and identifying at least one first portion of the signal comprising a first characteristic of the signal exceeding a first threshold. The method also includes identifying at least one first portion of the signal comprising a second characteristic of the signal exceeding a second threshold, the first characteristic being different than the second characteristic. The method further includes determining a filtered signal indicative of the blood pressure of the patient by excluding the at least one first portion and the at least one second portion from the signal. The method includes determining a set of mean arterial pressure values based on the filtered signal and determining an autoregulation status of the patient based on the set of mean arterial pressure values.

    Determining a limit of autoregulation

    公开(公告)号:US11419558B2

    公开(公告)日:2022-08-23

    申请号:US15980235

    申请日:2018-05-15

    Applicant: Covidien LP

    Abstract: In some examples, a device includes processing circuitry configured to receive first and second signals indicative of first and second physiological parameters and determine a trendline function based on values of first and second physiological parameters. The processing circuitry is further configured to determine transformed values of the first physiological parameter based on the trendline function. The processing circuitry is configured to determine correlation coefficient values for the transformed values of the first physiological parameter and the values of the second physiological parameter. The processing circuitry is further configured to determine a limit of autoregulation of the patient based on the correlation coefficient values. The processing circuitry is configured to determine an autoregulation status based on the estimate of the limit of autoregulation and output, for display, an indication of the autoregulation status.

    Calibration for continuous non-invasive blood pressure monitoring using artificial intelligence

    公开(公告)号:US11367525B2

    公开(公告)日:2022-06-21

    申请号:US16723678

    申请日:2019-12-20

    Applicant: Covidien LP

    Abstract: A system for continuous non-invasive blood pressure monitoring may include processing circuitry configured to determine calibration data for a continuous non-invasive blood pressure model at a calibration point, receive, from an oxygen saturation sensing device, a PPG signal at a particular time subsequent to the calibration point, derive values of the set of metrics for the patient from the PPG signal, and determine, using the continuous non-invasive blood pressure model and based at least in part on inputting the calibration data determined at the calibration point, the values of the set of metrics, and an elapsed time at the particular time since the calibration point into the continuous non-invasive blood pressure model, a blood pressure of the patient at the particular time.

    AI-based video tagging for alarm management

    公开(公告)号:US11328572B2

    公开(公告)日:2022-05-10

    申请号:US16854059

    申请日:2020-04-21

    Applicant: Covidien LP

    Abstract: Implementations described herein discloses, a method of AI based video tagging for alarm management includes receiving, using a processor, a video stream, the video stream comprising a sequence of images for at least a portion of a patient, determining, using the processor, a physiological parameter for the patient based on the sequence of images, detecting, using machine learning, presence of a noise object and setting a interaction-flag to a positive value in response to detecting the noise object, comparing a quality level of the sequence of images with a threshold quality level, and modifying an alarm level based on the value of the interaction-flag and comparison of the quality level of the sequence of depth images with the threshold quality level.

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