Systems and methods for blood pressure estimation using smart offset calibration can include a computing device associating a calibration photoplethysmographic (PPG) signal generated from a first sequence of image frames obtained from a photodetector of the computing device with one or more measurement values generated by a blood pressure measurement device different from the computing device. The computing device can obtain a recording PPG signal generated from a second sequence of image frames obtained from the photodetector, and identify a calibration model from a plurality of blood pressure calibration models based on the calibration PPG signal and the recording PPG signal. The computing device can generate a calibrated blood pressure value using the recording PPG signal, features associated with the calibration PPG signal and the identified calibration model.

A biological information measuring device includes a case section having, in sectional view, a trapezoidal shape including an upper base and a lower base shorter than the upper base, a first leg crossing the upper base and the lower base, and a second leg that is an opposite side of the first leg, a display section disposed on the second leg side, a circuit board housed in the case section, a flexible board configured to electrically connect the circuit board and the display section, and a pulse-wave sensor section disposed on the first leg side and configured to detect a pulse wave signal of a user. An atmospheric pressure sensor configured to detect an atmospheric pressure is housed in the case section. The flexible board is disposed on the lower base side and the atmospheric pressure sensor is disposed not to overlap the pulse wave sensor in plan view.

The systems and methods described herein determine metrics of cardiac or vascular performance, such as cardiac output, and can use the metrics to determine appropriate levels of mechanical circulatory support to be provided to the patient. The systems and methods described determine cardiac performance by determining aortic pressure measurements (or other physiologic measurements) within a single heartbeat or across multiple heartbeats and using such measurements in conjunction with flow estimations or flow measurements made during the single heartbeat or multiple heartbeats to determine the cardiac performance, including determining the cardiac output. By utilizing a mechanical circulatory support system placed within the vasculature, the need to place a separate measurement device within a patient is reduced or eliminated. The system and methods described herein may characterize cardiac performance without altering the operation of the heart pump (e.g., without increasing or decreasing pump speed).

A method of presenting data from a remote sensor that is monitoring a subject includes obtaining a data stream from the remote sensor, wherein the data stream includes a sensor metric, a metric identifier, dynamically updated integrity information about an accuracy of the sensor metric, and a diagnostic assessment of a health condition of the subject, and then displaying, via a display associated with the client device, the diagnostic assessment of the health condition of the subject, a metric statistic associated with the diagnostic assessment, and a recommendation as to an action to be taken by the subject.

An electronic device, a method to be executed by an electronic device, and a non-transitory memory storing a program for causing an electronic device to execute processes include acquiring a pulse wave of a subject, and estimating a blood glucose level and/or a lipid level of the subject based on a displacement ratio in the pulse wave. The displacement ratio comprises a ratio between a displacement of the pulse wave at a peak of the pulse wave and a displacement of the pulse wave at a predetermined time after the peak of the pulse wave, and the predetermined time is a fixed value.

Disclosed herein are in vivo non-invasive methods and devices for the measurement of the hemodynamic parameters, such as blood pressure, cardiac output, stroke volume and vascular tone, of a subject, and the mechanical anelastic in vivo properties of the subject's arterial blood vessels. An exemplary method requires obtaining the peripheral pulse volume waveform (PVW), the peripheral pulse pressure waveform (PPW), and the peripheral pulse velocity waveform (PUW) from the same artery; calculating the time phase shift between the PPW and PVW, and the plot of pulse pressure versus pulse volume; and determining the blood pressures and power law components of the anelastic model from the waveforms PPW and PVW, the cardiac output from the waveforms PPW and PUW, and the quality factor of the artery based upon the calculations. The disclosed methods and devices can be used to diagnose and treat cardiovascular disease in a subject in need thereof.

A non-contact facial blood pressure measurement method based on 3D CNN is disclosed, which belongs to the technical field of computer vision. The method includes the following steps. S110: collecting an actual face video sample and training a blood pressure prediction model based on face images using 3D CNN neural network. S120: obtaining a face video in real time through a HD camera. S130: recognizing face key points in the face video obtained in S120 through dlib face recognition model, selecting a face region of interest, and extracting face images from the region. S140: performing a wavelet transform operation on the face images extracted in S130 to remove noise. S150: inputting seven consecutive frames of the face images into the 3D CNN blood pressure prediction model trained in S110 to obtain a blood pressure value of the measured person. The disclosure realizes non-contact facial blood pressure measurement.

An apparatus for estimating bio-information, includes a sensor including a cover having a transmitting area provided at a center of the cover, and non-transmitting areas provided at both edges of the cover, a light source configured to emit light onto an object that is in contact with the cover, and a detector configured to detect a first optical signal of the emitted light that is scattered or reflected from the object after passing through the transmitting area, and a second optical signal of the emitted light that is reflected from the non-transmitting areas. The apparatus further includes a processor configured to estimate bio-information, based on the detected first optical signal and the detected second optical signal.

A method for monitoring blood pressure (BP) of a user using a cuffless monitoring system comprising a pulsatility waveform measuring device configured to measure a pulsatility waveform signal of the user, the method comprising an initialization routine (10) including performing an adequacy routine (20) for adjusting the measurement parameters of the pulsatility waveform measuring device (103); and performing a reliability test for determining a reliability of the measurement. The method provides incremental feedback of the adequacy of the acquired signals, the reliability of pulsatility waveforms, and the repeatability of the absolute BP values.

An exemplary embodiment of the present disclosure provides systems and methods for non-invasively measuring blood pressure, the system and methods comprise a wearable device having a first surface, a first sensor positioned on the first surface of the wearable device, the first sensor configured to receive a first signal, wherein the first signal is indicative of a first blood-volume change in a first vessel of a subject, a second sensor positioned within the wearable device, the second sensor configured to receive a second signal, wherein the second signal is indicative of a cardiac mechanical motion of the subject, and a processor positioned within the wearable device, the processor configured to generate an output based at least on the first signal and the second signal, the output representing a blood pressure measurement of the subject.