Systems and methods for aiding a clinician in the proper positioning, placing or otherwise locating of a non-contact detector component of a non-contact patient monitoring system are described. The systems and methods may employ a targeting aid superimposed on a display screen component of the non-contact patient monitoring system, the targeting aid being designed to assist the clinician in properly locating the non-contact detector for proper and accurate functioning of the non-contact patient monitoring system. The systems and methods described herein may also employ a bendable mounting arm to which the non-contact detector is attached such that the non-contact detector can be easily moved into the proper location when used in conjunction with the targeting aid superimposed on the display.

The present invention relates to a device, system and method for determining a vital sign of a person. To improve accuracy and reliability of vital sign determination, the device comprises an input unit (20) for obtaining a vital sign related signal of at least a body part of the person, from which a vital sign can be derived, a body part position determining unit (21) for determining if said body part of the person is in contact with a support or not and generating a contact signal indicating if said body part is in contact with the support or not, a quality metric setting unit (22) for setting, based on said contact signal, a quality metric for use in the determination of a vital sign of the person, and a vital sign deriving unit (23) for deriving a vital sign from the obtained vital sign related signal, wherein the set quality metric is used in the derivation of the vital sign and/or in a judgment of the reliability of a derived vital.

A health monitoring system and corresponding method for monitoring a physiological condition of a user may include collecting, by a monitoring device, measurements representing physiological signals of the body, transmitting the measurements from the monitoring device to a local device, and receiving, at a remote server, the measurements and additional data from the local device. The remote server may include a processing module, a review portal and a clinician portal, such that the remote server may be arranged to automatically classify the measurements representing physiological signals of the body, verify the classifications, and provide the verified measurements at a clinician portal.

A photoplethysmogram (PPG) sensor includes a pixel array that collects light, a pixel sampler that converts the light collected through the pixel array into a plurality of pixel data, an effective area determiner that determines an effective area and a non-effective area of the pixel array based on the pixel data, a power controller that is operable to cut off power to the non-effective area of the pixel array, and a PPG data generator that generates PPG data from pixel data corresponding to the effective area among the pixel data.

Systems, methods, and devices of a health device network may include: a non-invasive glucometer that non-invasively measures analyte levels; an invasive glucometer communicatively coupled directly to the non-invasive glucometer; a cloud-based server communicatively coupled to the non-invasive glucometer or the invasive glucometer; a user device communicatively coupled to the cloud-based server; and/or a user interface that displays the invasive glucose measurement, the non-invasive glucose measurement, a data batch, and/or processed data to the user. The non-invasive glucometer and/or the invasive glucometer may aggregate an invasive glucose measurement and a non-invasive glucose measurement into the data batch. A data analytics application on the cloud-based server may be configured to: integrate the invasive glucose measurement and the non-invasive glucose measurement; identify a correlation between the invasive glucose measurement and the non-invasive glucose measurement; and/or generate a predictive model based on the invasive glucose measurement and the non-invasive glucose measurement.

Systems, methods, and devices of a health device network may include: a non-invasive glucometer that non-invasively measures analyte levels; an invasive glucometer communicatively coupled directly to the non-invasive glucometer; a cloud-based server communicatively coupled to the non-invasive glucometer or the invasive glucometer; a user device communicatively coupled to the cloud-based server; and/or a user interface that displays the invasive glucose measurement, the non-invasive glucose measurement, a data batch, and/or processed data to the user. The non-invasive glucometer and/or the invasive glucometer may aggregate an invasive glucose measurement and a non-invasive glucose measurement into the data batch. A data analytics application on the cloud-based server may be configured to: integrate the invasive glucose measurement and the non-invasive glucose measurement; identify a correlation between the invasive glucose measurement and the non-invasive glucose measurement; and/or generate a predictive model based on the invasive glucose measurement and the non-invasive glucose measurement.

A method, intended for the evaluation of the quality of at least one periodic or quasi-periodic physiological signal, which includes the steps of: segmenting the physiological signal temporally into a plurality of signal segments; for each given signal segment, determining a distance representative of a shape difference between the given signal segment and at least one signal segment temporally offset relative to the given signal segment; and determining a quality index of the given signal segment according to the distance determined for the given signal segment.

A method for generating PPG signals may include photographing a skin surface to generate fragment video data; extracting fragment frame images from the fragment video data; performing image quality detection on the fragment frame images to generate an image quality detection result; when the image quality detection result indicates an up-to-standard image, performing one-dimensional red and green light signal extraction on the fragment frame images to generate first red and green signals; performing signal band-pass filtering preprocessing on the first red and green signals to generate second red and green signals; performing maximum frequency difference determination on the second red and green signals to generate a first determination result; when the first determination result indicates an up-to-standard signal, performing signal-to-noise ratio determination on the second red and green signals to generate a second determination result; and when the second determination result indicates an up-to-standard signal, generating a first PPG signal.

Disclosed are one or more proximity sensors. At least one of the proximity sensors includes a first dielectric layer, an electrically conductive layer, and an electrode. The first dielectric layer includes an inner surface and an outer surface. The electrically conductive layer is positioned proximate to one of the inner surface or the outer surface of the first dielectric layer. The electrode includes an outer surface. The outer surface of the electrode is positioned proximate the inner surface of the first dielectric layer. The outer surface of the electrode and the electrically conductive layer define a gap.

An information processing method that is executed by a computer, the method comprising: acquiring motion information detected by a motion detection device, the motion detection device configured to detect a motion of a subject; storing the acquired motion information; deriving reference motion information on a left half of a body of the subject and reference motion information on a right half of the body of the subject based on the stored motion information in a predetermined period; and determining whether an abnormal state in which there is a possibility of cerebral infarction in the subject is present based on the derived reference motion information and motion information on the left half of the body of the subject and motion information on the right half of the body of the subject at a detection time subsequent to the predetermined period.