Systems, methods and media are disclosed for identifying the crossing of a virtual barrier. A person in a 3D image of a room may be circumscribed by a bounding box. The position of the bounding box may be monitored over time, relative to the virtual barrier. If the bounding box touches or crosses the virtual barrier, an alert may be sent to the person being monitored, a caregiver or a clinician. Bounding box tracking may be used in addition to or instead of an initial tracking process, such as skeletal tracking.

A bio-information measuring apparatus bio-information measuring method are provided. The bio-information measuring apparatus includes: a pulse wave obtainer configured to obtain a pulse wave signal, and a processor configured to correct a feature of the obtained pulse wave signal based on a variation in an amplitude of the obtained pulse wave signal, and to measure bio-information based on the corrected feature.

Systems and methods are presented for monitoring brain pulsatility. A change in volume of the brain is estimated based at least in part on an output of a non-contact, surface measuring sensor (e.g., a distance sensor or a camera). A metric indicative of brain pulsatility is then calculated based at least in part on a ratio of the estimated change in volume of the brain relative to a change in arterial blood pressure.

A driving assistance system and a driving assistance method are provided. The driving assistance system includes a physiological information sensing system, an external physical symptom detection system, and a processing device. The physiological information sensing system is configured to sense physiological information of a driver. The external physical symptom detection system is configured to detect an external physical symptom of the driver. The processing device is coupled to the physiological information sensing system and the external physical symptom detection system. When the physiological information of the driver and the external physical symptom of the driver are abnormal, the processing device initiates an emergency procedure.

A physiological monitoring device includes: a sensor interface, a display configured to display information related to the patient, and at least one processor. The at least one processor is configured to: operate the physiological monitoring device into a non-transport mode while docked to one of at least one monitor mount; display first location context information corresponding to a first patient care area on the display while the physiological monitoring device is operating in the non-transport mode in the first patient care area; detect an undocking event in response to undocking the physiological monitoring device from a first monitor mount of the at least one monitor mount, wherein the first monitor mount is located in the first patient care area; and in response to detecting the undocking event, operate the physiological monitoring device in a transport mode, including changing the first location context information to transport context information on the display.

Systems and methods for aiding, supplementing, and/or increasing the monitoring capabilities of responsible persons over a supervised person are disclosed herein. In some implementations, the system includes one or more controlling persons, one or more supervising persons, a supervised person, and a cloud server. Each of the controlling persons and the supervising persons can have a personal electronic device. The supervised person can have a wearable electronic device. The electronic devices allow the controlling persons and the supervising persons to actively communicate with the cloud server to upload data related to the supervised person that is accessibly stored in the cloud server. In turn, the wearable device can include one or more sensors to measure and communicate various bioindicators to the cloud server. The system allows the controlling persons to monitor the health of, development of, and/or current control over the supervised person.

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 wearable analyte breath alert device and method for non-invasive monitoring of an analyte in a sample from a user. The device comprises an outer casing, a forward face having an in-line insignia, a front port and an activation button, a rear face having a detector threshold region, a side port and a LED indicator, a reversible core having a main processor module and a volatile organic compound (VOC) sensor adaptable to detect at least one volatile organic compound of the user. The VOC sensor further comprises a central sensor circuit having at least one nano gas sensor, a sensor signal conditioning unit and an A/D interface. The central sensor circuit is operably connected to a Bluetooth Low Energy (BLE) element having a microcontroller. An alarm component is coupled with the BLE element that alerts the user based on the analyte detected by the nano gas sensor.

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 for monitoring health of a subject based on a physiological response to physical exertion, by processing circuitry of a medical device system, is described that includes detecting a plurality of exertion events of the subject based on a first sensed signal that varies as a function of movement of the subject. The method further includes determining a response of a physiological parameter of the subject to the exertion event for each of the detected exertion events based on second sensed signal that varies as a function of the physiological parameter. The method further includes determining that a change in the responses over time crosses threshold and generating an alert to a user based on the determination that the change crosses the threshold.