A dry electrode and a physiological multi-parameter monitoring equipment are disclosed. The waterproof dry electrode comprises an encapsulation, extraction electrode and a contact surface layer, wherein the extraction electrode and the contact surface layer are connected with each other and disposed in the encapsulation; the contact surface layer comprises an exposed part and an embedded part encapsulation; the encapsulation comprises flexible silica gel and hard plastic portion, the embedded part being embedded into the hard plastic portion, and the hard plastic portion being packaged in the flexible silica gel. Through the above arrangement in the present invention, the dry electrode can reach a waterproof grade of IPX7, which is higher than living waterproof grade of an ordinary dry electrode. The PMPME can be a patch-type acquisition and monitoring equipment which is convenient for long time wearing and physiological multi-parameter monitoring, with excellent sealing and waterproofness, and the electrode is reusable.

The invention relates to a spirometer (1) comprising a MEMS-based thermal fluid flow sensor (13, 13.1, 13.2) for generating a signal in response to a fluid flow generated during inhalation or exhalation; and a microcontroller (14) for calculating the fluid flow from the signal generated by the flow sensor (13, 13.1, 13.2). The spirometer (1) may be connected to other devices, such as a smartphone or a personal computer or any other computing unit which is adapted to collect, store, analyse, exchange and/or display data. The invention further describes the use of the spirometer (1) in measuring a user's lung performance and/or monitoring it over time. Furthermore, the spirometer (1) may be provided in a system together with an air quality measurement device for determining the air quality at a location of interest; and a computing unit for collecting, analysing and correlating the user's lung performance data obtained from the spirometer (1) with the air quality data, and optionally geolocalisation data of said location.

A wearable electronic device is disclosed, including: a housing having a front plate disposed facing in a first direction, a rear plate disposed facing in a second direction opposite to the first direction, at least a part of the rear plate substantially transparent, and a side member defining a space between the front plate and the rear plate, a substrate disposed within the space, a biometric sensor module disposed between the substrate and the rear plate including at least one light source configured to emit light to an exterior of the wearable electronic device and at least one light detector configured to receive reflected light corresponding to the emitted light reflected from the exterior, and at least one magnetic substance disposed between the light source and the light detector to limit an amount of light reaching the biometric sensor module other than the reflected emitted light.

Embodiments of the present invention provide a method for identifying a body position of a detection object in medical imaging, a medical imaging system, and a computer-readable storage medium. The method comprises: receiving an image group by a trained deep learning network, the image group comprising a plurality of pre-scan images in a plurality of directions obtained by pre-scanning a detection object; and outputting body position information of the detection object by the deep learning network.

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 personal monitoring system includes one or more passive biometric sensors and a communication device. A passive biometric sensor is operable to sense a body condition of a body in accordance with a sense signal at a sense frequency to produce sensed data of a body condition. The passive biometric sensor is further operable to transmit an e-field signal via the body regarding the sensed data, wherein the e-field signal is in accordance with an e-field transmit/receive frequency. The communication device is operable to receive the e-field signal via the body. The communication device is further operable to recover the sensed data from the received e-field signal.

The wheal and flare analyzing system analyzes the mast cell reaction to an allergen being administered in a scratch or prick skin test. The system comprises a sensor array and a processing unit. The sensor array includes a plurality of emitters surrounding a receiver at the allergen test site. Energy of various wavelengths is emitted into the allergen test site. An energy receiver measures reflected various wavelengths from the plurality of emitters. A microprocessor is in digital communication with the plurality of emitters and the energy receiver. The reflected wavelengths have an energy return indicative of the intensity of the allergic reaction in the mast cells. The intensity of the allergic reaction is analyzable from the reflected wavelengths and other data over time. A plurality of temperature sensors measuring local dermal temperatures surrounding the sensor array, the local dermal temperature being indicative of the intensity of the allergic reaction.

Inventions herein include at least mostly optically clear orthodontic braces and feet orthotics (collectively referred to as “appliances”) with backscatter based sensors. These two categories of appliances share a common property requiring that the given appliance must be correctly custom manufactured to fit a patient's own particular geometry and dimensions of their teeth and/or feet in order to perform as intended. Incorporating such appliances with backscatter based sensors enables simple, easy, fast, efficient, and cost effective measurements, in real-time or near real-time, of stresses, forces, structural changes, and/or the like in the given appliance; which in turn can aid in determining if adjustments or re-manufacture of the appliance may be needed or desired; and/or wherein such measurements may aid in evaluating performance of the given appliance. In some embodiments, such measurements may also be taken remotely away from a practitioner; and then communicated to a remotely located practitioner.

The present invention provides a closed loop control method in an artificial pancreas and a system using the method, comprising sensing an activity level of a patient by at least one motion sensor and providing signals to at least one processer; then adjusting a series of related algorithms depending partly on the signals by the processer to provide more accurate and reliable data that is the basis of desirable treatment plans, and sending corresponding instructions by the processer for automatic operations of the artificial pancreas to realize a closed loop control.