Embodiments of the present technology include a wearable physiological monitoring device, related algorithms and software that are tied to a portable electronic device for readout. The wearable device can perform real-time measurement of a number of physiological and environmental parameters including heart rate, pulse oximetry, respiration, movement, environmental particulate matter, moisture, temperature (e.g., ambient air and body temperatures) and geospatial location. Some embodiments may establish a physiological baseline for a patient by measuring the above parameters during a healthy state. Collected data can be wirelessly transmitted to a portable electronic device or monitoring and feedback platform where software will analyze the data and make assessments of the device wearer's health based upon the wearer's baseline.

A method for predicting a future dental situation for a patient. Acquiring historical data including at least: previous time point and context parameter values. Acquiring at a time point all the data related to the current dental situation, including at least: the current time point, context parameter values at the current time point, statistical analysis of the historical data and the current data, so as to predict, at a future time point, at least one future dental situation for the current patient. Depending on the future dental situation, (re)evaluation of the benefit of an orthodontic treatment. Steps may include creating a three-dimensional digital reference model, acquiring at least one two-dimensional image, analysing each updated image and creation, searching, for each updated image, and collecting data relative to the updated reference model and relative to the orthodontic appliance.

A fingerprint capture system, a fingerprint capture device, an image processing apparatus, a fingerprint capture method, and a storage medium that can acquire a high quality fingerprint image are provided. A disclosed example includes: a capture unit that captures a fingerprint; an image processing unit that processes a transferred fingerprint image captured by the capture unit; a display unit on which the fingerprint image transferred to the image processing unit is displayed; a recording unit where the fingerprint image transferred to the image processing unit is recorded by the image processing unit; and an instruction unit that inputs, in the image processing unit, a record instruction that instructs the image processing unit to record the fingerprint image in the recording unit. The image processing unit records, in the recording unit, the fingerprint image displayed on the display unit at the time the record instruction is input by the instruction unit.

A system for monitoring a person may include a person-worn sensor device including at least one sensor (e.g., at least one accelerometer, magnetometer, altimeter, etc.) configured to collect sensor data and a processor to process data from the person-worn sensor device. The processor may be configured to determine or access an orientation of a physical support apparatus (e.g., bed, table, wheelchair, chair, sofa, or other structure for supporting the person), receive sensor data collected by the person-worn sensor device, calculate an orientation of the person relative to the physical support apparatus based on (a) the orientation of the physical support apparatus and (b) the sensor data collected by the person-worn sensor device, and identify, based on the determined orientation of the person relative to the physical support apparatus, a physical support apparatus exit condition indicating an occurrence or anticipated occurrence of the person exiting the physical support apparatus.

A baby foot strap comprises a strap with an opening for a heel and a flange that wraps over the top of the foot, and at least one sensor attached to an interior of the strap, so as to monitor one or more desired health parameters of the baby.

The present application discloses a intelligent light fixture management method based on children's sleep, comprising: controlling a target light fixture to turn on, when the child is on the target bed; controlling the target light fixture to turn off, when the child is confirmed to fall asleep on the target bed; obtaining body parameter information and action information of the child when the child is sleeping; controlling the target light fixture to turn on, when the body parameter information or action information of the child when the child is sleeping indicates that the child is about to wake up. In this way, when the child is preparing to sleep in the bed, the light fixture is turned on to improve the security of the child before going to sleep, assisting that the child get to sleep quickly. After it's found that the child has fallen asleep, the light fixture is turned off to avoid the waste of electric energy. At the same time, the body parameter information and action information of the child when the child is sleeping are monitored, when the body parameter information or action information when the child is sleeping indicates that the child is about to wake up, the light fixture is turned on to ensure that the child will not feel lack of security because of afraid of darkness when waking up at night, thereby ensuring that children can continue to enter a normal state of sleep after waking up.

A process, establishing Bluetooth pairing between a patient sensor (1) and a patient monitor (2), includes docking energy contacts (3) of the patient sensor with charging contacts (4) of a charging device (5) for charging a battery (6) of the patient sensor with an automatic detection of docking of the patient sensor with the charging device by a monitor detection device (7) of the patient monitor. The patient monitor is brought into a state of readiness for establishing Bluetooth pairing with the patient sensor. Patient sensor and charging device docking is automatically detected by a sensor detection device (8) of the patient sensor. The patient sensor is brought into a state of readiness for establishing Bluetooth pairing with the patient monitor. Bluetooth pairing between the patient sensor and the patient monitor is automatically established. A patient monitor system (20) is configured for carrying out the process.

Methods, devices, kits and computer-implemented methods for diagnosing (and optionally treating) tuberculous meningitis (TBM) are provided. In one embodiment, the method comprises testing a cerebrospinal fluid (CSF) sample from a subject suspected of having TBM for the presence of MPO and at least two other biomarkers, at least one of the other biomarkers being selected from the group consisting of IFN-γ, sICAM-1, VEGF-A and CXCL8. For example, the method can comprise testing the sample for MPO, IFN-γ and VEGF-A or for MPO, IFN-γ, sICAM-1 and CXCL8. In another embodiment, the method comprises testing a blood sample from a subject suspected of having TBM for the presence of at least one biomarker selected from the group consisting of adipsin (complement factor D), Ab42 and IL-10, and at least two other biomarkers. In one example, the method comprises testing the sample for the presence of adipsin (complement factor D), Ab42 and EL-10.

A person sensor system (1) includes a person sensor (2) to determine personal parameters of a person, a holding device (3) for holding the person sensor (2) on an article of clothing of the person in interaction with the person sensor (2) and a magnetic device (4) with a first magnetic device section (5) and with a second magnetic device section (6) for attracting each other by magnetic force. The first magnetic device section (5) is arranged at the person sensor (2) and the second magnetic device section (6) is arranged at the holding device (3). A magnetic field detection device (7) detects a magnetic field of the magnetic device (4). The person sensor system (1) is configured to set an operating state of the person sensor system (1) as a function of the magnetic field detected. A person monitoring system (28) includes the person sensor system (1).

Systems and methods for detecting a motor developmental delay and/or neurodevelopmental disorder of an infant are described herein. An example method can include receiving motion data associated with the infant's gross motor activity; analyzing, using a machine learning algorithm, the motion data to detect a kinematic feature; comparing the kinematic feature to an expected relationship between the kinematic feature and infant age; and detecting the neurodevelopmental disorder based on the comparison. An infant sensor suit is also described herein. An example infant sensor suit can include an article of clothing; a plurality of sensors; a power source operably coupled to the sensors; and a wireless transmitter operably coupled to the sensors. The sensors, power source, and wireless transmitter can be incorporated into the article of clothing.