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.

Determining a physical state of a person includes detecting positions of different portions of the person, transforming detected positions into a point cloud having a density that varies according to movement of each of the portions, correlating movement and position data from the point cloud with known physical state positions and transitions between different states, choosing a particular physical state by matching the data from the point cloud with the particular physical state, and obtaining vital signs of the person during an optimal period of time for automatic capturing of vital signs by detecting when the person is in a particular state. The particular state may be a static state. The static state may be standing, sitting, or laying down. The vital signs may include measuring a breathing rate and measuring a heartbeat rate. Vital signs may be obtained by detecting pulsations in the point cloud representing breathing and heartbeats.

Presented are concepts for monitoring a physical or mental capability of a person. One such concept employs the step of detecting a value of a property of the person or an object manipulated by the person. A trend in a physical or mental capability of the person may then be determined based on the detected value and historical data relating to one or more previously detected values of the property.

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.

The present invention discloses a virtual community system for an elderly health service based on a big data technology, including an information obtaining module for obtaining personal information of elderly people, a management platform for processing user information, a recommendation module for sending recommended information to a user, and a backend terminal for providing a manual service. The information obtaining module includes a locator, configured to obtain the elderly people's position information to prevent the elderly people from getting lost; and a health bracelet, configured to detect the elderly people's heart rate and blood pressure which directly reflect the elderly people's physical condition. The present invention is designed to meet an existing need. One-time treatment for a lifetime medical service is implemented based on existing medical data and personal data acquired by health equipment.

In an example, the technique also detects and measures vital signs of each human target by continuous, non-intrusive method. In an example, the vital signs of interest include a heart rate and a respiratory rate, which can provide valuable information about the human's wellness. Additionally, the heart rate and respiratory rate can also be used to identify a particular person, if more than two target humans living in a home. Of course, there can be other variations, modifications, and alternatives.

The object of the present invention is to assess the driving aptitude of a target person. Provided is a driving aptitude assessment apparatus 200 including: functional impairment degree assessment means configured to assess the degree of functional impairment of a brain of a target person on the basis of test result information indicating a result of a neuropsychological test administered to the target person and head image data obtained by tomography of a head of the target person; and driving aptitude assessment means configured to assess the driving aptitude of the target person on the basis of an assessment result by the functional impairment degree assessment means.

The present invention relates to a light-weight, small and portable ambulatory sensor for measuring and monitoring a person's physical activity. Based on these measurements and computations, the invented system quantifies the subject's physical activity, quantifies the subject's gait, determines his or her risk of falling, and automatically detects falls. The invention combines the features of portability, high autonomy, and real-time computational capacity. High autonomy is achieved by using only accelerometers, which have low power consumption rates as compared with gyroscope-based systems. Accelerometer measurements, however, contain significant amounts of noise, which must be removed before further analysis. The invention therefore uses novel time-frequency filters to denoise the measurements, and in conjunction with biomechanical models of human movement, perform the requisite computations, which may also be done in real time.

According to an aspect there is provided an apparatus for determining a measure of the physical fitness of a subject, the apparatus comprising a processing unit that is configured to receive a first measurement signal from a first sensor that measures the force or pressure exerted on an object by the subject over time, the first measurement signal comprising measurements representing the force or pressure exerted on the object during a first movement in which the subject sits down on the object and/or during a second movement in which the subject stands up after sitting on the object; and analyze the first measurement signal to determine the measure of the physical fitness of the subject.

The invention relates to a method and apparatus for providing feedback to a user, in particular relating to the fall risk of the user and/or relating to advice to reduce the fall risk of the user. According to an embodiment, there is provided an apparatus for providing feedback to a user, the apparatus comprising a user interface for providing feedback to the user; and a processing unit. The processing unit is configured to obtain measurements of the fall risk of the user over a time period, the time period comprising at least one time portion in which the fall risk of the user increases to a first threshold value while moving, the user rests for a resting period when the fall risk reaches the first threshold value, and the user subsequently resumes moving; analyse the measurements of the fall risk of the user to determine the duration of each resting period and the fall risk of the user at the end of each resting period when the user subsequently resumes moving; determine a fall risk recovery profile for the user from the duration of each resting period and the fall risk of the user at the end of each resting period; determine the duration of a resting period required for the fall risk of the user to decrease to a second threshold value using the fall risk recovery profile; and provide feedback to the user on the determined duration via the user interface.