According to an embodiment, a method of processing acceleration information by a wearable device is provided, the method including: acquiring the acceleration information indicating acceleration according to movement of the wearable device; acquiring a plurality of acceleration characteristics including a plurality of characteristics of a power spectrum of the acceleration and a range of the acceleration on the basis of the acceleration information; determining characteristic values according to two characteristics determined according to a type of a disease to be monitored among the plurality of acceleration characteristics; and providing an alarm signal in response to the characteristic value falling within an abnormality range.

A tissue hydration monitor and method includes a sensor module having a plurality of LEDs positioned to emit a plurality of different wavelengths of light toward the user's skin and a detector that detects light transmitted and reflected through the user's skin to generate signals corresponding to an intensity of detected light at each of the different wavelengths. A processor/controller module generates a baseline hydration level based on the received signals, calculates a relative hydration level, and generates an output indicative of relative hydration personalized to the user. The housing is secured against the user's skin by an adhesive patch or a strap.

Systems and methods for predicting problem behavior in individuals with developmental and behavior disabilities. A plurality of sensors are configured to collect multimodal data signals of a subject individual including a wearable upper body motion sensing device with a plurality of inertial measurement units (IMUs). An electronic controller is configured to receive output signals from each of IMUs and to model an upper body position of the subject individual based on the output signals from the IMUs. A trained machine-learning model is then applied by providing an input data set that includes multimodal signal data (e.g., including signal data from at least one IMU) and/or features extracted from the multimodal signal data. The machine-learning model is trained to produce as output an indication of whether a precursor to the problem behavior is detected and, in response to detecting the precursor, a notification (or alarm) is generated.

The present disclosure is related to methods, systems and apparatus for performing electrophysiological measurements utilizing three or more electrodes attached to a patient. The system in various embodiments may include three or more electrodes attached to the patient and at least one analog-to-digital converter with external circuitry electrically coupled to the electrodes. The system may further include a microprocessor for driving the analog-to-digital conversion process, various inputs and variable frequency current outputs electrically coupled to the microprocessor for receiving signals from the electrodes and sending driven current signals to the electrodes.

A detection device, a detection system and a detection method capable of detecting accurate position and orientation of a wearable device on a body are provided. A detection device includes a wireless communicator that receives orientation information indicating an orientation of a wearable device disposed on a body from the wearable device by wireless communication, measures an intensity of a radio wave radiated from the wearable device, and outputs intensity information indicating measured intensity of the radio wave; and a calculator that calculates a position and an orientation of the wearable device on the body based on the orientation information and the intensity information.

A method for measuring gut permeability includes administering a solution including a fluorescent contrast agent to a subject; irradiating a location on the skin of the subject to cause a portion of the solution leaked into the bloodstream to fluoresce; obtaining fluorescence data of the intensity of the fluorescence as a function of time; normalising the fluorescence data to obtain normalised data of said intensity as a function of time; and analysing said normalised data to determine the gut permeability by calculating: (a) the first peak value of said intensity; (b) the integral of said intensity with respect to time; (c) the product of the first peak value of said intensity and the time at said peak value; (d) the time at which the first peak value of said intensity occurs; or (e) the first peak value of said intensity divided by the time at which said peak value occurs.

Disclosed is a method for determining an unworn state of a sensor system comprising a pair of sensors configured for mounting on first and second body parts either side of a joint. The method comprises: obtaining one or more measurements from each sensor; calculating a relative angle between the two sensors using one or more of the obtained one or more measurements; calculating, using one or more of the obtained one or more measurements, a joint angle between the first and second body parts, where the joint angle is defined in a plane of normal bending of the joint; and determining, based on the calculated angles, whether either of the sensors is not mounted and if so, determining that the system is in an unworn state. Also disclosed is a system for providing information about a joint.

A method of calibrating a pair of body mounted sensors, the method comprising the steps of: (a) in a baseline position of a joint to be measured, determining a first offset between a measured joint angle and an angle between pair of sensors, one mounted on each side of the joint to be measured, so as to calibrate the sensors; (b) after at least one of the sensors has been removed and reapplied, placing the joint back into the baseline position such that the sensors are in a second configuration relative to each other; and (c) determining a second offset between the measured knee angle and an angle between the pair of sensors in the second configuration in order to recalibrate the sensors such that, in each of the first and second configurations, the same joint angle for the baseline position is reported.

Embodiments provide physiological measurement systems, devices and methods for continuous health and fitness monitoring. A wearable strap may detect reflected light from a user's skin, where data corresponding to the reflected light is used to automatically and continually determine a heart rate of the user. The wearable strap may monitor heart rate data including heart rate variability, resting heart rate, and sleep quality. The systems may include a processing module that generates an indicator of physical recovery based on the heart rate data. The recovery indicator may be used to determine strain related to an exercise routine, qualitative information on the user's health, whether to alter a user's exercise plan, and so forth.

Methods, devices, systems, and kits are provided that buffer the time spaced glucose signals in a memory, and when a request for real time glucose level information is detected, transmit the buffered glucose signals and real time monitored glucose level information to a remotely located device, process a subset of the received glucose signals to identify a predetermined number of consecutive glucose data points indicating an adverse condition such as an impending hypoglycemic condition, confirm the adverse condition based on comparison of the predetermined number of consecutive glucose data points to a stored glucose data profile associated with the adverse condition, where confirming the adverse condition includes generating a notification signal when the impending hypoglycemic condition is confirmed, and activate a radio frequency (RF) communication module to wirelessly transmit the generated notification signal to the remotely located device only when the notification signal is generated.