A technology for a wearable medical device for monitoring medical parameters. Medical measurement data can be received at the wearable medical device from a medical measurement sensor attached to the wearable medical device or a medical measurement sensor in communication with the wearable medical device. A calibration coefficient can be determined for calibrating the wearable medical device based on the medical measurement data. The wearable medical device can be calibrated based on the calibration coefficient.

Methods and devices to monitor an analyte in body fluid are provided. Embodiments include continuous or discrete acquisition of analyte related data from a transcutaneously positioned in vivo analyte sensor automatically or upon request from a user. The in vivo analyte sensor is coupled to an electronics unit holding a memory with instruction to cause processing circuitry to initiate a predetermined time period that is longer than a predetermined life of the sensor, during the predetermined time period, convert signals from the sensor related to glucose to respective corresponding glucose levels, without relying on any post-manufacture independent analyte measurements from a reference device, and at the expiration of the predetermined time period, disable, deactivate, or cease use of one or more feature.

Apparatus for providing muscular biofeedback, comprising: facewear supporting biosensors arranged such that, in use, the biosensors are situated for detecting activity of a predetermined set of facial muscles; a feedback unit for providing biofeedback to a wearer of the facewear; and a control unit coupled to the biosensors and the feedback unit and arranged to identify patterns in the signals from the biosensors characteristic of one or more predefined imbalances in muscle activity between the left and right sides of the face; wherein the control unit is configured to, on identifying a pattern in the signals from biosensors characteristic of a first predefined imbalance in muscle activity between the left and right sides of the face, cause the feedback unit to provide biofeedback in correspondence with the imbalance.

Medical devices, systems and methods are provided. One method involves obtaining fabrication process measurement data for a plurality of instances of a sensing element, obtaining reference output measurement data from the plurality of instances in response to a reference stimulus, determining a predictive model for a measurement output of the sensing element as a function of fabrication process measurement variables based on the relationship between the fabrication process measurement data and the reference output measurement data, generating a simulated output measurement distribution across a range of the fabrication process measurement variables using the predictive model, identifying performance thresholds for the measurement output based on the simulated output measurement distribution, obtaining output measurement data from the instance of the sensing element in response to the reference stimulus, and verifying the output measurement data satisfies the performance threshold prior to calibrating a subsequent instance of the sensing element.

A computer implemented method for determining heart arrhythmias based on cardiac activity that includes under control of one or more processors of an implantable medical device (IMD) configured with specific executable instructions to obtain far field cardiac activity (CA) signals at electrodes located remote from the heart, and obtain acceleration signatures, at an accelerometer of the IMD, indicative of heart sounds generated during the cardiac beats. The IMD is also configured with specific executable instructions to declare a candidate arrhythmia based on a characteristic of at least one R-R interval from the cardiac beats, and evaluate the acceleration signatures for ventricular events (VEs) to re-assess a presence or absence of at least one R-wave from the cardiac beats and based thereon confirming or denying the candidate arrhythmia.

A magnetometer-based metal detection device and methods of use are described. The device includes a proximal portion, a central body and a distal portion, and at least one magnetometer positioned within or on the distal portion. The at least one magnetometer includes at least one sensor capable of sensing a magnetic field in three orthogonal axes. Also described is a method of calibrating the device to achieve rotational invariance, and a method of determining a directionality or directional line along which a target metal object lies.

A system and method for personalized calibration for glucose sensing. In some embodiments, the method includes obtaining a plurality of first glucose measurements from a subject, at a plurality of first sampling times during a time interval, using a first glucose sensor; obtaining a plurality of second glucose measurements from the subject, at a plurality of second sampling times during the time interval, using a second glucose sensor; and estimating a first in-vivo calibration parameter for the first glucose sensor and the second glucose sensor, based on the first glucose measurements and the second glucose measurements, wherein a first in-vivo time-constant, relating blood glucose to an output of the first glucose sensor, is different from a second in-vivo time-constant, relating blood glucose to an output of the second glucose sensor.

An apparatus for estimating blood glucose is provided. The apparatus for estimating blood glucose may include a spectrometer configured to measure a spectrum from an object, and a processor configured to monitor a change in a contact state between the object and the spectrometer, determine a calibration section based on the monitored change in the contact state, extract a background signal from a spectrum of the determined calibration section, and generate a personalized blood glucose estimation model based on the extracted background signal.

Apparatus and methods are operative to probe the condition of a sensor either initially, at any point thereafter or continuously during a continuous sensor operation for measuring an analyte in a bodily fluid (such as performed by, e.g., a continuous glucose monitoring (CGM) sensor). Results of the probe may include calibration indices determined from electrical signals obtained during the probe. The calibration indices may indicate whether in-situ adjustment of the sensor's calibration should be performed either initially and/or at random check points. Probing potential modulation parameters also may be used during analyte calculations to reduce the effects of lot-to-lot sensitivity variations, sensitivity drift during monitoring, temperature, interferents, and/or the like. Other aspects are disclosed.

A dynamic neuropsychological assessment tool according to an embodiment utilizes speech recognition, speech synthesis and machine learning to assess whether a patient is at risk for a neurological disorder, such as Alzheimer's disease. The dynamic neuropsychological assessment tool enables self-administration by a patient. The tool performs pre-test validation operations on the test environment, test equipment, and the patient's capability for performing the test at that time. The tool also enables dynamic modification of a questionnaire presented to the patient while the patient completes the questionnaire. Also provides the dynamic modification of which tests to present the patient with. The modification can be rule based or modified by a provider. The dynamic neuropsychological assessment tool enables providers and administrators to modify and improve tests and validate them using machine learning based on previously completed assessments and results.