Embodiments described herein include a device and a non-transitory computer-readable medium. The device includes one or more processors, an analyte sensor, a communication module, and memories. The processors are configured to generate analyte data indicative of a monitored analyte level measured by the analyte sensor corresponding to a first time, generate analyte data indicative of the monitored analyte level measured by the analyte sensor corresponding to a second time, calculate a correction parameter based on the analyte data corresponding to the analyte data corresponding to the first time and analyte data corresponding to the second time, and perform a lag correction to obtain the monitored analyte level using at least the calculated correction parameter. The calculated correction parameter comprises a lag time determined from the analyte data. The performed lag correction comprises a linear correction model based on the calculated correction parameter.

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 method of scanning an oral cavity including: acquiring, using an intraoral scanner (IOS) head, without changing a position of the IOS head, a first image of a first region of interest (ROI) and a second image of a second ROI where the first and the second ROIs are of different portions of a dental arch of the oral cavity and do not overlap; reconstructing depth information for the first and the second ROI; and generating a single model of the dental arch by combing the depth information.

An analyte sensor system is provided. The system includes a base configured to attach to a skin of a host. The base includes an analyte sensor configured to generate a sensor signal indicative of an analyte concentration level of the host, a battery, and a first plurality of contacts. The system includes a sensor electronics module configured to releasably couple to the base. The sensor electronics module includes a second plurality of contacts, each configured to make electrical contact with a respective one of the first plurality of contacts, and a wireless transceiver configured to transmit a wireless signal based at least in part on the sensor signal. The system includes a first sealing member configured to provide a seal around the first and second plurality of contacts within a first cavity. Related analyte sensor systems, analyte sensor base assemblies and methods are also provided.

An example method includes establishing a communications link between an electrophysiology (EP) monitoring system and an implantable medical device (IMD). IMD electrical data is received at the monitoring system via the communications link. The IMD electrical data may be synchronized with EP measurement data to provide synchronized electrical data based on timing of a synchronization signal sensed by an IMD electrode and/or EP electrodes. The method also includes computing reconstructed electrical signals for locations on a surface of interest within the patient's body based on the synchronized electrical data and geometry data. The geometry data represents locations of the EP electrodes, a location of the IMD electrode within the patient's body and the surface of interest.

An example method for calibrating a glucose sensor includes determining, by one or more processors, a set of electrical parameters for the glucose sensor of a plurality of glucose sensors and determining, by the one or more processors, a cluster for the glucose sensor based on the set of electrical parameters. Each cluster of the plurality of clusters identifies respective configuration information. In this example, the method includes configuring, by the one or more processors, the glucose sensor to determine a glucose level of a patient based on configuration information identified by the determined cluster.

The invention comprises a method for estimating state of a cardiovascular system, comprising the steps of: providing a cardiac analyzer, comprising: a blood pressure sensor, the blood pressure sensor generating a time-varying pressure state waveform output from a portion of a person; a system processor connected to the blood pressure sensor; and a dynamic state-space model of a cardiovascular system, the system processor receiving cardiovascular input data, from the blood pressure sensor, related to a transient pressure state of the cardiovascular system, where at least one probabilistic model, of the dynamic state-space model, operating on the time-varying pressure state waveform output generates a probability distribution function to a non-pressure state of the cardiovascular system. The probability distribution function is iteratively updated using synchronized updated time-varying pressure state waveform output from the blood pressure sensor and a non-pressure state output related to a cardiovascular system parameter is generated.

The present disclosure includes a handheld processing device including medical applications for minimally and noninvasive glucose measurements. In an embodiment, the device creates a patient specific calibration using a measurement protocol of minimally invasive measurements and noninvasive measurements, eventually creating a patient specific noninvasive glucometer. Additionally, embodiments of the present disclosure provide for the processing device to execute medical applications and non-medical applications.

Disclosed are devices, systems and methods for in vivo monitoring of localized environment conditions within a patient user by measuring analytes, including glucose, oxygen, and/or other analytes. In some aspects, a sensor device includes a wafer-based substrate, at least one electrochemical sensor two-electrode contingent including a working electrode and a reference electrode on the substrate and configured to detect a target analyte in a body fluid when the sensor device is deployed within a subject's body, where the working electrode is functionalized by a chemical layer configured to facilitate a reaction involving the target analyte that produces an electrical signal; and an electronics unit in communication with the electrochemical sensor electrode contingent to transmit the electrical signal to an external processor.

Method for detecting biomechanical and functional parameters of the knee in a situation of performance stress, which comprises: a step for the set up of video recording means (1); a step for the set up of multiple optical markers (4) at specific landmark anatomic points (PA) of the foot and of the knee of a person; a step for the set up, at the plantar surface of the foot, of baropodometric means (5); a step for the acquisition, by means of the video recording means (1), of images of at least one reference action, and a step for the detection, by means of the baropodometric means (5), of baropodometric parameters; a step for calculating, from the baropodometric parameters, the coordinates of the center of pressure (COP) of the foot and of the constraining reaction force (FV) acting on the foot; a step for calculating a force arm (BF) given by the distance between the center of pressure (COP) and a reference point (PR) of the knee; a step for calculating a biomechanical parameter indicative of the valgus moment, derived from the vector product (PV) of the force arm (BF) and the constraining reaction force (FV).