A robotic surgery system is disclosed that can include an instrument including an operational tool coupled to a positioner and an input device configured to generate input signals in response to manipulation by an operator representing a desired spatial positioning of the tool within a tool workspace including extents corresponding to physical movement limitations for the positioner. A processor can be configured to receive the input signals and process the signals to determine the desired spatial positioning. The processor can be configured to initiate a movement management function in response to a determination that the desired spatial positioning would result in a movement of the positioner associated with a potential service life reduction for the instrument. The processor can be configured to generate drive signals for movement of the positioner in response to a determination that the desired spatial positioning is not associated with a potential reduction in service life.

Systems and methods for processing sensor data and end of life detection are provided. In some embodiments, a method for determining the end of life of a continuous analyte sensor includes evaluating a plurality of risk factors using an end of life function to determine an end of life status of the sensor and providing an output related to the end of life status of the sensor. The plurality of risk factors may be selected from the list including the number of days the sensor has been in use, whether there has been a decrease in signal sensitivity, whether there is a predetermined noise pattern, whether there is a predetermined oxygen concentration pattern, and error between reference BG values and EGV sensor values.

A medical sensor includes an application-specific integrated circuit (ASIC), medical hardware, and a communication module. The ASIC is communicatively coupled to the medical hardware and communication module. The ASIC is configured to receive measurement signals from the medical hardware and provide the measurement signals to the communication module. The communication module is configured to process the measurement signal into measurement results and transmit the measurement results to a remove device. The communication module includes an application layer for processing the measurement signals and a link layer for transmitting the measurement results. The ASIC is configured to detect that a voltage supplied to the ASIC is below a threshold level and determine an amount of time that the voltage has been below the threshold level. The ASIC is further configured to respond to the voltage supplied to the ASIC being below a threshold level based on the determined amount of time.

An electronic detection device with electrochromic indicator is disclosed herein. In one embodiment, the detection device includes a sensor configured to sense a predetermined wavelength, an electrochromic display configured to indicate an intensity of the predetermined wavelength exposure received by the sensor; a capacitor configured for charging by the predetermined wavelength, wherein the capacitor is configured to at least in part power the device; and an antenna configured for communicative coupling with a smart device.

A physiological test credit method determines if test credits are available to the monitor and checks if a Wi-Fi connection is available. If test credits are less than a test credit threshold, the monitor connects to a test credit server, processes server commands so as to download test credits and disconnects from the server. In various embodiments, the monitor is challenged to break a server code, the server is challenged to break a monitor code. The server validates monitor serial codes, and saves monitor configuration parameters.

Methods, systems, and devices for improving continuous glucose monitoring (“CGM”) are described herein. More particularly, the methods, systems, and devices describe retrieving a machine learning model that is trained to classify CGM sensor data and blanking the CGM sensor data based on an outlier classification from the machine learning model. The system may terminate sensors for which there is an aggregation of blanked CGM sensor data. The methods, systems, and devices described herein may additionally comprise a machine learning model that is trained to detect and correct for erroneous sensor use conditions based on error patterns in sensor data. The system may determine resolutions for correcting the detected erroneous sensor use conditions.

The invention relates to a sensor system for measuring and/or processing measured pressure and/or humidity values, comprising at least one sensor for measuring pressure and/or humidity and at least one processing unit, which is set up and intended to control the sensor and/or to store and/or process data measured by the sensor. Furthermore, the sensor system comprises at least one evaluation unit, which evaluates the data forwarded to it by the processing unit and subsequently forwards these data or a data record generated from the data to a CPU, in particular wirelessly, wherein these data comprise a user behavior, movement sequences, body functions, body behavior, weight, pressure or moisture of a skin of the user, and are collected and subsequently evaluated by the CPU.

Disclosed herein are single-use integral indicators and methods and systems for employing the same. Such indicators and their uses are directed toward identifying and rendering inoperable single-procedure medical devices after their intended—and only—use.

Systems and methods for processing sensor data and end of life detection are provided. In some embodiments, a method for determining the end of life of a continuous analyte sensor includes evaluating a plurality of risk factors using an end of life function to determine an end of life status of the sensor and providing an output related to the end of life status of the sensor. The plurality of risk factors may be selected from the list including the number of days the sensor has been in use, whether there has been a decrease in signal sensitivity, whether there is a predetermined noise pattern, whether there is a predetermined oxygen concentration pattern, and error between reference BG values and EGV sensor values.

Aspects of the present disclosure include a sensor configured to store in memory indications of sensor use information and formulas or indications of formulas for determining the useful life of a sensor from the indications of sensor use information. A monitor connected to the sensor monitors sensor use and stores indications of the use on sensor memory. The monitor and/or sensor compute the useful life of the sensor from the indications of use and the formulas. When the useful life of the sensor is reached, an indication is given to replace the sensor.