Ultrasensitive, ultrathin thermodynamic sensing platforms for the detection of chemical compounds at trace levels are disclosed. Embodiments of the ultrathin sensor comprise substrate, adhesion, microheater, and catalyst layers. A sensor array may include a plurality of sensors each having a different catalyst. When a sensor array exposed to an analyte, each of the various sensors of the array may experience an endothermic reaction, an exothermic reaction, or no reaction. A comparison of the reaction results to data comprising previously-obtained reaction results may be used to determine information on the analyte. Advantageously, these ultrathin vapor sensors utilize less power and provide greater sensitivity, and may be used to detect and identify analytes at the PPT level. Specialized sensors configured to detect analytes falling into a certain category (e.g., explosives, drugs and narcotics, biomarkers, etc.) are disclosed, as well as general purpose sensors capable of detecting analytes from a plurality of categories.

Disclosed are an array type skin-conformal sensor for heart rate and body temperature measurement, the array type skin-conformal sensor including a base sheet configured to be attached to the skin in tight contact therewith, the base sheet being made of a skin-conformal material, a measurement portion formed at one surface of the base sheet, the measurement portion being deformed by deformation of the skin, whereby resistance of the measurement portion is changed, and an electrode pattern formed at one surface of the base sheet, one end of the electrode pattern being connected to the measurement portion to transmit a change in resistance of the measurement portion, and a heart rate and body temperature measurement apparatus using the same. Since the skin-conformal sensor is attached to the skin in tight contact therewith, it is possible to measure the heart rate even though a blood vessel is deeply located.

The present invention relates to device, system and method for detecting a cardiac and/or respiratory disease of a subject. The proposed device comprises a sound input (20) for obtaining a sound signal representing sounds generated by the subject's body; a motion input (21) for obtaining a motion signal representing motions generated by the subject's body; and a processor (22) for processing the obtained sound signal and motion signal. This processing includes identifying inhalation and/or exhalation periods of the subject based on the motion signal, detecting abnormal lung sounds during inhalation and/or exhalation periods based on the sound signal, determining abnormal lung sound characteristics of the detected abnormal lung sounds, determining breathing characteristics of the subject's breathing based on the sound signal, determining the phase of the abnormal lung sounds in the inhalation-exhalation cycle, and detecting a cardiac and/or respiratory disease of the subject based on the determined abnormal lung sound characteristics, the determined breathing characteristics and the determined phase of the abnormal lung sounds in the inhalation-exhalation cycle.

The present invention provides a closed loop control method in an artificial pancreas and a system using the method, comprising sensing an activity level of a patient by at least one motion sensor and providing signals to at least one processer; then adjusting a series of related algorithms depending partly on the signals by the processer to provide more accurate and reliable data that is the basis of desirable treatment plans, and sending corresponding instructions by the processer for automatic operations of the artificial pancreas to realize a closed loop control.

Described herein are methods for identifying a labor state in a pregnant female, including: receiving an input indicating a gestational age; acquiring a physiological signal; processing the physiological signal to extract a parameter of interest; and feeding the parameter of interest into a machine learning model. The machine learning model is configured to: determine a first labor probability based on the parameter of interest, determine a second labor probability based on the parameter of interest or a second parameter of interest and the gestational age, and classify the labor state of the pregnant female based on the first and second labor probability.

A medical system is disclosed. The medical system has a housing and a module received in the housing. The module includes an analyte sensor configured for detecting an analyte in a body fluid of a user, an electronics unit electrically connected to the analyte sensor, an insertion component configured for inserting the analyte sensor into body tissue of the user, and a sterility cap at least partially surrounding the insertion component. A removable protective cap is connected to the housing and covers the module. The protective cap at least partially surrounds the sterility cap. The sterility cap has a sterility testing access that has at least one of a septum and a multiple-step sealing. A method of sterility testing the medical system is also disclosed in which a rinsing liquid is inserted into an interior space of the sterility cap and microbial testing of the rinsing liquid is then completed.

Systems and methods for monitoring the status of a joint or limb using color sensing. First and second color sensors are provided to sense first and second color encoded surfaces at first and second locations of a joint or limb, respectively. The color sensing data are processed to obtain the respective motion information of the first and second locations.

A method can include receiving, using one or more processors, a first record including a first data associated with a personal identification from a first database, receiving, using the one or more processors, a second record including a second data associated with a user identification from a second database, pairing, using the one or more processors, the first data and the second data based upon a shared data item contained in the first record and the second record, and displaying, using one or more processors, a report based upon the first data and the second data.

In an example, a method includes collecting biodata of a subject. The method includes generating or updating a personalized ML model of the subject from the biodata of the subject. The method includes detecting anomalies in the biodata based on the personalized ML model. The method includes filtering the detected anomalies to determine whether the detected anomalies indicate that the subject has a clinical condition or is at risk of having the clinical condition.

A system comprising a plurality of electrodes adapted to measure bio impedance measurements using electrical currents passing in a target thorax area of a target therebetween during a learning phase, at least one radiofrequency (RF) sensor adapted to measure RF interaction measurements of RF radiation interacting with the target thorax area during the learning phase, and at least one processor adapted to: calculate calibration function according to the bio impedance measurements and the RF interaction measurements, and determine a target thorax area value by adjusting subsequent bio impedance measurements using subsequent electrical currents passing in the target thorax area during an operational learning phase using the calibration function.