A healthcare device and a vehicle system are capable of charging a sensor device that measures a biosignal. The healthcare device includes the sensor device that includes a biosignal measuring sensor that measures the biosignal and uses the biosignal measuring sensor as a charging electrode during charging, a healthcare controller that collects and calculates the biosignal measured through the biosignal measuring sensor, a sensor device battery that receives power from an external pogo pin through an electrode of the biosignal measuring sensor during charging by the charging electrode to charge a power supply of the sensor device battery, and a selecting device that connects the biosignal measuring sensor to any one of the healthcare controller and the sensor device battery.

An external adjustment device for non-invasively adjusting an adjustable implant, the external adjustment device including a controller in communication with an actuator associated with the implant and a sensor configured to receive information from or about the implant. The external adjustment device may include a power source and a display. The external adjustment device may include a magnetic element configured to generate a rotating magnetic field; and a driver configured to drive the magnetic element to generate the rotating magnetic field and configured to rotate a permanent magnet of an implant. Upon placing the external adjustment device in proximity to the implant, the magnetic element is configured to magnetically couple with the permanent magnet. The external adjustment device may be configured to non-invasively determine one or more of a magnetic coupling state and a stalled state of the magnetic element and the permanent magnet disposed within the implant.

A control circuit for a sensor provided in a long member which can be inserted into a lumen to measure the flow velocity of a fluid in the lumen and a measurement device. The control circuit includes a drive circuit supplying a drive current to the sensor. A leakage current detection circuit detects a leakage current and performs an output corresponding to the detected leakage current. The leakage current detection circuit outputs a detection signal in response to detection of a leakage current exceeding a threshold value. A stop circuit stopping supply of the drive current to the sensor by the detection signal is further provided.

The present disclosure presents glucose sensing methods and systems. One such system comprises an electrospun-nanofibrous-membrane (ENFM)-based amperometric glucose sensor integrated on a silicon chip, in which the glucose sensor has a working electrode, a reference electrode, and a counter electrode, wherein the working electrode comprises an ENFM-based sensing electrode. The system further comprises a potentiostat circuit integrated on the silicon chip such that the potentiostat circuit comprises a voltage control unit to control a voltage difference between the working electrode and the reference electrode and a transimpedance amplifier to measure a current flow between the working electrode and the counter electrode, in which a strength of the current flow corresponds to an amount of glucose present in a sample of blood on the glucose sensor.

This disclosure relates to systems and methods for monitoring and classifying released gases in an enclosed system having a gas source, by a gas sensor that has been a priori pre-trained to distinguish an off-gas event (OGE) or a thermal run off event (TRE) from non-OGE interfering gases release. The pre-training utilizes one of a machine learning (ML) or a deep learning (DL) algorithm to pre-train the gas sensor to detect a plurality of known gas analyte to generate sensor signals with respective unique characteristics, extracting features from the sensor signals to establish a decision boundary or an estimated probability of a false positive release of the OGE or the TRE from the non-OGE type of interfering gas release. The established decision boundaries or probability distributions are implemented as candidate model for field deployment to classify the released gases to distinguish whether OGE or TRE takes place.

A healthcare device and a vehicle system are capable of charging a sensor device that measures a biosignal. The healthcare device includes the sensor device that includes a biosignal measuring sensor that measures the biosignal and uses the biosignal measuring sensor as a charging electrode during charging, a healthcare controller that collects and calculates the biosignal measured through the biosignal measuring sensor, a sensor device battery that receives power from an external pogo pin through an electrode of the biosignal measuring sensor during charging by the charging electrode to charge a power supply of the sensor device battery, and a selecting device that connects the biosignal measuring sensor to any one of the healthcare controller and the sensor device battery.

An exercise suit with integrated weights includes a shirt portion and a pants portion that are constructed from a lightweight elastomeric material. A plurality of soft weights are disposed along the shirt and pants portions at locations adjacent to the major muscle groups of the suit wearer. Each of the weights can be permanently secured along the inside facing surface of the shirt and pants, and conform to the shape and movement of the suit wearer. The suit also includes a fitness monitor having a heartbeat sensor, timer and display.

Embodiments provide apparatus, systems, and methods for communicating analyte data and/or related information. In a first aspect, the apparatus includes a transmitter/receiver unit which is configurable as either a transmitter or a receiver. The transmitter/receiver unit may be coupled to an on-body sensor and may be configured as a transmitter, or may be coupled to a management unit and may be configured as a receiver as part of a continuous analyte monitoring system. Analyte data communication systems and methods are provided, as are other aspects.

Embodiments of the present application provide a headphone with a biological feature detection function, an interaction system and a biological feature detection method. The headphone includes: a loudspeaker, a microphone, a biological feature detection module, a mode switching module, a first communication module, a control module and a power management module. The control module is configured to detect and determine whether an instruction is received from the smart terminal, and control, according to the instruction received from the smart terminal, the biological feature detection module, the mode switching module, the power management module and the first communication module to work, and further configured to parse the biological feature from the biological feature detection module under control of the instruction received from the smart terminal, and transmit the parsed biological feature to the smart terminal via the first communication module.

A physiological parameter tracking system has a reference parameter calculator configured to provide a reference parameter responsive to a physiological signal input. A physiological measurement output is a physiological parameter derived from the physiological signal input during a favorable condition and an estimate of the physiological parameter according to the reference parameter during an unfavorable condition.