An example of a system for monitoring and treating respiratory distress in a patient may include signal inputs, a signal processing circuit, and a respiratory distress analyzer. The signal inputs may be configured to receive patient condition signals indicative of autonomic balance of the patient. The signal processing circuit may be configured to process the patient condition signals and to generate patient condition parameters indicative of the autonomic balance using the processed patient condition signals. The respiratory distress analyzer may be configured to determine a state of the respiratory distress using the patient condition parameters, and may include a parameter analysis circuit configured to analyze the autonomic balance of the patient and to determine the state of the respiratory distress using an outcome of the analysis.

A physiological monitoring device includes: a sensor interface, a display configured to display information related to the patient, and at least one processor. The at least one processor is configured to: operate the physiological monitoring device into a non-transport mode while docked to one of at least one monitor mount; display first location context information corresponding to a first patient care area on the display while the physiological monitoring device is operating in the non-transport mode in the first patient care area; detect an undocking event in response to undocking the physiological monitoring device from a first monitor mount of the at least one monitor mount, wherein the first monitor mount is located in the first patient care area; and in response to detecting the undocking event, operate the physiological monitoring device in a transport mode, including changing the first location context information to transport context information on the display.

In various examples, a cognitive load of a user may be inferred. Motion sensor data indicative of head movement of the user may be generated with a motion sensor disposed adjacent a head of the user. The motion sensor data may be analyzed to infer a feature of a gait of the user. The user's cognitive load may be inferred based on the feature of the gait.

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.

A physiological signal monitoring system includes a single set of sensing electrodes to provide conditioned physiological signals to a primary monitoring device and a secondary monitoring device. The monitoring system includes pre-processing circuitry configured to receive a raw physiological signal. The pre-processing circuitry is configured to produce a primary physiological signal and a secondary physiological signal. Each of the primary and secondary physiological signals are conditioned. The primary conditioned physiological signal is directed to a primary monitoring device such as a hospital wearable defibrillator device. The secondary conditioned physiological signal is directed to telemetry modeling circuitry where it is further processed to output one or more telemetry signals. The one or more telemetry signals are output to a secondary monitoring device such as a three lead ECG monitoring device. Thus, a single set of sensing electrodes can provide physiological signals to multiple monitoring devices.

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.

Devices, systems, and methods can be used to suggest a discovery to an individual related to their health and wellness, including receiving data about the individual from a user interface regarding a goal for the individual, querying the individual regarding their perception of the goal, determining, a likely state of the individual (e.g., readiness to change), and selecting a subset of discoveries to display to the individual from a database that correspond to both the goal for the individual and the likely state of the individual. Displaying information may include receiving motion data including duration of motion, classifying a type of activity the individual is engaged in based on the motion data and likely intensity of the activity, and displaying a graphical user interface including a color spectrum, depending on one of the type of activity, intensity of the activity, or duration of the activity.

The differential voltage measuring system has a number of signal measuring circuits, each having a capacitive sensor element for capturing a measurement signal relating to the patient. The differential voltage measuring system further has a signal processing apparatus for determining at least one bioelectrical signal from the measurement signals and a computer unit which is configured to ascertain, on the basis of the at least one bioelectrical signal, and to provide, an item of breathing information, said breathing information indicating a breathing activity of the patient.

A system for monitoring a sleep of a user includes a plurality of patches for placement adjacent to a surface of a body of a user, a processor, and a data communication system. Each patch from the plurality of patches includes at least one sensor. The data communication system transmits positional data generated by the plurality of sensors, including orientation data and motion data, to the processor. The processing of the positional data includes detecting a change in position of the body of the user between a first position and a second position. Based on the first image and the second image, an animation of a movement of the body from the first position to the second position is generated.

A system for electronic patient care includes a hub. The hub is configured to monitor a patient-care device. The sandbox may be configured to control access to at least one of a hardware resource and a software resource. The hub is further configured to identify the patient-care device and execute an application to monitor the patient-care device. The hub executes the application within the sandbox component such that the application accesses the at least one of the hardware resource and the software resource through the sandbox component. The hub may be further configured to control the patient-care device. The hub may be further configured to receive an identification from the patient-care device and download the application from a server associated with the identification. The hub may be further configured to receive an identification from the patient-care device and update the application from a server associated with the identification.