There is provided an apparatus for use in measuring blood pressure. The apparatus comprises a processor configured to acquire a signal indicative of pressure oscillations detected inside a cuff inflated to pressurize a measurement site of a subject undergoing cardiopulmonary resuscitation. The pressure oscillations detected inside the cuff are indicative of a pulse of the subject. The processor is also configured to trigger a blood pressure measurement for the subject based on the pressure oscillations detected inside the cuff.

A system for providing a visual summary of a condition of a patient when traumatic brain injury (TBI) is suspected or diagnosed includes at least one patient condition sensor configured to sense data representative of a patient condition parameter of interest for a TBI patient; at least one airflow sensor configured to sense data representative of ventilations provided to the patient; at least one visual display for providing the visual summary to a user; and at least one controller. The at least one controller is configured to cause the visual display to provide the visual summary. The visual summary can include at least one visual representation of at least one patient condition parameter for each time interval of a plurality of time intervals, at least one visual representation of ventilation information, and a visual indication of when at least one patient condition parameter is outside of a target range.

In an embodiment, a method includes receiving, by a user device, a code start trigger, where the user device is dockable on a crash cart and in communication with a controller disposed in relation to the crash cart. The method also includes, responsive to the code start trigger, initiating a code workflow, creating an event log for the code workflow, and determining a patient rhythm. The method also includes monitoring for real-time code events. The monitored real-time code events include patient intervention and a new patient rhythm. The method also includes, responsive to a determination that a real-time code event has occurred, executing programmed action that includes updating the event log.

The present disclosure describes a closed-loop fluid resuscitation and/or cardiovascular drug administration system that uses continuous measurements and adaptive control architecture. The adaptive control architecture uses a function approximator to identify unknown dynamics and physiological parameters of a patient to compute appropriate infusion rates and to regulate the endpoint of resuscitation.

An EKG monitor and cable management system, including a housing, a plurality of retraction reels operably mounted in said housing; and a plurality of EKG leads, each including wires having electrodes disposed at a terminal end, each spooled on one of said reels. The leads deploy and retract in pairs, with the frontal leads retracting as a group of three pairs onto three separate retraction reels.

Technologies and implementations for a wearable healthcare system, which may be worn by a person. The wearable healthcare systems may include one or more motion sensors. A motion analysis modules may be included in the wearable healthcare system, which may be configured to determine physical activities and intensity of the physical activities of the person.

A medical monitoring and treatment device that includes a therapy delivery interface, a plurality of therapy electrodes coupled to the therapy delivery interface, a plurality of electrocardiogram sensing electrodes to sense electrocardiogram signals of a patient, a sensor interface to receive the electrocardiogram signals and digitize the electrocardiogram signals, and at least one processor coupled to the sensor interface and the therapy delivery interface to analyze the digitized electrocardiogram signals, to detect a cardiac arrhythmia based on the digitized electrocardiogram signals, and to control the therapy delivery interface to apply electrical therapy to the patient based upon the detected cardiac arrhythmia. The at least one processor is further configured to analyze a frequency domain transform of the digitized electrocardiogram signals, to determine a metric indicative of a metabolic state of a heart of the patient, and to accelerate or delay application of the electrical therapy based upon the metric.

A feedback device for an acute care provider includes: at least one motion sensor; a haptic output component for providing feedback having a varying haptic pattern to the acute care provider regarding performance of a resuscitation activity; and a controller. The controller can be configured to receive and process a signal representative of performance of the resuscitation activity from the at least one motion sensor, compare the acute care provider's performance of the resuscitation activity to a target performance of the resuscitation activity, and cause the haptic output component to provide haptic feedback to the acute care provider by changing the haptic pattern based, at least in part, on the signal from the at least one motion sensor and the comparison of the acute care provider's performance to the target performance of the resuscitation activity. The device can be adapted to be wrist-worn by the acute care provider.

A headset, configured to be attached to a human head, includes an accelerometer providing a signal indicative of head acceleration due to blood flow through the brain. An analyzer evaluates a plurality of samples indicative of acceleration over time where each sample corresponds to the head movement resulting from a cardiac contraction. The analyzer identifies brain conditions at least partially based on a level of chaos of the plurality samples. The algorithm applied by the analyzer is partially formulated based on clinical data and examination of a plurality of subjects. In one example, the plurality of samples evaluated by the analyzer are indicative of the head accelerometer only in a single axis. In some situations, the analyzer identifies brain conditions further based on contemporaneous neurological examination of the subject.

The abnormality determination apparatus includes a movement quantity detection unit and an abnormality level determination unit. The movement quantity detection unit detects movement quantities of a plurality of parts of the monitored person. Restraint information is information indicating a restraint status of the monitored person. The abnormality level determination unit determines an abnormality level of the monitored person on the basis of the movement quantities of the plurality of parts detected by the movement quantity detection unit and the restraint information.