A CPR apparatus includes a chest compression unit and a means for mounting the chest compression unit on a patient. The chest compression unit includes a plunger disposed in a housing. At its one end extending from the housing the plunger has a compression member. The plunger is driven in a reciprocating manner by a reversible electromotor via a mechanism for translating rotational motion to linear motion or by a linear induction electromotor. The chest compression unit includes an electromotor control unit including a microprocessor, a first monitor for monitoring the position of the plunger in respect of the housing and a second monitor for monitoring the position of the plunger in respect of the mechanism for translating rotational motion to linear motion or the rotor of the linear induction electromotor. The monitored positions are communicated to the electromotor control unit. Also disclosed is a corresponding CPR method.

Automated CPR systems incorporating biological feedback can include an automated compression piston system, a data acquisition system, computer systems for running various control algorithms, ventilation control systems, and/or drug delivery systems. Automated CPR systems can be used as stand-alone systems for treating patients in cardiac arrest, or they can be used to administer pretreatment to a patient prior to defibrillation.

Embodiments of the present invention include a system having at least one sensor configured to monitor a muscle oxygen saturation (SmO2) level of a patient who is undergoing cardiac arrest and to generate a signal representing SmO2 level; a user interface device; a processor communicably coupled to the user interface device, the processor configured to cause the user interface device to present an array of two or more possible nodes of a clinical decision support tree, wherein at least one of the nodes indicates cardiopulmonary resuscitation (CPR) treatment of the patient with no ventilation, and wherein at least another of the nodes indicates CPR treatment of the patient with active ventilation; determine which of the two or more possible nodes should be emphasized based on the SmO2 level; and update the array of the two or more possible nodes based on the determination.

Apparatus and methods relate to a pneumatic compression therapy device configured to suggest content to the patient based on a determined disease state, the content pertaining to suggested changes in lifestyle based on a standard of care. In an illustrative embodiment, the suggested changes may include modifications to treatment location, treatment time, diet, eating habits, or sleeping schedule. Various examples may further sample the patient's health and automatically adjust a treatment parameter within a predetermined parameter range based on a history of measured parameters, such as limb volume, for example. In coordination with the therapeutic treatment, the therapy device may deliver suggested content to guide the patient to make more healthful lifestyle choices to reduce recovery time and improve patient health outcomes.

The invention relates to a method and apparatus for diagnosis, performance and/or regulation of physiological functions, in particular in an anaesthetized patient. The apparatus has a pressure device (10) for at least one body region or extremity (55) of a patient (50), wherein pressure-increasing means (21) and pressure-reducing means (22) are assigned to the pressure device (10), and a control device (30) is provided with which the pressure in the pressure device (10) can be controlled via the pressure-increasing means (21) and the pressure-reducing means (22).

Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, treatment plans for optimizing a user outcome. The method comprises receiving attribute data associated with a user. The attribute data comprises one or more symptoms associated with the user. The method also comprises, while the user uses a treatment apparatus to perform a first treatment plan for the user, receiving measurement data associated with the user. The method further comprises generating, by the artificial intelligence engine configured to use one or more machine learning models, a second treatment plan for the user. The generating is based on at least the attribute data associated with the user and the measurement data associated with the user. The second treatment plan comprises a description of one or more predicted disease states of the user. The method also comprises transmitting, to a computing device, the second treatment plan for the user.

A mobile walker has a frame, at least two wheels which are embodied and arranged on the frame to move the mobile walker around on a ground surface, at least one hand grip embodied and arranged on the frame to be used by a user of the mobile walker as a support and pushing aid, at least one measured value recording unit embodied and programmed to record at least one vital parameter of the user, and a processor unit which is connected communicatively to the measured value recording unit and which is embodied and programmed to assess the recorded vital parameter and/or transmit the same to a control center arranged separately from the mobile walker.

A computer-implemented method for facilitating cardiac rehabilitation among eligible users is disclosed. The method includes the steps of (1) receiving health information associated with one or more users; (2) for each user of the one or more users: determining, based on health information associated with the user, a respective eligibility of the user for cardiac rehabilitation; (3) determining, based on the respective eligibilities, that at least one user of the one or more users is eligible for cardiac rehabilitation; (4) generating a treatment plan for the at least one user, where the treatment plan pertains to a cardiac rehabilitation that is specific to the at least one user; and (5) assigning the treatment plan to at least one electromechanical machine to enable the user to perform the cardiac rehabilitation.

Systems and methods related to the field of cardiac resuscitation, and in particular to devices for assisting rescuers in performing cardio-pulmonary resuscitation (CPR), are described herein. In one aspect, a method for managing cardiopulmonary resuscitation (CPR) treatment to a person in need of emergency assistance includes monitoring a parameter that indicates a fatigue level of a rescuer and providing an indication that a different person should perform the CPR component if the rescuer is exhibiting fatigue.

A computer-implemented method is disclosed. The method includes determining whether one or more messages have been received from at least one of an electromechanical machine, a sensor, and an interface. Then the one or more messages may pertain to at least one of a user and a usage of the electromechanical machine by the user. The electromechanical machine may be configured to be manipulated by the user while the user is performing a treatment plan. The method also includes, responsive to determining that the one or more messages have not been received, determining, using one or more machine learning models, one or more preventative actions to perform. The method also includes causing the one or more preventative actions to be performed.