An apparatus may be configured for documenting a code blue scenario when adhered to the chest of a subject undergoing resuscitation by sensing and transmitting information associated with the code blue scenario. Such information may include one or more of vital signs of the subject during resuscitation, information associated with chest movements of the subject during resuscitation, and audio information from an environment of the subject during resuscitation. A computing platform that is separate and distinct from the apparatus may provide code blue documentation conveying information related to the vital signs of the subject and derived from the audio information from the environment of the subject during resuscitation.

The present disclosure pertains to a system configured to determine one or more parameters of chest wall oscillation therapy for a subject. The system includes a wearable garment configured to provide percussion to one or more parts of a lung of a subject. The wearable garment includes: percussion excitation elements configured to produce the percussion; and sensors configured to generate output signals conveying information related to a response of the one or more parts of the lung to the percussion. The system includes a control unit configured to determine frequency and energy density information for the sounds made by the one or more parts of the lungs caused by the percussion, the frequency and energy density information determined based on the output signals; and determine the one or more parameters of the chest wall oscillation therapy based on the frequency and energy density information.

One aspect of the present invention is different embodiments of legs and feet massage apparatuses for providing massage effects to the legs and/or feet of a user. Another aspect is different embodiments of hands and arms massage apparatuses for providing massage effects to the arms and/or hands of the user. Additional aspect is an armrest sliding adjustment apparatus. A further aspect is a bicep and tricep panel sliding adjustment apparatus. Additional aspect is a chair that includes at least one of the following devices, apparatuses and systems described in this application: any of the legs and feet massage apparatuses; any of the hands and arms massage apparatuses; an armrest sliding adjustment apparatus; a bicep and tricep panel sliding adjustment apparatus; a neck and shoulder massage system; an integrated smart medical device; at least one health monitoring device or system; a virtual reality device; and a touchscreen-based control system.

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 respiration-assistance apparatus or method can include or use a lifting element such as to cyclically push, pull, or lift, toward a superior direction of the subject, at least one subject region during an inhalation portion of a respiration cycle of the subject. A cyclical member can couple the lifting element to a fixed reference. Abdominal or ribcage compression can be provided. A multi-action or other cam can be used, such as together with a reciprocating element. Examples can be configured for use with a wheelchair, a bed, a vacuum or suction affixation element, a wearable garment, etc.

A percussive therapy system includes a percussive therapy device that includes a housing, an electrical source, a motor positioned in the housing, a switch for activating the motor, a push rod assembly operatively connected to the motor and configured to reciprocate in response to activation of the motor, and an attachment configured to be operatively connected to a distal end of the push rod assembly of the percussive massage device and to provide at least one therapeutic effect to a user. The attachment may include at least one of an actuator configured to provide the at least one therapeutic effect to the user and a sensor configured to obtain at least one of biometric data of the user and information regarding operation of the percussive therapy device.

A computer-implemented system may include a stair-climbing machine configured to be manipulated by a user while the user performs a treatment plan, an interface comprising a display configured to present information associated with the treatment plan, and processing structure configured to receive, from one or more data sources, information associated with the user, wherein the information comprises one or more risk factors associated with a cardiac-related event; generate, using one or more trained machine learning models, the treatment plan for the user, wherein the treatment plan is generated based on the information associated with the user, and the treatment plan comprises one or more exercises associated with managing the one or more risk factors in order to reduce a probability that a cardiac intervention will occur; and transmit the treatment plan to cause the stair-climbing machine to implement the one or more exercises.

Described herein are wearable sensory stimulation and monitoring devices that can be worn around the back of the neck along and in contact with the spine. The wearable device includes cuff, band and head cover members as form factors. Apparatuses described herein stimulate one or more senses including auditory, tactile or olfactory. Apparatuses are also described that allow for sensing and monitoring of physiologic parameters such as heart rate, blood pressure and movement. The device also has features that allow for easy attachment or integration to articles worn on the head such as augmented reality and virtual reality accessories to provide visual stimulation and entertainment.

A computer-implemented method is disclosed. The method includes receiving, at a computing device, a first treatment plan designed to treat an invasive surgical-related health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the invasive surgical-related health issue, enable the user to perform an exercise at different exertion levels. Next, while the user uses the electromechanical machine to perform the first treatment plan, receiving, at the computing device, data from sensors configured to measure the data associated with the invasive surgical-related health issue and transmitting the data. One or more machine learning models are used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the data, and the invasive surgical-related health issue. The method additionally includes receiving the second treatment plan.

Systems including an elliptical machine and a processing device. The processing device may be configured to receive, before or while a user operates the elliptical machine, one or more messages pertaining to the user or a use of the elliptical machine by the user. The processing device may be also configured to determine whether the one or more messages were received by the processing device. In response to determining that the one or more messages were not received by the processing device, the processing device may be configured to determine, via one or more machine learning models, one or more actions to perform. The one or more actions may include at least one of initiating a telecommunications transmission, stopping operation of the elliptical machine, and modifying one or more parameters associated with the operation of the elliptical machine.