A prosthetic device includes a flexible interface configured to conform to a residual limb of a user, a prosthetic socket including an outer shell more rigid than the flexible interface and positioned external to at least a portion of the flexible interface, and one or more vibrational devices placed in connection with the flexible interface to impart vibration to the residual limb.

A prosthetic device includes a flexible interface configured to conform to a residual limb of a user, a prosthetic socket including an outer shell more rigid than the flexible interface and positioned external to at least a portion of the flexible interface, and one or more vibrational devices placed in connection with the flexible interface to impart vibration to the residual limb.

Provided are a brain stimulation system, method, apparatus and storage medium based on artificial intelligence. The system includes: a plurality of brain stimulation terminals and a cloud platform. The cloud platform is configured to, with artificial intelligence algorithm especially machine learning and deep learning, generate multi-dimensional psychological big data using physiological data and psychological state evaluation parameters gotten from the plurality of brain stimulation terminals and established models of algorithm for disease diagnosis. The brain stimulation terminal is configured to analyze the physiological data and psychological state evaluation parameters of a target subject, measure a mental state of the target subject, obtain brain stimulation parameters required for the target subject according to the mental state, and generate corresponding non-invasive brain stimulation for the target subject according to the brain stimulation parameters based on the multi-dimensional big data through the artificial intelligence algorithm.

Provided are a brain stimulation system, method, apparatus and storage medium based on artificial intelligence. The system includes: a plurality of brain stimulation terminals and a cloud platform. The cloud platform is configured to, with artificial intelligence algorithm especially machine learning and deep learning, generate multi-dimensional psychological big data using physiological data and psychological state evaluation parameters gotten from the plurality of brain stimulation terminals and established models of algorithm for disease diagnosis. The brain stimulation terminal is configured to analyze the physiological data and psychological state evaluation parameters of a target subject, measure a mental state of the target subject, obtain brain stimulation parameters required for the target subject according to the mental state, and generate corresponding non-invasive brain stimulation for the target subject according to the brain stimulation parameters based on the multi-dimensional big data through the artificial intelligence algorithm.

A blood treatment machine includes a patient comfort feedback mechanism configured to be adjusted by a patient to indicate comfort levels of the patient. The machine is configured to adjust one or more treatment parameters based on the patient feedback.

Algorithms for detecting endotracheal intubation and/or misplacement of endotracheal tubes in child patients during anesthesia for use with anesthesia machines, mechanical ventilators, and/or respiratory function monitors. An algorithm uses end-tidal carbon dioxide (EtCO.sub.2), and tidal volume (TV) or peak inspiratory pressure (PIP) to detect exact intubation time. Another algorithm uses respiratory parameters to identify and/or confirm the type of airway device used during mechanical ventilation, and to detect if and when an issue has arisen with use of a specific airway device to provide real-time decision support to attending medical care professionals.

Algorithms for detecting endotracheal intubation and/or misplacement of endotracheal tubes in child patients during anesthesia for use with anesthesia machines, mechanical ventilators, and/or respiratory function monitors. An algorithm uses end-tidal carbon dioxide (EtCO.sub.2), and tidal volume (TV) or peak inspiratory pressure (PIP) to detect exact intubation time. Another algorithm uses respiratory parameters to identify and/or confirm the type of airway device used during mechanical ventilation, and to detect if and when an issue has arisen with use of a specific airway device to provide real-time decision support to attending medical care professionals.

Systems and methods for treating biologic fluids are disclosed. Some disclosed embodiments may be used to filter cerebrospinal fluid (CSF) from a human or animal subject, heat CSF to a target temperature, cool CSF to a target temperature, apply light treatment to CSF, separate cells via their dielectric properties, apply spiral and/or centrifugal separation, introduce additives to target particles, and/or apply combinations thereof. The method may include the steps of withdrawing fluid comprising CSF, treating the fluid, and returning a portion of the treated fluid to the subject. During operation of the system, various parameters may be modified, such as flow rate.

Supplying therapeutic gas based on inhalation duration. At least some of the example embodiments are methods including: sensing a current inhalation of the patient; providing a flow of therapeutic gas to the patient based on the sensing; and ceasing the flow of therapeutic gas to the patient based on a value indicative of previous inhalation duration.

Supplying therapeutic gas based on inhalation duration. At least some of the example embodiments are methods including: sensing a current inhalation of the patient; providing a flow of therapeutic gas to the patient based on the sensing; and ceasing the flow of therapeutic gas to the patient based on a value indicative of previous inhalation duration.