A network-based rehabilitation system for treating ailments of a user utilizing an enhanced reality environment is provided. The system has an enhanced reality device wearable by the user, the device being in communication with a network and configured to enable a user to interact with the enhanced reality environment to execute a rehabilitation routine; at least one sensor configured to capture biometrics of the user, a condition of the user, or both, wherein the at least one sensor is in communication with the enhanced reality device and the network; a progress analysis module configured to analyze a rehabilitation routine performance of the user, and a routine modification module configured to adjust the rehabilitation routine based on the performance of the user, wherein the routine modification module executes a machine learning algorithm and recommends a routine adjustment based on the machine.

A network-based rehabilitation system for treating ailments of a user utilizing an enhanced reality environment is provided. The system has an enhanced reality device wearable by the user, the device being in communication with a network and configured to enable a user to interact with the enhanced reality environment to execute a rehabilitation routine; at least one sensor configured to capture biometrics of the user, a condition of the user, or both, wherein the at least one sensor is in communication with the enhanced reality device and the network; a progress analysis module configured to analyze a rehabilitation routine performance of the user, and a routine modification module configured to adjust the rehabilitation routine based on the performance of the user, wherein the routine modification module executes a machine learning algorithm and recommends a routine adjustment based on the machine.

Provided are systems, methods, and devices for intracranial measurement, stimulation, and generation of brain state models. Systems include a plurality of intracranial electrodes configured to be coupled to a brain of a user. Systems further include an interface configured to obtain measurements from the plurality of intracranial electrodes. Systems include a first processing device including one or more processors configured to generate a plurality of brain state parameters characterizing one or more features of at least one brain state of the user, and a second processing device including one or more processors configured to generate at least one model of the brain of the user based, at least in part, on the plurality of brain state parameters and the measurements. Systems include a controller including one or more processors configured to generate a control signal based on the plurality of brain state parameters and the at least one model.

Provided are systems, methods, and devices for intracranial measurement, stimulation, and generation of brain state models. Systems include a plurality of intracranial electrodes configured to be coupled to a brain of a user. Systems further include an interface configured to obtain measurements from the plurality of intracranial electrodes. Systems include a first processing device including one or more processors configured to generate a plurality of brain state parameters characterizing one or more features of at least one brain state of the user, and a second processing device including one or more processors configured to generate at least one model of the brain of the user based, at least in part, on the plurality of brain state parameters and the measurements. Systems include a controller including one or more processors configured to generate a control signal based on the plurality of brain state parameters and the at least one model.

Controllers induce a hypoglycemic condition within a predetermined blood glucose range abnormal cells including senescent and cancerous cells are targeted for apoptosis. One or more controllers are in signal communication with sensors and measure physiological vital signs. Controllers are in signal communication with one or more fluid flow control devices to control delivery of at least insulin and glucose and at least one cocktail containing at least one of a senolytic and chemotherapeutic. The fluid control devices are in signal communication with at least one microprocessor having memory and the one or more physiological sensors, one or more databases or lookup tables and, wherein the controller controls the fluid control devices for at least insulin glucose, and the cocktail to keep blood glucose level (BGL) within a target hypoglycemic range.

A wearable computing device with bio-signal sensors and a feedback module provides an interactive mediated reality (“VR”) environment for a user. The bio-signal sensors receive bio-signal data (for example, brainwaves) from the user and include bio-signal sensors embedded in a display isolator, having a deformable surface, and having an electrode extendable to contact the user's skin. The wearable computing device further includes a processor to: present content in the VR environment via the feedback module; receive bio-signal data of the user from the bio-signal sensor; process the bio-signal data to determine user states of the user, including brain states, using a user profile; modify a parameter of the content in the VR environment in response to the user states of the user. The user receives feedback indicating the modification of the content via the feedback module.

A wearable computing device with bio-signal sensors and a feedback module provides an interactive mediated reality (“VR”) environment for a user. The bio-signal sensors receive bio-signal data (for example, brainwaves) from the user and include bio-signal sensors embedded in a display isolator, having a deformable surface, and having an electrode extendable to contact the user's skin. The wearable computing device further includes a processor to: present content in the VR environment via the feedback module; receive bio-signal data of the user from the bio-signal sensor; process the bio-signal data to determine user states of the user, including brain states, using a user profile; modify a parameter of the content in the VR environment in response to the user states of the user. The user receives feedback indicating the modification of the content via the feedback module.

Systems and methods described herein use pairing to associate a wireless sensor with a patient monitoring device such as a bedside patient monitor or a mobile device. A signal emitted by a patient monitoring device can be detected by a wireless sensor. The wireless sensor can be associated with the detected signal and pair the wireless sensor with the patient monitoring device. The wireless sensor can be configured to enter into a patient parameter sensing mode of operation after the association of the wireless sensor with the patient monitoring device.

Systems and methods described herein use pairing to associate a wireless sensor with a patient monitoring device such as a bedside patient monitor or a mobile device. A signal emitted by a patient monitoring device can be detected by a wireless sensor. The wireless sensor can be associated with the detected signal and pair the wireless sensor with the patient monitoring device. The wireless sensor can be configured to enter into a patient parameter sensing mode of operation after the association of the wireless sensor with the patient monitoring device.

A system includes a communication interface for receiving information that includes data collected from an array of neural activity sensors that were placed on a patient during a session of applied stimuli. A processor is configured to analyze the received information to obtain a frequency spectrum for each sensor for a given stimulus of the applied stimuli. Neural network frequencies that correspond to an indicated impaired functionality of the nervous system of the patient are selected. For each selected frequencies, a spatial map of neural activity is generated. Each of the generated spatial maps is compared with retrieved corresponding spatial maps to identify treatment frequencies from among the selected neural network frequencies. A treatment protocol is generated for input into an electromagnetic field generator to cause the generator to apply to the patient an electromagnetic field at each identified treatment frequency.