A system for closed-loop pulsed transcranial stimulation for cognitive enhancement. During operation, the system identifies a region of interest (ROI) in a subject's brain and then estimates ROI source activations based on the estimated source of the ROI. It is then determined if a subject is in a bad encoding state based on the ROI source activations. Finally, one or more electrodes are activated to apply a pulsed transcranial stimulation (tPS) therapy when the subject is in a bad encoding state, a predefined external event or behavior occurs, or the subject is in a consolidation state during sleep.

A training apparatus has an input device and a wearable computing device with a bio-signal sensor and a display to provide an interactive virtual reality (VR) environment for a user. The bio-signal sensor receives bio-signal data from the user. The user interacts with content that is presented in the VR environment. The user interactions and bio-signal data are scored with a user state score and a performance scored. Feedback is given to the user based on the scores in furtherance of training. The feedback may update the VR environment and may trigger additional VR events to continue training.

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.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for synchronizing neuroelectric measurements with diagnostic content presentation by performing actions that include causing a presentation system to present diagnostic content a user, where the diagnostic content includes: a first content frame prompting the user to perform a physical task, a second content frame including electroencephalogram (EEG) synchronization content, the second content frame sequentially following the first content frame, and a third content frame indicating an outcome of the physical task, the third content frame sequentially following the second content frame. The actions include obtaining, from a brainwave sensor, EEG signals of the user during presentation of the diagnostic content. The actions include providing the EEG signals as input features to a machine learning model that is trained to predict a psychological state of the user based on the EEG signals.

A breathing gases supply apparatus 1 can comprise a blower 103/105 and breathing circuit for delivering breathing gases to a patient. The apparatus also can comprise a first controller 109, the controller 109 configured to receive input from at least one sensor 110-112 indicative of patient breathing, and a transmitter 201 configured to communicate with the controller 109 and transmit control signals to an electronic apparatus 203. The controller 109 can be configured to determine sleep in a patient based on the occurrence of a breathing pattern indicative of sleep, detected from the input received from the sensor 110-112 and upon determining sleep, operate the transmitter 201 to send a control signal to control an electronic apparatus 203.

A monitor that includes multiple detection channels having multiple input ports for receiving a group of electrical physiological signals from a person; wherein multiple switching circuits of the monitor are configured according to a first configuration when the monitor operates in a first mode, thereby causing each electrical physiological signal of the group to be processed by up to a single selected detection channel of the multiple detection channels; wherein the multiple switching circuits of the monitor are configured according to a second configuration when the monitor operates in a second mode thereby causing one or more of the multiple electrical physiological signals of the group to be processed by at least two selected detection channels of the multiple detection channels.

System and method for evaluating a cognitive load on a user, corresponding to a stimulus is disclosed. Electroencephalogram (EEG) data corresponding to the stimulus of a user is received. The stimulus corresponds to a mental task performed by the user. The EEG data is split into a plurality of slots. A slot of the plurality of slots comprises a subset of the EEG data. One or more EEG features are extracted from the subset of the EEG data. The one or more EEG features are represented in one of a frequency domain and a time domain. A plurality of data points present in the one or more EEG features is grouped into two or more clusters using an unsupervised learning technique. The two or more clusters comprise one or more data points of the plurality of data points. The one or more data points correspond to a level of the cognitive load.

A system for monitoring the cardiopulmonary functioning of a person includes a remote terminal and a sensor module configured to be worn by the person. The sensor module includes at least one physiological sensor configured to sense the following types of physiological information generated by the person: pulse rate, blood flow, and blood pressure; at least one signal processor configured to process signals generated by the at least one physiological sensor; and at least one transmitter responsive to the at least one signal processor that is configured to transmit at least one signal to the at least one remote terminal. The at least one signal processor is configured to focus processing resources on one of the types of physiological information in response to a specified preference by the person.

Aspects of the present disclosure provide methods and apparatuses for determining a subject's sleep stage based on a PPG signal measured using an in-ear earpiece. In aspects, one or more physiological signals are estimated based on the PPG. Based, at least in part, on the determined sleep stage, one or more outputs are provided. In an example, the outputs are provided to the subject, the subject's physician, the subject's clinician, the cloud, and/or a device external to the apparatus. The methods and apparatus of determining the subject's sleep state described herein are continuous and non-invasive and eliminate the need for a clinical setting.

Exosuit systems and methods according to various embodiments are described herein. The exosuit system can be a suit that is worn by a wearer on the outside of his or her body. It may be worn under the wearer's normal clothing, over their clothing, between layers of clothing, or may be the wearer's primary clothing itself. The exosuit may be assistive, as it physically assists the wearer in performing particular activities, or can provide other functionality such as communication to the wearer through physical expressions to the body, engagement of the environment, or capturing of information from the wearer.