A system for determining a treatment outcome for a subject for a neurological disorder includes a processor, a classifier and a display. The processor is configured to receive a set of electroencephalogram (EEG) data associated with the subject and to determine at least one functional connectivity parameter based on the EEG data. The classifier is coupled to the processor and is configured to receive the at least one functional connectivity parameter and to generate a prediction for a treatment outcome based on the at least one functional connectivity parameter. The display is coupled to the classifier and is configured to display the prediction for the treatment outcome.

A system for determining a treatment outcome for a subject for a neurological disorder includes a processor, a classifier and a display. The processor is configured to receive a set of electroencephalogram (EEG) data associated with the subject and to determine at least one functional connectivity parameter based on the EEG data. The classifier is coupled to the processor and is configured to receive the at least one functional connectivity parameter and to generate a prediction for a treatment outcome based on the at least one functional connectivity parameter. The display is coupled to the classifier and is configured to display the prediction for the treatment outcome.

Augmented reality systems and methods for user health analysis. Methods for user health analysis may include collecting data for an initial prediction model and continuing to collect additional data based on one or more data criteria. The methods may further include updating the initial prediction model based on the additional data to produce a revised prediction model or causing an intervention to occur based on the additional data. The data may be collected by a display system including one or more sensors configured to collect user-specific data and a display device configured to present virtual content to a user. The display device may be configured to output light with variable wavefront divergence.

Augmented reality systems and methods for user health analysis. Methods for user health analysis may include collecting data for an initial prediction model and continuing to collect additional data based on one or more data criteria. The methods may further include updating the initial prediction model based on the additional data to produce a revised prediction model or causing an intervention to occur based on the additional data. The data may be collected by a display system including one or more sensors configured to collect user-specific data and a display device configured to present virtual content to a user. The display device may be configured to output light with variable wavefront divergence.

A sensor connector apparatus is disclosed to connected between an electroencephalographic spectrum analyzer and a sensor for use in the electroencephalographic spectrum analyzer. The sensor connector apparatus includes sensor connectors. Each of the sensor connectors includes: a connector to be connected to the electroencephalographic spectrum analyzer; a connector lead where the connector is connected to one end of the connector lead; and a conductive connector electrode that is connected to another end of the connector lead, and is connected to a sensor electrode of the sensor. The electroencephalographic spectrum analyzer is a bispectral index (BIS) processor, the sensor is a BIS Quatro sensor to be connected to the BIS processor, and the connector is connected to a sensor electrode of the BIS Quatro sensor.

An intelligent surgical tool control system, comprising a tool management system; an indicating means to indicate at least one surgical event; a communicable database for storing, for each item of interest, its identity, its present 3D position and at least one previous 3D position; and at least one processor to identify, from a surgical event, an output surgical procedure. The tool management system can comprise a maneuvering mechanism to maneuver a surgical tool in at least two dimensions; and a controller to control at least one of activation and deactivation of a surgical tool and articulation of a surgical tool. The indicating means can indicate a surgical event selected from movement of a moving element and presence of an item of interest, where movement is determinable if the current 3D position of the moving element is substantially different from a previous 3D position of the same.

Broadly speaking, embodiments of the present techniques provide a skin-conformable and compact wearable electronic apparatus for monitoring physiological and/or brain signals of the wearer.

A skin condition estimation method of the present disclosure is a skin condition estimation method executed by a computer and includes: acquiring first information related to hormone balance; and estimating a future skin condition on an estimation date after a first acquisition date on which the first information is acquired based on the first information.

The present invention discloses a brain activity analysis method and apparatus, which is based on a nonlinear waveform decomposition technology, wherein the changes of the intrinsic features in brain waves are decomposed and demodulated to extract the modulation signals of the components, including the frequency-modulation signals and the amplitude-modulation signals. The present invention further uses a feature mask to determine whether to proceed further decomposition and demodulation of the extracted modulation signals. If not, the multidimensional changes of the intrinsic features are obtained according to the feature mask. Then, quantitation and identification is performed to obtain the status of brain function. The present invention not only effectively increases the accuracy of the identification but also uses the feature mask to obviously reduce the complexity and the load of computation.

The present invention discloses a brain activity analysis method and apparatus, which is based on a nonlinear waveform decomposition technology, wherein the changes of the intrinsic features in brain waves are decomposed and demodulated to extract the modulation signals of the components, including the frequency-modulation signals and the amplitude-modulation signals. The present invention further uses a feature mask to determine whether to proceed further decomposition and demodulation of the extracted modulation signals. If not, the multidimensional changes of the intrinsic features are obtained according to the feature mask. Then, quantitation and identification is performed to obtain the status of brain function. The present invention not only effectively increases the accuracy of the identification but also uses the feature mask to obviously reduce the complexity and the load of computation.