A volatile organic compound detection device includes a collector comprising: a collector material configured to collect volatile organic compounds given off from a patient's skin; a heater comprising a heating element, the heating element configured to emit a thermal pulse to desorb the volatile organic compounds from the collector material; and a flow channel configured to receive the volatile organic compounds desorbed by the heater; and a fastener configured to secure the collector to the patient's skin.

There is provided a method of generating deep brain stimulation signals, the method comprising receiving a plurality of sensor signals from a corresponding plurality of sensors on or in a subject, and using the received sensor signals to generate a plurality of stimulation signals for application at a corresponding plurality of target sites in the brain of the subject. There is further provided a method of generating stimulation signals, the method comprising receiving a plurality of sensor signals from a corresponding plurality of sensors on or in a subject, and using the received sensor signals to generate a plurality of stimulation signals for application at a corresponding plurality of target sites on or in the subject using a model of the response of neurons in the subject to the stimulation signals that models neural tissue as a plurality of coupled populations of neurons.

One embodiment provides a method, including: obtaining EEG data from one or more single channel EEG sensor worn by a user; classifying, using a processor, the EEG data as one of nominal and abnormal; and providing an indication associated with a classification of the EEG data. Other embodiments are described and claimed.

An apparatus for minimally-invasive, including non-invasive, prevention and/or treatment of hydrocephalus and method for use of the same are disclosed. In one embodiment of the apparatus, a housing is sized for superjacent contact with a skull having a fontanel. Within the housing, a compartment includes a pressure applicator, such as a fluid-filled bladder, under the control of a pressure regulator. The pressure applicator is configured to selectively apply an external pressure to the fontanel. The compartment includes a pressure sensor configured to measure intracranial pulse pressure of the fontanel. Further, in one embodiment, the apparatus can cause pulse pressure modulation by adjusting the intracranial pulse pressure via the pressure applicator. This enables a non-invasive measurement of the pulse pressure and modulation thereof in infants, for example.

There is provided a method for seizure detection. The method includes: obtaining brain signal data of brain electrical activity of a subject; processing the brain signal data using a deep neural network to obtain a first processed output data of the brain signal data, the first processed output data indicating one or more seizure events in the brain signal data; processing the first processed output data using a statistical model to obtain a second processed output data of the brain signal data, wherein the statistical model is configured to model transitions between the one or more seizure events and one or more non-seizure events in the first processed output data of the brain signal data; and determining the one or more seizure events based on the second processed output data of the brain signal data.

An implantable medical device includes a detecting unit, a control unit and a communication unit. The control unit uses a seizure prediction algorithm to predict epilepsy seizure events in real time based on physiological information detected by the detecting unit, and stores internal data which comprise the detected physiological information and prediction information about the prediction result. The control unit is configured to, in a first communication mode, control its memory unit and communication unit to transmit the internal data to the external monitoring device, and in a second communication mode, control the communication unit to receive an updated seizure prediction algorithm from the external monitoring device and stores the algorithm in the memory unit for predicting seizure events.

Systems, processes and devices for real-time brain monitoring for epileptic spasms and hypsarrhythmia or electrodecremental events to generate and control an interface of a display device with a visual representation of a Brain Value Index for epileptic spasms and hypsarrhythmia or electrodecremental events, a connectivity map and treatment guidance. Systems, processes and devices for real-time brain monitoring capture sensor data, process the data and dynamically update the interface in real-time.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, an identity of a vehicle operator may be determined and a vehicle operator profile and/or operating data regarding autonomous operation features of the vehicle may be received after the vehicle operator opts into a rewards program and agrees to share their data. Autonomous operation and vehicle operator risk levels associated with operation of the autonomous or semi-autonomous vehicle may be determined. Based upon the risk levels and/or comparison thereof, one or more autonomous operation features may be disengaged. A preparedness level of the vehicle operator to assume or reassume control of operating the vehicle is determined prior to disengagement. If satisfactory, an alert is presented to the vehicle operator prior to disengagement of the autonomous operation features.

A system for modeling neurological activity includes a computer having one or more processors, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices. The program instructions are configured to receive electroencephalogram (“EEG”) data generated by an EEG device coupled to a plurality of electrodes disposed on a brain, the EEG data comprising a plurality of waveforms representative of electrical activity detected by the plurality of electrodes over a period of time; generate a graphical brain model representative of the brain; to convert the EEG data into a graphical EEG model representative of electrical activity; integrate the EEG model with the brain model, thereby enabling visualization of and interaction with the EEG model within the context of the brain model; and communicate the integrated EEG and brain model to a display.

The present disclosure relates to a device for predicting, detecting, monitoring, and controlling epilepsy and methods thereof. In particular, the present disclosure relates to early detection and control of epileptic seizures using sensor-based device. In some embodiments, the sensor-based device is wearable.