A system may include a portable EEG headset configured to capture user EEG signals, a computing device having a graphical user interface, and one or more processors. The one or more processors may be configured to execute instructions to (a) display a sequence of images on the graphical user interface; (b) receive, from the portable EEG headset, user EEG signals that are time-synchronized with the display of the sequence of images; (c) extract from the user EEG signals, one or more event-related potential (ERP) peaks associated with each image; (d) quantify one or more affect-related measures associated with the one or more ERP peaks; and (e) compare the quantified one or more affect-related measures to baseline data to determine a risk to the user.

A system may include a portable EEG headset configured to capture user EEG signals, a computing device having a graphical user interface, and one or more processors. The one or more processors may be configured to execute instructions to (a) display a sequence of images on the graphical user interface; (b) receive, from the portable EEG headset, user EEG signals that are time-synchronized with the display of the sequence of images; (c) extract from the user EEG signals, one or more event-related potential (ERP) peaks associated with each image; (d) quantify one or more affect-related measures associated with the one or more ERP peaks; and (e) compare the quantified one or more affect-related measures to baseline data to determine a risk to the user.

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.

The technology provides a multi-body earpiece suitable for use as an in-ear sensor system, which can be used for biometrics or a human-computer interface. The multi-body earpiece includes two body elements connected together by a flexure. These components provide at least 3 points of contact along different parts of the outer ear, in which the flexure is tethered to the two bodies and arranged to lock them in place during wear. In addition to having stability from moving while minimizing sound occlusion, this arrangement enables any electrodes for the on-board sensor(s) to remain in contact with the skin of the ear, and provide as many contact points in desired areas as the electronics dictate for the signals of interest.

A mobile user borne brain activity data and surrounding environment data correlation system comprising a brain activity sensing subsystem, a recording subsystem, a measurement computer subsystem, a user sensing subsystem, a surrounding environment sensing subsystem, a correlation subsystem, a user portable electronic device, a non-transitory computer readable medium, and a computer processing device. The mobile user borne system collects and records brain activity data and surrounding environment data and statistically correlates and processes the data for communicating the data into a recipient biological, mechatronic, or bio-mechatronic system.

The invention relates to a method and a device for providing a parameter which indicates a loss of consciousness of a patient under anesthesia. The method has the steps of: detecting (301) at least one EEG signal on the head of the patient; continuously determining (302) the spectral cut-off frequency in a current timeframe of the EEG signal; determining (303) the curve of the spectral cut-off frequency of the EEG signal in a period of time which begins before an anesthesia-inducing medication is administered and ends after the anesthesia-induced loss of consciousness is initiated; determining (304) the absolute minimum of the spectral cut-off frequency in the period of time, wherein a negative peak of the spectral cut-off frequency lies in the absolute minimum, and providing (305) information regarding at which point in time the absolute minimum was reached as a parameter for an indicative notification of the loss of consciousness of the patient.

The invention relates to a method and a device for providing a parameter which indicates a loss of consciousness of a patient under anesthesia. The method has the steps of: detecting (301) at least one EEG signal on the head of the patient; continuously determining (302) the spectral cut-off frequency in a current timeframe of the EEG signal; determining (303) the curve of the spectral cut-off frequency of the EEG signal in a period of time which begins before an anesthesia-inducing medication is administered and ends after the anesthesia-induced loss of consciousness is initiated; determining (304) the absolute minimum of the spectral cut-off frequency in the period of time, wherein a negative peak of the spectral cut-off frequency lies in the absolute minimum, and providing (305) information regarding at which point in time the absolute minimum was reached as a parameter for an indicative notification of the loss of consciousness of the patient.

A Brain-Computer Interface (BCI) based rehabilitation system and method is described in which an auditory or visual stimulus is provided to a user instructing them to imagine performing a physical action with a body part such as a hand during a trial period. A BCI processes the electroencephalography (EEG) signals to perform feature extraction and then feature translation (classification) to determine if the user intended to perform the action. If the intension was detected the body part is incrementally moved to provide proprioceptive feedback to the user. The feedback process is repeated at a Feedback Update Interval (FUI) of 100 ms or less. Preferably a reaction time test is used to determine the optimal FUI for an individual where shorter FUIs used for shorter reaction times. In one embodiment, if the user has slow reaction times, the FUI is initially between 100 ms and 1000 ms and gradually decreased over a series of sessions until the FUI is less than 100 ms.

The application belongs to the field of earphone technology, and discloses a type of monitoring earphones intended for autism spectrum disorder. The upper part of headband is fixed with an electroencephalogram signal sensor, and the two sides thereof are respectively secured with No. 1 buckle and No. 2 buckle, which are used to fix No. 1 No. 1 signal processor and No. 2 signal processor on the upper part of the headband. Once the user is found by the application to be not himself/herself, the earphone will play his/her favorite music with Bluetooth, serving the function of music therapy.

A mote includes an optical receiver that wirelessly receives a power and data signal in form of NIR light energy within a patient and converts the NIR light energy to an electrical signal having a supply voltage. A control module supplies the supply voltage to power devices of the mote. A clock generation circuit locks onto a target clock frequency based on the power and data signal and generates clock signals. A data recovery circuit sets parameters of one of the devices based on the power and data signal and a first clock signal. An amplifier amplifies a neuron signal detected via an electrode inserted in tissue of the patient. A chip identifier module, based on a second clock signal, generates a recorded data signal based on a mote chip identifier and the neuron signal. A driver transmits the recorded data signal via a LED or a RF transmitter.