Methods of analysis to extract and assess brain data collected from subject animals, including humans, to detect intentional and unintentional brain activity and other unexpected signals are disclosed. These signals are correlated to higher cognitive brain functions or unintended, potentially adverse events, such as a stroke or seizure, and to translation of those signals into defined trigger events or tasks.

A mobility controlling method and apparatus based on error monitoring are provided. The mobility controlling method includes: collecting an Event-Related Potential (ERP) for at least one passenger in a mobility for a predetermined time, determining an error factor by analyzing the ERP that is collected for the predetermined time, and performing mobility feedback based on the error factor.

Provided are a highly confidential personal authentication device which uses brain waves, a personal authentication method, and a personal authentication system and program. The authentication device using brain waves is provided with: an electroencephalograph; and a processing unit which, with respect to brain waves with respect to a plurality of stimulus events obtained by the electroencephalograph, determines a discrimination score according to a discrimination model for estimating brain information for each authentication candidate accumulated in advance, based on a discrimination-model-to-discrimination-model comparison of the discrimination score, identifies and authenticates an authentication candidate who provided the model. The identifying of the authentication candidate based on the discrimination score in the processing unit is based on the discrimination score and/or decoding accuracy determined from the discrimination score.

Technologies for filtering biosignals include one or more biosignal sensors coupled to a user to receive biosignals and a computing device to receive biosignals from the biosignal sensors. The biosignal sensors filter the received biosignals to identify abnormal biosignals using a plurality of domain filters including a time domain filter and a frequency domain filter. The biosignals identified as abnormal by each of the domain filters are transmitted to the computing device, while the remaining biosignals are discarded.

A wearable device includes a wearable device main body, a sensor part configured to contact a skin surface of a user of the wearable device, and measure a bio-signal of the user, and a shock absorber that is interposed between the wearable device main body and the sensor part to mechanically connect the wearable device main body and the sensor part, and that is configured to reduce motion transmission between the wearable device main body and the sensor part to permit the wearable device main body to move independently from the sensor part.

In an aspect of the invention, a method of identifying sensory inputs affecting working memory load of an individual is provided. The method comprises monitoring (S101) working memory load of the individual using a sensor device, detecting (S102) an increase in the working memory load of the individual, and identifying (S103), in response to the detected increase, at least one sensory input affecting the working memory load of the individual.

A learning system includes an output unit that outputs a first problem and a display message prompting a user to take a break, an acquisition unit that acquires an answer to the first problem from the user, an electroencephalogram measurement unit that measures an electroencephalogram of the user, and a control unit. The control unit determines whether first motivation is present on the basis of a first event-related potential included in the electroencephalogram and starting from a timing at which the first problem is output, determines whether second motivation of the user is present on the basis of a second event-related potential included in the electroencephalogram and starting from a timing at which the answer is acquired, and instructs the output unit to output a display message prompting the user to take a break if the first motivation is not present and the second motivations is not present.

A two part patient monitoring device includes an activator module and a sensor device. The activator module includes a non-galvanic data port that creates a communication path with a non-galvanic data port on the sensor device. The activator module includes power contact pads that are each at least partially surrounded by a bias ring. A bias voltage is applied to the bias rings and a processor or circuit in the activator module monitors the voltage on the bias ring to detect a leakage current. The sensor module includes power contact pins that engage the power contact pads to transfer power from the activator module to the sensor device. Each of the contact pins are surrounded by a seal member such that the connection between the power contact pins and the power contact pads is protected from debris and/or moisture.

An image generation system includes a region of interest identifying unit operable to identify a region of interest within a piece of content, the piece of content comprising one or more objects, and an image generation unit operable to generate an image for display comprising one or more of the one or more objects such that objects at a different visual depth to the region of interest are present in the generated image at a lower quality.

Provided are methods of inhibiting spreading depolarization in a subject by administering a sigma-1 agonist or a sigma-1 positive modulator to the subject. In some cases the subject is administered fenfluramine as the sigma-1 positive modulator. In some cases, the subject has been diagnosed with epilepsy, traumatic brain injury, migraines, stroke, ischemic attacks, hypoxia or an increased risk of sudden unexpected death in epilepsy (SUDEP), or a combination thereof.