Methods and systems for assessing a health state of a person via eye movement-driven biometric systems are provided. Examples of the health states that it would be possible to detect with such a system are but not limited to brain injuries (e.g., concussions), dementia, Parkinson's disease, post-traumatic stress syndrome, schizophrenia, fatigue, cybersickness, autism, Bipolar Disorder and other health conditions that manifest themselves in abnormal behavior of the human visual system. Described methods and systems can also detect influence of alcohol and/or drugs. The system extracts biometric template of a person by deriving features from the captured eye movement signal. The system may compare the difference between previous healthy state of a tested person and newly captured template or an averaged biometric template created from the records of multiple healthy people state of multiple people and a newly captured template from a person who needs to be tested. Based on the difference between the templates, a decision of a health state of a person is made. Described methods and systems may work on any device that has eye tracking capabilities including but not limited to desktop mounted eye tracking systems, head mounted eye tracking systems such as Virtual Reality and Augmented Reality or stand-alone mounted eye tracking systems.

Methods, systems, and devices are disclosed for monitoring electrical signals of the brain. In one aspect, a system for monitoring electrical brain activity associated with visual field of a user includes a sensor unit to acquire electroencephalogram (EEG) signals including a plurality of EEG sensors attached to a casing attachable to the head of a user, a visual display unit attachable to the head of the user over the user's eyes to present visual stimuli, in which the visual stimuli is configured to evoke multifocal steady-state visual-evoked potentials (mfSSVEP) in the EEG signals exhibited by the user acquired by the sensor unit, and a data processing unit in communication with the sensor unit and the visual display unit to analyze the acquired EEG signals and produce an assessment of the user's visual field, in which the assessment indicates if there is a presence of visual field defects in the user's visual field.

Methods, systems, and apparatuses are described causing light to be emitted, causing a frequency at which the light is emitted to vary, receiving, based on the frequency variation, a user input, determining a critical flicker frequency (CFF) corresponding to the user input, and determining, based on the CFF, a disease state.

Applications for a Composite Neuro-physiological State (CNS) value include rating using the value as in indicator of participant emotional state in computer games and other social interaction applications. The CNS is computed based on biometric sensor data processed to express player engagement with content, game play, and other participants along multiple dimensions such as valence, arousal, and dominance. An apparatus is configured to perform the method using hardware, firmware, and/or software.

Applications for a Content Engagement Power (CEP) value include generating a script, text, or other communication content or for controlling playout of communication content based on neuro-physiological data, gathering neuro-physiological data correlated to consumption of communication content, or rating effectiveness of personal communications. The CEP is computed based on neuro-physiological sensor data processed to express engagement with content along multiple dimensions such as valence, arousal, and dominance. An apparatus is configured to perform the method using hardware, firmware, and/or software.

A display device and a method of manufacturing the same are disclosed. In one aspect, the display device includes a substrate including a separation area and a plurality of pixel formed over the substrate. The separation area is formed between adjacent pixels, and a plurality of through holes are respectively defined by a plurality of surrounding inner surfaces of the separation area, and wherein each of the inner surfaces passes through the substrate. The display device also includes an encapsulation layer formed over the substrate and covering the inner surfaces of the separation area.

The present invention generally relates to apparatus, software and methods for assessing ocular, ophthalmic, neurological, physiological, psychological and/or behavioral conditions. As disclosed herein, the conditions are assessed using eye-tracking technology that beneficially eliminates the need for a subject to fixate and maintain focus during testing or to produce a secondary (non-optical) physical movement or audible response, i.e., feedback. The subject is only required to look at a series of individual visual stimuli, which is generally an involuntary reaction. The reduced need for cognitive and/or physical involvement of a subject allows the present modalities to achieve greater accuracy, due to reduced human error, and to be used with a wide variety of subjects, including small children, patients with physical disabilities or injuries, patients with diminished mental capacity, elderly patients, animals, etc.

A display device and a method of manufacturing the same are disclosed. In one aspect, the display device includes a substrate including a separation area and a plurality of pixel formed over the substrate. The separation area is formed between adjacent pixels, and a plurality of through holes are respectively defined by a plurality of surrounding inner surfaces of the separation area, and wherein each of the inner surfaces passes through the substrate. The display device also includes an encapsulation layer formed over the substrate and covering the inner surfaces of the separation area.

A method for measuring flicker fusion threshold. Set a measurement scheme, including setting N 8-shaped digital frames in a background light area that flickers within a set frequency. Set ten groups of different frequency combinations being applied to the N 8-shaped digital frames. Assign each frequency in each group of the frequency combinations with a stroke of the 8-shaped digital frame. Randomly select, for each of the N 8-shaped digital frames, one from the ten groups of the frequency combinations. Determine the value of each frequency in each group of frequency combinations in the N groups of frequency combinations. Recognize, by the subject, the flickering digits on the N 8-shaped digital frames in the background light area within the set frequency range. Determine the range of the flicker fusion threshold or the final flicker fusion threshold of the subject according to the result that can be seen by the subject.

A method for attention-based neurofeedback training. The method includes deriving a brain activity parameter value from a subject by providing neurofeedback training to the subject based on a training protocol, assessing an attention level of the subject simultaneously with providing the neurofeedback training, and updating the training protocol based on the attention level and the brain activity parameter value.