The present systems and methods provide a mechanism to assess viewer behavior, features of stimuli, and the interaction between viewer behavior and stimuli. The systems and methods described herein for quantifying blink response and blink inhibition provide moment-by-moments measurements of viewer engagement by measuring what is or is not engaging enough to warrant viewers' inhibition of blinking. The present disclosure describes measures of visual scanning, eye movements, blink data, and blink timing data to derive a measure of how engaged a person is with what he or she is looking at. Blink-related data as a measure of viewer engagement provides a mechanism for determining the most engaging spatial and temporal aspects of a stimulus.

Embodiments are directed to identifying and measuring bodily states and feedback systems. A computer system initializes a tracking and measuring device to generate patient data related to a bodily state or feedback system of a patient. The computer system gathers the patient data using the initialized tracking and measuring device, and identifies a baseline parameter used to determine a baseline state relative to the gathered patient data. The computer system further gathers additional patient data using the initialized tracking and measuring device and compares the additional gathered patient data to the identified baseline parameter. Then, if the additional gathered patient data differs from the baseline state by a specified threshold amount, the computer system determines that a change in the patient's bodily state or feedback system has occurred and/or determines the amount of change in the bodily state or feedback systems that has occurred.

Methods, systems, and devices for personalized (e.g., user specific) eye openness estimation are described. A network model (e.g., a convolutional neural network) may be trained using a set of synthetic eye openness image data (e.g., synthetic face images with known degrees or percentages of eye openness) and a set of real eye openness image data (e.g., facial images of real persons that are annotated as either open eyed or closed eyed). A device may estimate, using the network model, a multi-stage eye openness level (e.g., a percentage or degree to which an eye is open) of a user based on captured real time eye openness image data. The degree of eye openness estimated by the network model may then be compared to an eye size of the user (e.g., a user specific maximum eye size), and a user specific eye openness level may be estimated based on the comparison.

Techniques are provided for determining a qualitative, quantitative and/or categorical assessment of one or more users and/or images with respect to one or more populations. The eye movement data of the user may be obtained with respect to each image of the one or more images displayed for a period of time. One or more memory performance measures and/or one or more salience performance measures may be determined using the eye movement data with respect to the one or more regions of the one or more images for one or more of predetermined time ranges of the period of time. The quantitative, qualitative and/or categorical assessment of the user and/or images presented may be determined with respect to one or more populations, using the one or more memory performance measures and/or one or more salience performance measures.

Aspects of the present invention relate to providing assistance to medical professionals during the performance of medical procedures through the use of technologies facilitated through a head-worn computer.

A sleeping mask includes a signal processor for processing sensor data, an infrared light source coupled to the signal processor and configured to emit infrared light toward an eyelid of a user, and an array of infrared sensors coupled to the signal processor and configured to receive infrared light reflected from the eyelid of the user.

A method for preventing and detecting a fall of a user and implementing a system including sensors and alarm, a pair of eyeglasses with hinged stems including rims for supporting glasses, worn by the user. The sensors are set in the hinged stems and the rims of the eyeglasses. The sensors include a triaxial accelerometer, an IR transmitter and an IR receiver of infra-red light both directed to the cornea of the user, and a barometric sensor. The triaxial accelerometer signal is acquired and processed to derive a walking pace parameter, a sit to stand parameter, a head posture parameter and an acceleration magnitude over the three axes. A composite index is computed based on the walking pace, the sit to stand and the head posture parameters. The alarm is generated if the first composite index exceeds a threshold.

Blepharometric data (data describing eyelid position as a function of time) is recorded and processed for the purposes of predicting a future risk and/or current occurrence of neurological events such as seizures. For example, in one embodiment blepharometric data is recorded via infrared reflectance oculography spectacles, and processed in real time thereby to extract a set of blepharometric artifacts. Where those artifacts indicate prolonged spiking in blink calmness (for example based on spiking in negative inter-event duration, or negative IED), an alert is able to be generated thereby to indicate that the subject is at risk of a seizure in a proximal time period. This provides an opportunity to implement mitigation measures, for example to reduce the likelihood of the seizure manifesting, and/or to mitigate harm should the seizure occur.

Usability in interactive character control is improved. An information processing device executed by one or more processors in an information processing device, the information processing method comprising: acquiring at least an electrooculogram signal from another device mounted on a head of a user; detecting at least movement of eyes of a user, based on the electrooculogram signal; display-controlling a character superimposed on an image that is being displayed on a screen; and controlling motion of the character, based on a result of detecting the movement of eyes.

A distracted driver detection device for use in a vehicle includes a processor, a video camera, and an accelerometer. The processor is configured to compute an eye open ratio (EOR) and a mouth open ratio (MOR). The processor is configured to provide an audio alert signal to an audio alert component and provide a visual alert signal to a visual alert component when the EOR is less than an EOR threshold for a prescribed EOR assessment time, when the MOR is greater than the MOR threshold for a prescribed MOR assessment time, or when the estimate of the acceleration is greater than an acceleration threshold. The EOR and MOR are calculated from facial landmarks that are generated by a Histogram of Oriented Gradients (HOG) algorithm implemented by the processor.