A non-transitory, computer readable, storage medium stores a self-optometry control program that is executed by a first information processing device and includes a self-optometry program. The self-optometry program causes the first information processing device to perform executing a calling operation based on a calling instruction and setting an examination timing for an assistance operation such that the assistance operation starts from an examination item that was performed at a timing the calling instruction was inputted.

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects.

A method of performing an optometric examination of a patient includes positioning the patient behind a phoropter; presenting visual stimuli to the patient using a computer-controlled device; recording the patient's response to the stimuli; automatically adjusting the settings of the phoropter to improve one or more characteristics of the patient's vision; and automatically determining the prescription for the refractive error correction for the patient.

Utilizing color light for focal stimulation of the macula for photobleaching and dark adaptation provides a means to isolate the recovery ability of different types of cones. Having the ability of selectively analyzing the recovery of different types of cones opens the opportunity to determine the effect of disease on cone type for diagnosis and monitoring of disease severity. An endpoint target with a noticeable difference between the center of the target and the peripheral ring of the target at endpoint is described.

A method and a device allow to determine the contrast sensitivity threshold of the eyes of a user in an automatic manner without requiring an experienced examiner or active attention of the user. The method includes: a) providing a dataset of track data including data of eye movements, wherein the eye movements are stimulated to elicit an optokinetic nystagmus in the eyes of the user and wherein the track data are related to a particular contrast and spatial frequency of the stimulus; b) estimating at least one velocity component of the eye movement; c) comparing the velocity component with a velocity threshold; d) comparing a fraction of the track data which exceed the velocity threshold with a fractional threshold for the dataset, which is classified as eliciting the optokinetic nystagmus at the particular contrast of the stimulus; and e) determining the contrast sensitivity threshold of the eyes of the user.

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user’s body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects.

The present invention provides an eye tracking system including: a pupil sensing unit sensing a pupil of a user by at least one sensor embedded in smart glasses; a display unit including smart lenses to which a plurality of target objects is floated; an eye tracking unit tracking an eye through at least one sensor and acquiring eye state information of the user for the plurality of target objects; and an input unit performing an input after selecting a specific object in which the eye of the user stays for a predetermined time or more among the plurality of target objects as an input object based on the eye state information, in which at least one of a size, a color, and a movement direction of the input object is changed based on the eye state information of the user.

A non-transitory, computer readable, storage medium stores an optometry control program including a self-optometry application program. The self-optometry application program, when executed by a first information processing device, causes the first information processing device to perform executing an assistance operation to assist in a progress of a self-optometry for an examinee when a problem occurs during the progress of the self-optometry.

A non-transitory, computer readable, storage medium stores an optometry control program including a self-optometry application program. The self-optometry application program, when executed by a first information processing device, causes the first information processing device to perform executing an assistance operation to assist in a progress of a self-optometry for an examinee when a problem occurs during the progress of the self-optometry.

In some embodiments, initial feedback indicating threshold characteristics (under which a user sees initial stimuli presented on a user interface) may be provided to a prediction model, and a set of predicted characteristics (for a set of locations of the user interface) and a set of confidence scores associated with the set of locations may be obtained via the prediction model. Based on the set of confidence scores, one or more locations may be selected to be tested during a visual test presentation. As an example, the locations may be selected over one or more other locations of the set of locations based on the set of confidence scores. Based on predicted characteristics associated with the selected locations, stimuli may be presented at the selected locations during the visual test presentation. Visual defect information for the user may be generated based on feedback from the visual test presentation.