Techniques for lens design and evaluation involve configuring a rule comprising one of a “with the rule” and “against the rule”, configuring a cylinder comprising one of a “positive cylinder” and a “negative cylinder”, and utilizing the rule and the cylinder in one or both of a residual astigmatism metric algorithm and spherical equivalent metric algorithm to generate a discrete metric values each corresponding to ranges of residual refractive error.

Apparatuses or methods for determining a refractive error of an eye are disclosed. An intensity of light coming from an eye is measured, using a detector device, through at least two or at least three different apertures of the aperture device. The refractive error is then calculated based on the measured intensities.

Apparatuses or methods for determining a refractive error of an eye are disclosed. An intensity of light coming from an eye is measured, using a detector device, through at least two or at least three different apertures of the aperture device. The refractive error is then calculated based on the measured intensities.

Disclosed herein are methods and apparatus for making a determination about an eye comprising detecting light reflected out of an eye of a subject from a retina of the eye of the subject and making a determination about the eye of the subject based upon the reflected light, wherein the light is adjusted for color temperature when making the determination about the eye.

Disclosed herein are methods and apparatus for making a determination about an eye comprising detecting light reflected out of an eye of a subject from a retina of the eye of the subject and making a determination about the eye of the subject based upon the reflected light, wherein the light is adjusted for color temperature when making the determination about the eye.

To provide a display apparatus that makes it possible to further improve a performance in controlling video presentation according to characteristics of an eyeball of a user. A display apparatus is provided that includes a light source; a processor that performs processing on a distribution of characteristics of an eyeball; a monitoring section that monitors a state of the eyeball; a matching section that performs matching on the distribution of the characteristics of the eyeball and the state of the eyeball; and an irradiator that irradiates a specified position on a retina with video display light emitted by the light source.

Improved optical coherence tomography systems and methods to measure thickness of the retina are presented. The systems may be compact, handheld, provide in-home monitoring, allow the patient to measure himself or herself, and be robust enough to be dropped while still measuring the retina reliably.

Provided are an apparatus and a computer-readable storage medium having stored therein a program that can determine keratoconus with a simple configuration so as to allow the apparatus and the program to be distributed widely and contribute to early diagnosis of keratoconus. In a keratometer as a keratoconus determination apparatus, a prediction model for keratoconus is stored in a memory. The prediction model is a logistic regression model in which three parameters that are a steep meridian refractive power, a flat meridian refractive power, and a value indicating whether or not a subject eye has a with-the-rule astigmatism, are independent variables, and a probability of keratoconus is a dependent variable. A control unit substitutes the three parameter values into the prediction model, to obtain a probability of keratoconus. When the probability is greater than a cutoff value, the subject eye is determined to be suspected of having keratoconus.

Provided are an apparatus and a computer-readable storage medium having stored therein a program that can determine keratoconus with a simple configuration so as to allow the apparatus and the program to be distributed widely and contribute to early diagnosis of keratoconus. In a keratometer as a keratoconus determination apparatus, a prediction model for keratoconus is stored in a memory. The prediction model is a logistic regression model in which three parameters that are a steep meridian refractive power, a flat meridian refractive power, and a value indicating whether or not a subject eye has a with-the-rule astigmatism, are independent variables, and a probability of keratoconus is a dependent variable. A control unit substitutes the three parameter values into the prediction model, to obtain a probability of keratoconus. When the probability is greater than a cutoff value, the subject eye is determined to be suspected of having keratoconus.

A subjective optometry apparatus includes an optometry unit having an optical member, being located in front of a subject eye, and changing optical characteristics of a target light flus with using the optical member, and a measurement optical system that has a light projecting optical system for applying measurement light emitted from a measurement light source to a fundus of the subject eye through the optometry unit, and a light receiving optical system in which a detector receives reflected light of the measurement light reflected on the fundus of the subject eye through the optometry unit, and that objectively measures the optical characteristics of the subject eye. An optical axis of the measurement optical system is set to be off-axis from an optical axis of the optical member in the optometry unit.