A subjective optometry apparatus includes: a subjective measurer which has a corrective optical system disposed on an optical path of a light projecting optical system configured to project a target light flux toward an examinee's eye and configured to change an optical characteristic of the target light flux and which is configured to subjectively measure an optical characteristic of the examinee's eye; an acquisitor configured to acquire position information on at least one of examinee's right and left eyes; a determiner configured to determine, based on the position information acquired by the acquisitor, whether or not subjective measurement can be implemented in a binocular open state of the examinee's right and left eyes, thereby acquiring determination information; and a determination information output unit configured to output the determination information acquired by the determiner.

A method and apparatus are provided for measuring a sensitivity level across a visual field of a subject defined by a set of locations. The method comprises: presenting a sequence of visual stimuli on a display, wherein each stimulus in the sequence has a respective intensity level and is positioned on the display to correspond to a respective location from the set of locations; obtaining from the subject, for each stimulus, a respective binary response indicating whether or not the stimulus was seen by the subject; and after receiving the response from the subject for a given stimulus in the sequence, using a statistical model to estimate, for each location in the set of locations, the sensitivity level at that location; wherein the statistical model incorporates information about correlations in responses between different locations from the set of locations and takes as input, the respective binary response, intensity level and location for multiple stimuli presented in said sequence up to and including the given stimulus.

In some implementations, methods for selecting a set of beacons that are to be monitored by a mobile device may be employed. Specifically, an optimal set of beacons to monitor may be provided to a mobile device depending on particular groups of beacons that are in proximity to the mobile device, the distance from the mobile device to each of the particular groups of beacons, and the mobile device's position/movements as provided by a tracking service such as GPS. These techniques may ensure that the mobile device is not blind to the closest and/or most relevant beacons.

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.

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.

Methods and systems for dynamically determining stimuli characteristics for vision defect determination during a vision test. The methods and systems convert the feedback received from the binary suprathreshold test into a feature input that is provided to a prediction model. The prediction model may be trained to predict non-binary characteristics for sets of locations and confidence scores associated with the sets of locations based on feedback indicating binary characteristics under which users see one or more stimuli presented on user interfaces.

Methods and systems for dynamically determining stimuli characteristics for vision defect determination during a vision test. The methods and systems convert the feedback received from the binary suprathreshold test into a feature input that is provided to a prediction model. The prediction model may be trained to predict non-binary characteristics for sets of locations and confidence scores associated with the sets of locations based on feedback indicating binary characteristics under which users see one or more stimuli presented on user interfaces.

Methods and diagnostic tools are provided for assessing contrast sensitivity in a subject in the presence and absence of luminance noise by: i) presenting to the subject a series of scenes, each scene comprising at least a first target having a preselected level of contrast superimposed on a uniform background and a second target having a preselected level of contrast superimposed on a luminance noise background, wherein in each successively presented scene the first and second targets that are superimposed on the uniform background and on the luminance noise background, respectively, have contrast levels that are different from the contrast levels of the first and second targets superimposed on the uniform background and on the luminance noise background, respectively, in the previously presented scene; ii) monitoring responses by the subject to step i); and iii) evaluating the contrast sensitivity of the subject based on the monitored responses.

Methods and diagnostic tools are provided for assessing contrast sensitivity in a subject in the presence and absence of luminance noise by: i) presenting to the subject a series of scenes, each scene comprising at least a first target having a preselected level of contrast superimposed on a uniform background and a second target having a preselected level of contrast superimposed on a luminance noise background, wherein in each successively presented scene the first and second targets that are superimposed on the uniform background and on the luminance noise background, respectively, have contrast levels that are different from the contrast levels of the first and second targets superimposed on the uniform background and on the luminance noise background, respectively, in the previously presented scene; ii) monitoring responses by the subject to step i); and iii) evaluating the contrast sensitivity of the subject based on the monitored responses.

A new ocular contact lens has been designed to increase the amount of light reaching the retina. The contact lens edge is chamfered to redirect and increase the light reaching the retina. A light source encircles and contacts the straight or curved chamfered edge. Additionally, a reflective cylinder and its top wall encircle the lens to block any loss of light. This distal edge of the contact lens may be rounded to increase the angle of retina visible. A new ocular imaging camera has a low-light camera subassembly with server, a photosensor next to low-light camera, a short cylindrical housing, a space between the camera subassembly and the housing, an internal program in server to detect good or poor image quality and an alarm for poor image quality, wherein an operator recaptures the image. A system has a highly efficient method to screen and diagnose a large number of patients using the new ocular contact lens and ocular imaging camera. The system receives and processes the photographs. The photographs are transmitted to eye care specialists' smart phone, tablet or virtual reality device for evaluation. As specified, the eye care specialist separates normal from abnormal, diagnoses the abnormality, and may even provide detailed information, such as the grade of the abnormality. The server receives this information and automatically generates the suitable report for the healthcare professional. The server also processes payment to the eye care specialist.