A vision testing device includes a light-occluding casing for administering vision tests. A viewing station is coupled to the light-occluding casing so a test subject can see a first digital display housed within the light-occluding casing. A second digital display is external to the light-occluding casing and is configured to receive touch-based input. One or more predetermined vision tests are displayed via the first digital display. The second digital display receives input corresponding to the vision test displayed via the first digital display. The second digital display includes response indicators that can be activated via a swiping motion on the second digital display, and a response is recorded as a result of the swiping motion. Each answer corresponding to a swiping motion is stored and output as a result of the vision test.

Systems and methods for assessing the visual acuity of person using a computerized consumer device are described. The approach involves determining a separation distance between a human user and the consumer device based on an image size of a physical feature of the user, instructing the user to adjust the separation between the user and the consumer device until a predetermined separation distance range is achieved, presenting a visual acuity test to the user including displaying predetermined optotypes for identification by the user, recording the user's spoken identifications of the predetermined optotypes and providing real-time feedback to the user of detection of the spoken indications by the consumer device, carrying out voice recognition on the spoken identifications to generate corresponding converted text, comparing recognized words of the converted text to permissible words corresponding to the predetermined optotypes, determining a score based on the comparison, and determining whether the person passed the visual acuity test.

The present invention provides a human-computer interactive rehabilitation system, which can automatically calculate rehabilitation strength suitable for the patient, so that it is not necessary to manually evaluate and adjust the parameter settings in human-computer interactive rehabilitation system when different patients use it. At the same time, the human-machine interactive rehabilitation system and the hospital end can track the rehabilitation status and intervene through the data platform at any time. The platform establishes a cloud community feedback and encouragement mechanism, and immediately transmits the rehabilitation results to the designated barriers of the patients, provides patient encouragement feedback, and strengthens the community interaction and linkage in the medical relationship.

The present invention provides a human-computer interactive rehabilitation system, which can automatically calculate rehabilitation strength suitable for the patient, so that it is not necessary to manually evaluate and adjust the parameter settings in human-computer interactive rehabilitation system when different patients use it. At the same time, the human-machine interactive rehabilitation system and the hospital end can track the rehabilitation status and intervene through the data platform at any time. The platform establishes a cloud community feedback and encouragement mechanism, and immediately transmits the rehabilitation results to the designated barriers of the patients, provides patient encouragement feedback, and strengthens the community interaction and linkage in the medical relationship.

A ring halometer system configured to quantify dysphotopsias in a patient. The system includes a white screen and a first light source configured to emit a glare source from the white screen. The glare source is configured to form a veil of light visible to the patient when the glare source interacts with an optical surface of the eye of the patient. The system also includes a second light source configured to project a light ring with varying luminance concentric with the glare light source on the white screen, and a controller coupled to the second light source configured to adjust a size of the light ring. The system may also include an electronic device configured to determine a level of bothersomeness of the dysphotopsias experienced by the patient based on the size of the light ring.

The present disclosure describes the clinical workflow, method, apparatus and system of an on demand artificial intelligence visual screening and visual field screening system that incorporates a display simulator cockpit frame system inside a booth, kiosk, or exam room with machine learning and telemedicine capabilities. According to various embodiments, an artificial intelligent, physical or virtual assistant may help in the screening process of the patient, and an eye doctor via telemedicine may connect to the computers in display simulator cockpit system to perform necessary medical consultations, visual examination or screenings via the display simulator cockpit frame set-up display system. Where an on demand health care provider via remote administration tool technology, remote screen sharing and remote control software control the medical equipment, provide medical consultations and medical examination to a patient from anywhere in the world via cellphone wireless networks or wifi to interconnect both systems.

The present disclosure describes the clinical workflow, method, apparatus and system of an on demand artificial intelligence visual screening and visual field screening system that incorporates a display simulator cockpit frame system inside a booth, kiosk, or exam room with machine learning and telemedicine capabilities. According to various embodiments, an artificial intelligent, physical or virtual assistant may help in the screening process of the patient, and an eye doctor via telemedicine may connect to the computers in display simulator cockpit system to perform necessary medical consultations, visual examination or screenings via the display simulator cockpit frame set-up display system. Where an on demand health care provider via remote administration tool technology, remote screen sharing and remote control software control the medical equipment, provide medical consultations and medical examination to a patient from anywhere in the world via cellphone wireless networks or wifi to interconnect both systems.

Disclosed herein are methods and systems of evaluating test-retest precision using fractional rank precision or mean-average precision, comprising: a) collecting a test and a retest result of each subject, wherein the results are described in feature space(s) and collected from a vision test machine; b) selecting, a first test result of a first subject; c) calculating distances from the first test result to the retest result of each subject; d) assessing, a similarity between the first test result and the retest result of each subject by ranking the distances in a non-descending order; e) assessing a rank precision for the first subject based on a rank of a distance from the first test result to the retest result of the first subject; f) repeating b), c), d), and e) for each subject; and evaluating, the test-retest precision based on the rank precision for each of the plurality of subjects.

Disclosed herein are methods and systems of evaluating test-retest precision using fractional rank precision or mean-average precision, comprising: a) collecting a test and a retest result of each subject, wherein the results are described in feature space(s) and collected from a vision test machine; b) selecting, a first test result of a first subject; c) calculating distances from the first test result to the retest result of each subject; d) assessing, a similarity between the first test result and the retest result of each subject by ranking the distances in a non-descending order; e) assessing a rank precision for the first subject based on a rank of a distance from the first test result to the retest result of the first subject; f) repeating b), c), d), and e) for each subject; and evaluating, the test-retest precision based on the rank precision for each of the plurality of subjects.

Disclosed herein are methods and systems of evaluating test-retest precision using fractional rank precision or mean-average precision, comprising: a) collecting a test and a retest result of each subject, wherein the results are described in feature space(s) and collected from a vision test machine; b) selecting, a first test result of a first subject; c) calculating distances from the first test result to the retest result of each subject; d) assessing, a similarity between the first test result and the retest result of each subject by ranking the distances in a non-descending order; e) assessing a rank precision for the first subject based on a rank of a distance from the first test result to the retest result of the first subject; f) repeating b), c), d), and e) for each subject; and evaluating, the test-retest precision based on the rank precision for each of the plurality of subjects.