A medical imaging binocular indirect ophthalmoscope with computational processing unit, enabling simultaneous or time-delayed viewing and collaborative review of photographs or videos from an eye examination. The invention also claims a method for photographing and integrating information associated with the images, videos, or other data generated from the eye examination.

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 disclosure relates to head-mounted vision detection equipment, vision detection method and electronic equipment, which relates to the technical field of vision detection. The head-mounted vision detection equipment includes a virtual reality headset, a sound collection device and a fundus detection device that are arranged on the virtual reality headset, and a processor. The vision detection headset is configured to display content to be recognized under control of the processor; the sound collection device is configured to obtain a recognition voice of a wearer for the content to be recognized; the fundus detection device is configured to obtain a fundus image of the wearer; and the processor is configured to acquire the recognition voice and the fundus image.

According to some embodiments, a system and method for calculating binocular alignment is disclosed. The system and method comprise and utilize a first computing device for displaying different images for a first eye associated with a patient and a second eye associated with the patient. The first computing device is worn by the patient. A second computing device is used to determine a position of the first eye and the second eye.

A fundus illumination system includes an array of light sources, a first optical combiner, and a second optical combiner. The array of light sources are configured to be selectively enabled to emit non-visible light to illuminate a fundus of an eye. The first optical combiner is configured to receive reflected non-visible light that is reflected by the eye, direct a first component of the reflected non-visible light to a first camera to generate an image of the eye, and pass a second component of the reflected non-visible light. The second optical combiner is configured to receive a fundus imaging light responsive to the second component of the reflected non-visible light, and to direct the fundus imaging light to a second camera to generate an image of the fundus.

A head-mounted video camera, a processor, and a display are integrated within the head-mounted device worn by the user. The head-mounted device is configured to capture images of the environment and subject those images to specialized processing in order to diagnose and/or make up for deficiencies in the user's eyesight. Different modes of operating the device are provided that enable the user to configure the device for a specific application. The modes of operation include at least an assistive mode, a diagnostic mode, and a therapeutic mode. Each mode of operation may include further options, where each option is dedicated to a specific processing approach specific to a condition that may afflict the user, ranging from contrast sensitivity issues to strabismus.

Optimizing and/or personalizing activities to a user through artificial intelligence and/or virtual reality.

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.

An ophthalmic information processing apparatus includes a feature amount extractor and a classifier. The feature amount extractor is configured to extract a feature amount of each of two or more images different from each other of a subject’s eye. The classifier is configured to output two or more confidence score information for estimating classification result of a pathological condition of a disease of the subject’s eye, based on the feature amounts of each of the two or more images extracted by the feature amount extractor and one or more background data representing a state of the subject or a state of the subject’s eye.

A gaze-tracking method and system are disclosed that employs gaze rays generated from measured/tracked eye movements and fixation for interaction with objects and environment within a three-dimensional computing environment. The gaze ray is tracked to provide measures of ocular control, fovea control, and/or associated neural pathways in which the measures can be then used for one or more physiological assessments of the user, including, for example, eye dominance determination, vestibular assessment, visual fixation assessment, optokinetic assessment, smooth pursuit assessment, nystagmus quick phase assessment, saccades assessment, and vergence assessment.