Methods, systems and apparatus including computer programs encoded on a mobile device for measuring intraocular pressure among other parameters of an eye using image processing with deep neural networks. One or more physical processors of the computer system are programmed with computer program instructions which, when executed cause the computer system to obtain an image of the eye to be used for intraocular pressure measurement. One or more physical processors of the computer system are programmed with computer program instructions which, when executed cause the computer system to estimate the intraocular pressure of an eye from a picture of that eye.

An apparatus for at least one of diagnosing or treating an eye condition can include a goggle enclosure, sized and shaped to be seated on an eye socket of an eye to provide one or more cavities within the enclosure that extend about an entire exposed anterior portion of the eye, a pump, in fluidic communication with the one or more cavities to apply a fluid pressure to the one or more cavities, the pump configured to adjust a fluid pressure within the one or more cavities of the goggle enclosure, and a control circuit, including a data interface to receive data directly or indirectly indicating at least one of an intraorbital pressure, ICP, IOP, or a relationship between ICP and IOP, and based on processing the received data as a feedback control variable, controlling the pump to adjust the fluid pressure within the one or more cavities, the controlling including using further monitoring of the received data to control the pump.

Apparatus include a particle array configured to propagate an incident solitary wave to an eye, a housing configured to support the particle array, and a sensor coupled to the particle array and configured to detect a return solitary wave propagating along the particle array from the eye. Methods include directing an incident solitary wave along a solitary wave particle array coupled to an eye and detecting a return solitary wave propagating along the solitary wave particle array from the eye. Methods also include estimating intraocular pressure for the eye by comparing solitary wave data to a relationship between a time of return solitary wave time of flight and an intraocular pressure.

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.

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.

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.

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.

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.

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.

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.