Modular platform for ocular evaluations
Inventors
Serafini, Randal Alexander • Warburton, Andrew Jinrui • Serafini, Claudio Randal • Patel, Aashay Dineshkumar • Labkovich, Margarita • Valliani, Aly Al-Amyn • Murarka, Sumeet • Sadot, Avner • TEICHER, Ilana • Jacobi, Ori • Galili, Tal Preger
Assignees
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Publication Number
US-12588811-B2
Publication Date
2026-03-31
Expiration Date
Abstract
A screening platform enables comprehensive ocular evaluations. The screening platform includes a harness that is configured to fit a head of a patient and that includes one or more electronic components that are operable to power an interchangeable module, a central processing unit (CPU) with a graphical processing unit (GPU), and the interchangeable module with communication capabilities to external computational devices, multiple display output devices, and several types of input devices from both an operator and a patient at-hand, wherein the interchangeable module is separable from the screening platform.
Core Innovation
The invention is a modular screening platform for comprehensive ocular evaluations that includes a head-fitting harness with electronic components that power a plurality of separable, interchangeable modules. The interchangeable modules have communication capabilities to external computational devices, multiple display output devices, and one or more input devices from both an operator and the patient. The harness further includes a battery pack mounted on a rear of the harness that provides a counterweight to a mass of an interchangeable module on the head of the patient.
The modular screening platform includes a first CPU with a graphical processing unit (GPU), where the CPU or the GPU controls, displays, and processes data from the interchangeable modules by employing a machine-learning model. The machine-learning model is trained with training data that relates how different patients performed ocular evaluations based on an order of different tests and types of interchangeable modules. The machine-learning model is also trained to receive an indication of one or more patient conditions associated with the patient and output tests and corresponding interchangeable modules based on that indication.
The machine-learning model outputs an optimization of the tests and an examination order for the patient that are used to identify one or more pathologies associated with one or more ocular conditions and a preliminary diagnosis. The platform is further configured to automatically transfer results of ophthalmic tests to a patient-associated electronic health record via a wired or non-wired connection from the harness. The platform also supports guidance of coordinate-based tests and examinations using pupillary eye tracking coordinates.
Additional module-driven mechanisms support examination coordination, including tracking pupillary eye tracking coordinates using visible light, infrared, near ultraviolet light, or narrow-band light. The platform uses pupillary eye tracking coordinates to guide coordinate-based tests and examinations for a separate interchangeable module that aligns a retinal camera using manual or automatic mechanisms. The platform supports cross-analysis of functional and anatomical data from the same angle of a patient’s eye to generate referral and further screening recommendations for a healthcare provider.
Claims Coverage
Independent claim clm-00001 provides the core coverage of the modular, head-mounted ocular screening platform and its machine-learning-based test-order optimization for preliminary diagnosis; the inventive features are centered on detachable modules, harness electronics with CPU/GPU, machine-learning training on test order and patient conditions, counterweighting via a rear battery pack, and integration outputs for preliminary diagnosis and EHR transfer.
Modular head-mounted harness with separable interchangeable modules
A harness configured to fit a head of a patient, including electronic components operable to power a plurality of interchangeable modules, wherein the plurality of interchangeable modules are separable from the screening platform and include communication capabilities to external computational devices, multiple display output devices, and input devices from both an operator and the patient.
Rear battery pack counterweight for interchangeable module mass
A battery pack mounted on a rear of the harness and configured to provide a counterweight to a mass of an interchangeable module on the head of the patient.
CPU/GPU controls module data with a machine-learning model trained on test order and patient conditions
A first CPU with a graphical processing unit (GPU), wherein the CPU or the GPU controls, displays, and processes data from the interchangeable modules by employing a machine-learning model trained with training data of how different patients performed ocular evaluations based on an order of different tests and types of interchangeable modules.
Machine-learning outputs patient-condition-based tests and module selections
The machine-learning model is further trained to receive an indication of one or more patient conditions associated with the patient and output tests and corresponding interchangeable modules of the plurality of interchangeable modules based on the indication of the one or more patient conditions.
Optimized examination order for pathology identification and preliminary diagnosis
The machine-learning model outputs an optimization of the tests and an examination order for the patient that are used to identify one or more pathologies associated with one or more ocular conditions and a preliminary diagnosis.
Across the independent claim, the inventive coverage centers on a modular, detachable head-mounted ocular screening system using harness-powered interchangeable modules, a rear battery-pack counterweight, and a CPU/GPU-driven machine-learning model that selects tests and module types based on patient conditions and optimizes examination order to identify ocular pathologies and output a preliminary diagnosis.
Stated Advantages
Reduces overwhelming torque on the patient by constraining interchangeable module volume.
Automatically transfers results of ophthalmic tests to a patient-associated electronic health record.
Provides referral and further screening recommendations for a healthcare provider via cross-analysis of functional and anatomical data from the same angle of a patient’s eye.
Documented Applications
Comprehensive ocular evaluations using interchangeable modules for ophthalmic tests and examinations, including identification of one or more pathologies associated with ocular conditions and output of a preliminary diagnosis.
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