Recently, the General Offices of six ministries, including the Ministry of Industry and Information Technology, officially released the 2025 typical cases of digital products and services tailored for the elderly and people with disabilities. The project led by Professor Fu Xianping’s team from our university, titled “Accelerating the Clinical Application of Optical Aid Devices Using AI+VR Technologies to Enhance Visual Perception for Individuals with Visual Field Defects,” was selected as a featured case in the “Innovative Technologies for the Elderly and People with Disabilities” category. This recognition highlights our university’s innovative strength and application expertise in the interdisciplinary field of artificial intelligence, virtual reality, and visual health.

The project focuses on critical bottlenecks in optical visual field assistance, such as poor imaging quality, challenging field-of-view adaptation, low evaluation efficiency, and weak visual training. Through international collaborative research with Harvard Medical School centered on the workflow of “assistive imaging – device manufacturing – adaptation – training,” the project has overcome core technical challenges, including multi-module cascaded optical field assistance imaging, the preparation of personalized optical field assistive devices, intelligent field-of-view expansion performance adaptation and evaluation, and multimodal field expansion virtual reality (VR) training. These breakthroughs have enabled the industrial-scale manufacturing and intelligent adaptive training of optical visual field assistive devices. The research team developed a cascaded prism vision aid and an intelligent adaptation and training platform which significantly enhance the visual perception of individuals with visual field defects. These research outcomes have been applied in multi-center clinical settings at several prestigious institutions, including Shenzhen Eye Hospital, the Eye Hospital of Wenzhou Medical University, the First Affiliated Hospital of Sun Yat-sen University, the Second Affiliated Hospital of Fujian Medical University, and Henan Provincial Eye Hospital. These achievements will accelerate the R&D and production of innovative optical visual field assistive products, further strengthening the supply capacity for high-end, high-quality rehabilitation assistive devices.

The cascaded prism visual aid is designed to meet the visual-assistance imaging needs of individuals with visual field defects. It employs a dual-reflection optical design and a multi-module cascaded optical architecture, overcoming the expansion limit of conventional optical aids (approximately 57 prism diopters) and enabling high-power prism extension and high-clarity optical visual-field expansion up to 100 prism diopters. In addition, to address the challenges associated with the precision assembly of optical assistive devices, the system incorporates modular manufacturing of prism elements and additive manufacturing of prism mounting components. These components are engineered to conform to high-precision three-dimensional ocular models, meeting the tight tolerances required for visual-field expansion devices. As a result, the cascaded prism visual aid can support personalized and stage-specific visual-field expansion solutions for individuals with visual field defects.

The accompanying intelligent adaptive visual training platform utilizes ultra-high-definition real-time scene rendering across the entire visual field to conduct graded walking training in virtual scenarios using cascaded prism visual aids. This enables progressive visual field expansion for individuals with visual field defects while capturing multi-modal interaction data from virtual scenarios in real time. The system automatically quantifies and evaluates the ability for directed walking following visual field expansion, thereby enhancing the visual cognitive performance of visual field expansion aids. Concurrently, by collecting data on the characteristics of individuals with visual field defects, the platform generates virtual patient. Using pre-trained general-purpose large models, it conducts multi-dimensional, comprehensive walking collision simulations and visual field expansion simulations within virtual reality environments. This enables the quantitative analysis of potential collision risks, providing references for virtual simulation validation in visual behavior training and visual aid fitting.

The research team has been collaborating with Harvard Medical School of the United States since 2008 on research into low vision enhancement and visual training. Supported by the Base for Introduction of International Talents in Visual Aid Technology and Equipment at Dalian Maritime University, and guided by the concept of active health, the team has focused on visual perception in the elderly and people with visual field defects. It has been engaged in the research and development of key technologies, including optical visual aid imaging, precise fitting of assistive devices, intelligent visual training, and adaptation assessment. The research team will continue technological research and innovation to advance the field of visual rehabilitation, assist people with visual field defects in better integrating into society, and provide visual rehabilitation services for the growing population of the elderly and those with visual field defects.

This research has been supported by the Key Special Project for Intergovernmental International Science, Technology and Innovation Cooperation under the National Key Research and Development Program of China; the National Natural Science Foundation of China; the China Postdoctoral Science Foundation; research grants from the China Disabled Persons’ Federation; and the Joint Program of the Liaoning Provincial Science and Technology Plan, among others.