Towards a Smart Bionic Eye: AI-Powered Artificial Vision for the Treatment of Incurable Blindness

迈向智能仿生眼：人工智能驱动的人工视觉治疗不可治愈的失明

• 批准号: 10473346
• 负责人: Michael Beyeler
• 金额: $ 125.01万
• 依托单位: UNIVERSITY OF CALIFORNIA SANTA BARBARA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-19 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10473346
• 关键词: Address; Adopted; Affect; Artificial Intelligence; Bionics; Blindness; Brain; Code; Development; Devices; Electric Stimulation; Electrodes; Eye; Face; Genes; Goals; Human; Neurosciences; Ocular Prosthesis; Optic Nerve; Perception; Persons; Photic Stimulation; Quality of life; Self Care; Shapes; System; Technology; Thinking; Translating; Vision; Visual; Visual Aid; Visual impairment; Visual system structure; Visually Impaired Persons; Work; base; blind; computational neuroscience; computer human interaction; computer science; data-driven model; effective therapy; improved; insight; neural stimulation; neuroprosthesis; next generation; prototype; retinal damage; retinal stimulation; sensory substitution; stem cell therapy

Towards a Smart Bionic Eye: AI-Powered Artificial Vision for the Treatment of Incurable Blindness How can we return a functional form of sight to people who are living with incurable blindness? Despite recent advances in gene and stem cell therapies are showing great promise, there are no effective treatments for many people blinded by severe degeneration or damage to the retina, the optic nerve, or cortex. In such cases, an electronic visual prosthesis (“bionic eye”) may be the only option. However, the quality of current prosthetic vision is still rudimentary and does not differ much across different device technologies. A major outstanding challenge is translating electrode stimulation into a code that the brain can understand. Rather than aiming to one day restore natural vision with visual prostheses, we might be better off thinking about how to create practical and useful artificial vision. Specifically, a visual prosthesis has the potential to provide visual augmentations through the means of artificial intelligence (AI) based scene understanding, tailored to specific real-world tasks that are known to affect the quality of life of people who are blind (e.g., face recognition, outdoor navigation, self-care). The goal of this proposal is thus to address fundamental questions at the intersection of neuroscience, computer science, and human-computer interaction that will enable the development of a Smart Bionic Eye; that is, a visual neuroprosthesis that functions as an AI-powered visual aid by providing visual augmentations to support specific everyday tasks. To enable such a technology, we first need to 1) understand how visual prostheses interact with the human visual system to shape perception, 2) identify visual augmentation strategies that best support specific real-world tasks, and 3) develop a prototyping system that allows us to validate as well as iteratively improve upon our augmentation strategies with the bionic eye recipient in the loop. This work will further our understanding of how brain stimulation leads to perception, and the insights gained from identifying optimal visual augmentation strategies may be broadly applicable to different visual aids and sensory substitution devices, therefore potentially benefitting both people who are blind and people with low vision. Last but not least, the ability of a visual prosthesis to support everyday tasks might make the difference between abandoned technology and a widely adopted next-generation neuroprosthetic device.

迈向智能仿生眼：人工智能助力治疗不治之盲 我们如何才能让患有无法治愈的失明的人重拾功能性视力呢？尽管最近 基因和干细胞疗法的进展显示出巨大的希望，许多人还没有有效的治疗方法。 因视网膜、视神经或皮质严重退化或损伤而失明的人。在这种情况下，一个 电子视觉假体(“仿生眼”)可能是唯一的选择。然而，目前假眼的质量 仍然是初级的，在不同的设备技术之间没有太大差异。一项突出的重大挑战 将电极刺激转换成大脑可以理解的代码。与其把目标定在某一天 用视觉假体恢复自然视力，我们可能会更好地思考如何创造实用和 有用的人工视觉。具体地，视觉假体具有通过以下方式提供视觉增强的潜力 基于人工智能(AI)的场景理解方法，为特定的真实世界任务量身定做， 已知会影响盲人的生活质量(例如，人脸识别、户外导航、自我护理)。 因此，这项提案的目标是解决神经科学、计算机 科学和人机交互将使智能仿生眼的开发成为可能；也就是，视觉 通过提供视觉增强功能来支持特定功能的神经假体，其功能是人工智能支持的视觉辅助 每天的任务。要实现这样的技术，我们首先需要1)了解视觉假体是如何与 人类视觉系统来塑造知觉，2)识别最能支持特定 真实世界的任务，以及3)开发一个原型系统，它允许我们验证和迭代改进 根据我们的增强策略，仿生眼接收器处于循环中。 这项工作将进一步加深我们对大脑刺激如何导致知觉的理解，以及所获得的见解 从识别最佳视觉增强策略可以广泛地适用于不同的视觉辅助和 感官替代装置，因此对盲人和低视力者都有潜在的好处 幻象。最后但并非最不重要的是，视觉假体支持日常任务的能力可能会有所不同 在废弃的技术和被广泛采用的下一代神经假体设备之间。