Distance Filtering System for Retinal Implants

视网膜植入物距离过滤系统

基本信息

项目摘要

 DESCRIPTION (provided by applicant): We propose to develop and evaluate the utility of a novel input camera system for retinal prosthetics that allows users to filter optical imagery based on distance from the observer. We call this "depth filtering", which can be accomplished with a depth sensing stereoscopic camera system. Retinal prostheses can restore partial vision to people blinded by outer retinal degenerative diseases such as Retinitis Pigmentosa (RP) or Macular Degeneration. The Argus II Retinal Prosthesis System is intended to provide electrical stimulation of the retina to elicit visual perception in blind individuals with (near) total visionloss due to retinitis pigmentosa. The implanted epiretinal array provides a 10 x 6 grid of electrodes. Electrical pulses at these 60 pixel sites stimulate the retina's remaining cells and result in the perception of patterns of light. The current spatial resolution is only 60 total pixels, but the camera systems that provide image information to the prosthesis user transmit full-resolution video information. Information in the imagery consists of all visible items within the field of vie ranging for example from nearby obstacles to far away mountain scenery. The lack of perceived spatial resolution makes it extremely difficult for prosthesis users to differentiate between important nearby elements within the scene and relatively unimportant distant elements of the scenery, or vice versa. An image capture and processing system is proposed that selectively removes elements in a viewed scene that are outside a user-set depth range. We hypothesize that system utility in important tasks such as people or object finding and mobility will be less burden some, and performance improved, by providing only relevant visual information to the wearer. The proposed project seeks to develop and experiment with distance-filtered optical imagery as an input modality to retinal implants. Two prototype systems will be specified, designed, built and evaluated in Argus II patients: In phase 1 of the proposed project the image processing will be performed by a computer external to the Argus II system. In phase 2, a more powerful version of the next-generation Argus II video processing unit, capable of performing the image processing, will be utilized. This will be coupled with a new dual camera eyeglass assembly, making the phase 2 prototype fully integrated and ready for commercialization in the next generation Argus II system, and possibly in other visual prosthesis systems and head-mounted electronic low vision aids.
 描述(由申请人提供):我们提出开发和评估用于视网膜修复术的新型输入相机系统的实用性,该系统允许用户过滤基于光学图像的图像。 与观察者的距离。我们称之为“深度滤波”,这可以用深度感测立体相机系统来完成。视网膜假体可以恢复因视网膜色素变性(RP)或黄斑变性等外部视网膜退行性疾病而失明的人的部分视力。Argus II视网膜假体系统预期用于提供视网膜电刺激,以激发因视网膜色素变性导致(接近)完全视力丧失的盲人的视觉感知。植入的视网膜前阵列提供10 × 6的电极网格。在这60个像素点的电脉冲刺激视网膜的剩余细胞,并导致光模式的感知。目前的空间分辨率只有60个像素,但是向假肢用户提供图像信息的摄像机系统传输全分辨率视频信息。图像中的信息包括视野内的所有可见项目,例如从附近的障碍物到远处的山景。感知空间分辨率的缺乏使得假肢用户很难区分场景中重要的附近元素和相对不重要的远处元素,反之亦然。提出了一种图像捕获和处理系统,其选择性地移除所观看的场景中在用户设置的深度范围之外的元素。我们假设,在重要的任务,如人或物体的发现和流动性的系统效用将减少一些负担,性能提高,只提供相关的视觉信息的佩戴者。拟议的项目旨在开发和实验的距离过滤的光学图像作为输入方式的视网膜植入。将在Argus II患者中指定、设计、构建和评价两个原型系统:在拟定项目的第1阶段,图像处理将由Argus II系统外部的计算机执行。在第二阶段,将使用功能更强大的下一代Argus II视频处理单元,能够执行图像处理。这将与一个新的双摄像头的双摄像头组件相结合,使第二阶段的原型完全集成,并准备在下一代Argus II系统,并可能在其他视觉假体系统和头戴式电子低视力辅助器的商业化。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Gislin Dagnelie其他文献

Gislin Dagnelie的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Gislin Dagnelie', 18)}}的其他基金

Distance Filtering System for Retinal Implants
视网膜植入物距离过滤系统
  • 批准号:
    8905641
  • 财政年份:
    2015
  • 资助金额:
    $ 99.08万
  • 项目类别:
Develop and Validate a Prosthetic Low Vision Rehabilitation (PLoVR) Curriculum
开发并验证假肢低视力康复 (PLoVR) 课程
  • 批准号:
    8435523
  • 财政年份:
    2011
  • 资助金额:
    $ 99.08万
  • 项目类别:
Develop and Validate a Prosthetic Low Vision Rehabilitation (PLoVR) Curriculum
开发并验证假肢低视力康复 (PLoVR) 课程
  • 批准号:
    8209150
  • 财政年份:
    2011
  • 资助金额:
    $ 99.08万
  • 项目类别:
Develop and Validate a Prosthetic Low Vision Rehabilitation (PLoVR) Curriculum
开发并验证假肢低视力康复 (PLoVR) 课程
  • 批准号:
    8334708
  • 财政年份:
    2011
  • 资助金额:
    $ 99.08万
  • 项目类别:
Develop and Validate a Prosthetic Low Vision Rehabilitation (PLoVR) Curriculum
开发并验证假肢低视力康复 (PLoVR) 课程
  • 批准号:
    8812848
  • 财政年份:
    2011
  • 资助金额:
    $ 99.08万
  • 项目类别:
Survey and Test Platform for Use in Underserved Populations
用于服务不足人群的调查和测试平台
  • 批准号:
    8201880
  • 财政年份:
    2011
  • 资助金额:
    $ 99.08万
  • 项目类别:
Survey and Test Platform for Use in Underserved Populations
用于服务不足人群的调查和测试平台
  • 批准号:
    8327703
  • 财政年份:
    2011
  • 资助金额:
    $ 99.08万
  • 项目类别:
Develop and Validate a Prosthetic Low Vision Rehabilitation (PLoVR) Curriculum
开发并验证假肢低视力康复 (PLoVR) 课程
  • 批准号:
    8714236
  • 财政年份:
    2011
  • 资助金额:
    $ 99.08万
  • 项目类别:
Develop and Validate a Prosthetic Low Vision Rehabilitation (PLoVR) Curriculum
开发并验证假肢低视力康复 (PLoVR) 课程
  • 批准号:
    8601700
  • 财政年份:
    2011
  • 资助金额:
    $ 99.08万
  • 项目类别:
Develop and Validate a Prosthetic Low Vision Rehabilitation (PLoVR) Curriculum
开发并验证假肢低视力康复 (PLoVR) 课程
  • 批准号:
    8024133
  • 财政年份:
    2011
  • 资助金额:
    $ 99.08万
  • 项目类别:

相似海外基金

DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 99.08万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了