Raster Scanning Can Improve Task Performance in Simulated Prosthetic Vision

IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Haozhe Zac Wang;Yan Tat Wong
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Abstract

Current challenges exist for cortical visual prostheses in presenting complex visual scenes. One of the major constraints is the number of electrodes that can be stimulated simultaneously, due to issues with electrical interaction between electrodes and the resulting complications in visual perception. To overcome this, studies have presented the outline of objects sequentially. However, this method has only been tested with simple visual stimuli, such as letters. We combined the strengths of both simultaneous and sequential presentation of phosphenes via a novel stimulation protocol named raster scanning. We tested this method using simulated prosthetic vision with a Virtual Reality headset and evaluated participants’ visual abilities over three tasks. We recorded head movement data to investigate the various strategies participants employed to explore the visual scene. We found that raster scanning could improve task accuracy and reduce response time across three tasks. Moreover, raster scanning required less head movement to complete tasks. These results suggest that raster scanning binds visual cues more efficiently than head scanning alone. Our findings underscore the importance of sequentially presenting visual information and confirm the potential of cortical visual prostheses to provide functional vision, even under the current spatial and temporal constraints.
栅格扫描可以提高模拟假肢视觉的任务性能。
目前皮质视觉假体在呈现复杂视觉场景方面存在挑战。主要的限制之一是可以同时刺激的电极数量,这是由于电极之间的电相互作用问题以及由此导致的视觉感知并发症。为了克服这一点,研究人员先后提出了物体的轮廓。然而,这种方法只在简单的视觉刺激下进行了测试,比如字母。我们通过一种名为光栅扫描的新型刺激方案结合了同时和顺序呈现光幻视的优势。我们使用虚拟现实耳机模拟假肢视觉测试了这种方法,并评估了参与者在三个任务中的视觉能力。我们记录了头部运动数据,以调查参与者在探索视觉场景时采用的各种策略。我们发现栅格扫描可以提高任务精度,缩短三个任务的响应时间。此外,栅格扫描需要较少的头部运动来完成任务。这些结果表明,光栅扫描比单独的头部扫描更有效地结合视觉线索。我们的研究结果强调了顺序呈现视觉信息的重要性,并证实了皮质视觉假体提供功能性视觉的潜力,即使在当前的空间和时间限制下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.60
自引率
8.20%
发文量
479
审稿时长
6-12 weeks
期刊介绍: Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.
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