Zapf Marc P, Matteucci Paul B, Lovell Nigel H, Zheng Steven, Suaning Gregg J
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:2597-600. doi: 10.1109/EMBC.2014.6944154.
Simulated prosthetic vision (SPV) in normally sighted subjects is an established way of investigating the prospective efficacy of visual prosthesis designs in visually guided tasks such as mobility. To perform meaningful SPV mobility studies in computer-based environments, a credible representation of both the virtual scene to navigate and the experienced artificial vision has to be established. It is therefore prudent to make optimal use of existing hardware and software solutions when establishing a testing framework. The authors aimed at improving the realism and immersion of SPV by integrating state-of-the-art yet low-cost consumer technology. The feasibility of body motion tracking to control movement in photo-realistic virtual environments was evaluated in a pilot study. Five subjects were recruited and performed an obstacle avoidance and wayfinding task using either keyboard and mouse, gamepad or Kinect motion tracking. Walking speed and collisions were analyzed as basic measures for task performance. Kinect motion tracking resulted in lower performance as compared to classical input methods, yet results were more uniform across vision conditions. The chosen framework was successfully applied in a basic virtual task and is suited to realistically simulate real-world scenes under SPV in mobility research. Classical input peripherals remain a feasible and effective way of controlling the virtual movement. Motion tracking, despite its limitations and early state of implementation, is intuitive and can eliminate between-subject differences due to familiarity to established input methods.
在视力正常的受试者中模拟假体视觉(SPV)是一种既定的方法,用于研究视觉假体设计在诸如移动性等视觉引导任务中的预期效果。为了在基于计算机的环境中进行有意义的SPV移动性研究,必须建立虚拟场景导航和体验到的人工视觉的可信表示。因此,在建立测试框架时,明智的做法是充分利用现有的硬件和软件解决方案。作者旨在通过集成最先进但低成本的消费技术来提高SPV的真实感和沉浸感。在一项初步研究中评估了身体运动跟踪在逼真的虚拟环境中控制运动的可行性。招募了五名受试者,他们使用键盘和鼠标、游戏手柄或Kinect运动跟踪执行避障和寻路任务。分析步行速度和碰撞作为任务性能的基本指标。与传统输入方法相比,Kinect运动跟踪导致性能较低,但结果在不同视觉条件下更均匀。所选择的框架已成功应用于一项基本虚拟任务,适用于在移动性研究中在SPV下逼真地模拟现实世界场景。传统输入外设仍然是控制虚拟运动的可行且有效的方法。运动跟踪尽管有其局限性且处于早期实施阶段,但直观且可以消除因熟悉既定输入方法而导致的受试者间差异。