XRAE: Extended Reality Acuity Examination

Research and real world use cases have shown that extended reality (XR) can provide immense benefits to a wide range of applications both in the commercial, private, and government sectors. XR has been shown to increase accuracy, decrease errors, and improve training in a variety of applications. Many of these XR implementations include text based user interfaces (UI) to instruct or present data to a user. However, text readability is a major limitation in these XR environments due to a variety of factors including device resolution, vergence accommodation conflict (VAC), and user visual acuity. This paper presents the Extended Reality Acuity Examination (XRAE) application as a comprehensive solution to generate text optimized for an XR environment, its user, and the associated XR hardware. A two-step approach was developed and studied. Step one was the creation of a virtual Snellen Chart with options to customize different text characteristics. The Snellen Chart has been widely used by optometrists as a quick and effective means to judge a user’s visual acuity. A user simply selects the text they can read clearly and comfortably from several options presented. Step two was the real-time generation of a user-specific text (i.e., size, font, and other characteristics) and distribution to all UI elements. The net result of XRAE is text-based UI elements customized to a user and associated XR environment that can be easily implemented in a wide range of use cases.