Effective Throughput Analysis of Different Task Execution Strategies for Mid-Air Fitts' Tasks in Virtual Reality

作     者：Batmaz, Anil Ufuk Stuerzlinger, Wolfgang 

作者机构：Concordia Univ Comp Sci Dept Montreal PQ Canada Simon Fraser Univ Sch Interact Arts & Amp Technol Burnaby BC Canada 

出 版 物：《IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS》 (IEEE Trans Visual Comput Graphics)

年 卷 期：2022年第28卷第11期

页      面：3939-3947页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0835[工学-软件工程] 

主　　题：Fitts' task Virtual Reality Effective Throughput Speed-Accuracy Trade-off 

摘      要：Fitts law and throughput based on effective measures are two mathematical models frequently used to analyze human motor performance in a standardized pointing task, e.g., to compare the performance of input and output devices. Even though pointing has been deeply studied in 2D, it is not well understood how different task execution strategies affect throughput in pointing in 3D virtual environments. In this work, we examine the effective throughput measure, claimed to be invariant to task execution strategies, in Virtual Reality (VR) systems with three such strategies, as fast, as precise, and as fast and as precise as possible for ray casting and virtual hand interaction, by re-analyzing data from a 3D pointing IS0 9241-411 study. Results show that effective throughput is not invariant for different task execution strategies in VR, which also matches a more recent 2D result. Normalized speed vs. accuracy curves also did not fit the data. We thus suggest that practitioners, developers, and researchers who use MacKenzie s effective throughput formulation should consider our findings when analyzing 3D user pointing performance in VR systems.