Effects of variation in system responsiveness on user performance in virtual environments

2025-07-24

AI Summary

This study investigates how system response time (SRT) variability in virtual environments affects user performance in grasp-and-place tasks, focusing on the independent and interactive effects of mean system response time (MSR) and SRT standard deviation (SDSR), while examining visual feedback frequency as a moderator of response sensitivity. A within-subjects experimental design was employed, with three controlled conditions systematically varying MSR and SDSR; task completion time, error rate, and subjective workload were measured in a high-fidelity VR environment. Results show that SDSR significantly impairs performance only when exceeding 82 ms; placement tasks exhibit greater sensitivity than grasping tasks; and tasks with higher visual feedback frequency are more vulnerable to SDSR. Based on these findings, we propose a “task feedback–driven dynamic response control strategy,” offering empirically grounded, implementable design principles for real-time performance optimization in VR interaction systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Intelligent Robots: Manipulation

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures

Abstract

System responsiveness (SR) is defined as the elapsed time until a system responds to user control. SR fluctuates over time, so it must be described statistically with mean (MSR) and standard deviation (SDSR). In this paper, we examine SR in virtual environments (VEs), outlining its components and methods of experimental measurement and manipulation. Three studies of MSR and SDSR effects on performance of grasp and placement tasks are then presented. The studies used within-subjects designs with 11, 12, and 10 participants, respectively. Results showed that SDSR affected performance only if it was above 82 ms. Placement required more frequent visual feedback and was more sensitive to SR. We infer that VE designers need not tightly control SDSR and may wish to vary SR control based on required visual feedback frequency. These results may be used to improve the human-computer interface in a wide range of interactive graphical applications, including scientific visualization, training, mental health, and entertainment.

Problem

• Examining system responsiveness impact on virtual environment tasks
• Assessing mean and deviation effects on grasp and placement performance
• Optimizing human-computer interfaces for interactive graphical applications

Innovation

• Statistical description of system responsiveness fluctuations
• Experimental measurement and manipulation in VEs
• SR control based on visual feedback frequency