Measuring motion-to-photon latency for sensorimotor experiments with virtual reality systems.

Area of Science:

• Human-Computer Interaction
• Virtual Reality Systems
• Sensorimotor Research

Background:

• Consumer virtual reality (VR) systems are increasingly used in scientific research for studying sensorimotor behaviors.
• Accurate measurement of system properties, particularly motion-to-photon latency, is essential for reliable VR research.
• Existing methods for latency measurement are often system-specific and do not account for motion prediction algorithms.

Purpose of the Study:

• To develop a novel, system-independent method for measuring motion-to-photon latency in VR systems.
• To assess how motion prediction algorithms affect latency during user movements.
• To evaluate the latency of popular VR headsets (HTC Vive, Oculus Rift, Oculus Rift S, Valve Index).

Main Methods:

• Developed a high-speed camera-based technique to co-register real-world and virtual controller movements.
• Applied the technique to measure motion-to-photon latency across different VR headsets using Unity and SteamVR.
• Analyzed how latency changes dynamically throughout a movement, including the effect of motion prediction.

Main Results:

• Initial mean latencies for sudden movements ranged from 21 to 42 ms across tested headsets.
• Motion prediction effectively reduced latency to 2-13 ms within approximately 25-58 ms of movement onset.
• Sudden accelerations were found to increase latency and decrease spatial accuracy.

Conclusions:

• The novel camera-based technique provides a reliable, system-independent way to measure VR motion-to-photon latency.
• Understanding the impact of motion prediction on latency is critical for sensorimotor research in VR.
• Researchers can use this method to validate VR systems and optimize experimental designs for improved data accuracy.