Auditory, haptic, and visual stimuli provide alerts, notifications, and information for a wide variety of applications ranging from virtual reality to wearable and hand-held devices. Response times to these stimuli have been used to assess motor control and design human-computer interaction systems. In this study, we investigate human response times to 26 combinations of auditory, haptic, and visual stimuli at three levels (high, low, and off). We developed an iOS app that presents these stimuli in random intervals and records response times on an iPhone 11. We conducted a user study with 20 participants and found that response time decreased with more types and higher levels of stimuli. The low visual condition had the slowest mean response time (mean +/- standard deviation, 528 +/- 105 ms) and the condition with high levels of audio, haptic, and visual stimuli had the fastest mean response time (320 +/- 43 ms). This work quantifies response times to multi-modal stimuli, identifies interactions between different stimuli types and levels, and introduces an app-based method that can be widely distributed to measure response time. Understanding preferences and response times for stimuli can provide insight into designing devices for human-machine interaction.

翻译：听觉、触觉和视觉刺激为从虚拟现实到可穿戴及手持设备等广泛的应用场景提供警报、通知与信息。这些刺激的反应时间已被用于评估运动控制及设计人机交互系统。本研究针对低、高、关闭三个层级下26种听觉、触觉与视觉刺激组合，探究人类的反应时间。我们开发了一款iOS应用程序，以随机间隔呈现这些刺激，并在iPhone 11上记录反应时间。通过20名参与者的用户实验发现：刺激类型越多、层级越高，反应时间越短。低视觉条件下的平均反应时间最慢（均值±标准差，528±105毫秒），而高音频、触觉与视觉刺激组合条件下的平均反应时间最快（320±43毫秒）。本工作量化了多模态刺激的反应时间，揭示了不同刺激类型与层级间的交互作用，并提出了一种可广泛部署的基于应用程序的反应时间测量方法。理解刺激偏好与反应时间，可为设计人机交互设备提供参考依据。