Improving Texture Discrimination in Virtual Tasks by using Stochastic Resonance

Sandeep Zechariah George, H. Khosravi, Ryan M Peters, L. Oehlberg, Sonny Chan
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Abstract

We investigate enhancing virtual haptic experiences by applying Stochastic Resonance or SR noise to the user's hands. Specifically, we focus on improving users' ability to discriminate between virtual textures modelled from nine grits of real sandpaper in a virtual texture discrimination task. We applied mechanical SR noise to the participant's skin by attaching five flat actuators to different points on their hand. By fastening a linear voice-coil actuator and a 6-DOF haptic device to participants' index finger, we enabled them to interact and feel virtual sandpapers while inducing different levels of SR noise. We hypothesize that SR will improve their discrimination performance.
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基于随机共振的虚拟任务纹理识别方法
我们研究通过将随机共振或SR噪声应用于用户的手来增强虚拟触觉体验。具体来说,我们专注于在虚拟纹理识别任务中提高用户区分由真实砂纸的九个磨粒建模的虚拟纹理的能力。我们通过将五个平面致动器连接到参与者手上的不同点,将机械SR噪声应用于参与者的皮肤。通过将线性音圈致动器和6自由度触觉装置固定在参与者的食指上,我们使他们能够在产生不同程度的SR噪声的同时进行交互并感受到虚拟砂纸。我们假设SR会提高他们的辨别能力。
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