Noisy vibrotactile signals transmitted during tactile explorations of an object provide precious information on the nature of its surface. Linking the properties of such vibrotactile signals to the way they are interpreted by the haptic sensory system remains challenging. In this study, we investigated humans' perception of noisy, stationary vibrations recorded during exploration of textures and reproduced using a vibrotactile actuator. Since intensity is a well-established essential perceptual attribute, an intensity equalization was first conducted, providing a model for its estimation. The equalized stimuli were further used to identify the most salient spectral features in a second experiment using dissimilarity estimations between pairs of vibrations. Based on dimensionally reduced spectral representations, linear models of dissimilarity prediction showed that the balance between low and high frequencies was the most important cue. Formal validation of this result was achieved through a Mushra experiment, where participants assessed the fidelity of resynthesized vibrations with various distorted frequency balances. These findings offer valuable insights into human vibrotactile perception and establish a computational framework for analyzing vibrations as humans do. Moreover, they pave the way for signal synthesis and compression based on sparse representations, holding significance for applications involving complex vibratory feedback.

翻译：在物体触觉探索过程中传输的噪声振动触觉信号为表面性质提供了宝贵信息。将此类振动触觉信号的特性与触觉感觉系统的解释方式相关联仍具挑战性。本研究探究了人类对纹理探索过程中记录并通过振动触觉致动器再现的平稳噪声振动的感知。由于强度是公认的基本感知属性，首先进行强度均衡处理，并建立了强度估计模型。在第二项实验中，利用均衡刺激，基于振动对之间的相异度估计，识别出最显著的频谱特征。基于降维后的频谱表示，相异度预测的线性模型表明，低频率与高频率之间的平衡是最关键的线索。通过Mushra实验对该结果进行了正式验证，参与者评估了具有不同频率平衡扭曲的再合成振动的保真度。这些发现为人类振动触觉感知提供了宝贵见解，并建立了人类分析振动的计算框架。此外，它们为基于稀疏表示的信号合成与压缩奠定了基础，对涉及复杂振动反馈的应用具有重要意义。