IEEE Trans Haptics. 2022 Apr-Jun;15(2):429-440. doi: 10.1109/TOH.2021.3130091. Epub 2022 Jun 27.
We used broadband electroadhesion to reproduce the friction force profile measured as a finger slid across a textured surface. In doing so, we were also able to reproduce with high fidelity the skin vibrations characteristic of that texture; however, we found that this did not reproduce the original perception. To begin, the reproduction felt weak. In order to maximize perceptual similarity between a real texture and its friction force playback, the vibratory magnitude of the latter must be scaled up on average ≈ 3X for fine texture and ≈ 5X for coarse texture samples. This additional gain appears to correlate with perceived texture roughness. Additionally, even with optimal scaling and high fidelity playback, subjects could identify which of two reproductions corresponds to a real texture with only 71 % accuracy, as compared to 95 % accuracy when using real texture alternatives. We conclude that while tribometry and vibrometry data can be useful for texture classification, they appear to contribute only partially to texture perception. We propose that spatially distributed excitation of skin within the fingerpad may play an additional key role, and may thus be able to contribute to high fidelity texture reproduction.
我们使用宽带电粘性来复制手指在纹理表面上滑动时测量的摩擦力曲线。在这样做的过程中，我们还能够高度逼真地复制出具有该纹理特征的皮肤振动；然而，我们发现这并没有复制出原始的感知。首先，这种复制感觉很微弱。为了使真实纹理与其摩擦力重放之间的感知相似性最大化，后者的振动幅度必须平均放大 ≈ 3 倍用于精细纹理，和 ≈ 5 倍用于粗糙纹理样本。这种额外的增益似乎与感知纹理粗糙度相关。此外，即使进行了最佳的缩放和高保真播放，与使用真实纹理替代物时的 95%准确率相比，受试者只能以 71%的准确率识别出两个复制品中哪一个对应于真实纹理。我们的结论是，尽管摩擦测量和振动测量数据可用于纹理分类，但它们似乎仅部分有助于纹理感知。我们提出，手指垫内皮肤的空间分布激励可能发挥额外的关键作用，因此可能能够有助于实现高保真的纹理复制。
