Humans rely on their fingers to sense and interact with external environment. Understanding the tribological behavior between finger skin and object surface is crucial for various fields, including tactile perception, product appearance design, and electronic skin research. Quantitatively describing finger frictional behavior is always challenging, given the complex structure of the finger. In this study, the texture and sliding direction dependence of finger skin friction was quantified based on explicit mathematic models. The proposed double-layer model of finger skin effectively described the nonlinear elastic response of skin and predicted the scaling-law of effective elastic modulus with contact radius. Additionally, the skin friction model on textured surface considering adhesion and deformation factors was established. It revealed that adhesive term dominated finger friction behavior in daily life, and suggested that object texture size mainly influenced friction-induced vibrations rather than the average friction force. Combined with digital image correlation (DIC) technique, the effect of sliding direction on finger friction was analyzed. It was found that the anisotropy in finger friction was governed by the finger’s ratchet pawl structure, which also contributes to enhanced stick-slip vibrations in the distal sliding direction. The proposed friction models can offer valuable insights into the underlying mechanism of skin friction under various operating conditions, and can provide quantitative guidance for effectively encoding friction into haptics.

人类依靠手指来感知外部环境并与之互动。了解手指皮肤和物体表面之间的摩擦学行为对于触觉感知、产品外观设计和电子皮肤研究等各个领域都至关重要。鉴于手指的复杂结构，定量描述手指摩擦行为始终具有挑战性。在本研究中，基于显式数学模型对手指皮肤摩擦的纹理和滑动方向依赖性进行了量化。所提出的手指皮肤双层模型有效地描述了皮肤的非线性弹性响应，并预测了有效弹性模量与接触半径的标度律。此外，还建立了考虑粘附和变形因素的纹理表面表面摩擦模型。研究表明，粘性项在日常生活中主导手指摩擦行为，并表明物体纹理尺寸主要影响摩擦引起的振动，而不是平均摩擦力。结合数字图像相关（DIC）技术，分析滑动方向对手指摩擦力的影响。研究发现，手指摩擦力的各向异性是由手指的棘爪结构控制的，这也有助于增强远端滑动方向的粘滑振动。所提出的摩擦模型可以为各种操作条件下皮肤摩擦的潜在机制提供有价值的见解，并且可以为有效地将摩擦编码为触觉提供定量指导。