The growing demand for natural interactions with technology underscores the importance of achieving realistic touch sensations in digital environments. Realizing this goal highly depends on comprehensive databases of finger-surface interactions, which need further development. Here, we present SENS3—www.sens3.net—an extensive open-access repository of multisensory data acquired from fifty surfaces when two participants explored them with their fingertips through static contact, pressing, tapping, and sliding. SENS3 encompasses high-fidelity visual, audio, and haptic information recorded during these interactions, including videos, sounds, contact forces, torques, positions, accelerations, skin temperature, heat flux, and surface photographs. Additionally, it incorporates thirteen participants’ psychophysical sensation ratings (rough–smooth, flat–bumpy, sticky–slippery, hot–cold, regular–irregular, fine–coarse, hard–soft, and wet–dry) while exploring these surfaces freely. Designed with an open-ended framework, SENS3 has the potential to be expanded with additional textures and participants. We anticipate that SENS3 will be valuable for advancing multisensory texture rendering, user experience development, and touch sensing in robotics.@en

The ever-emerging mobile market induced a blooming interest in stylus-based interactions. Most state-of-the-art styluses either provide no haptic feedback or only deliver one type of sensation, such as vibration or skin stretch. Improving these devices with display abilities of a palette of tactile feels can pave the way for rendering realistic surface sensations, resulting in more natural virtual experiences. However, integrating necessary actuators and sensors while keeping the compact form factor of a stylus for comfortable user interactions challenges their design. This situation also limits the scientific knowledge of relevant parameters for rendering compelling artificial textures for stylus-based interactions. To address these challenges, we developed FeelPen, a haptic stylus that can display multimodal texture properties (compliance, roughness, friction, and temperature) on touchscreens. We validated the texture rendering capability of our design by conducting system identification and psychophysical experiments. The experimental results confirmed that FeelPen could render a variety of modalities with wide parameter ranges necessary to create perceptually salient texture feels, making it a one-of-a-kind stylus. Our unique design and experimental results pave the way for new perspectives with stylus-based interactions on future touchscreens.

@en