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SENS3: Multisensory Database of Finger-Surface Interactions and Corresponding Sensations

Jagan K. Balasubramanian, Bence L. Kodak, Yasemin Vardar

TL;DR

SENS3 addresses the challenge of delivering realistic touch by providing a comprehensive multisensory database of finger-surface interactions. It records visual, auditory, and tactile data from 50 surfaces explored with four exploratory procedures, alongside skin temperature and heat flux measurements, and couples these with psychophysical adjective ratings from 13 participants. The data are collected with a custom apparatus and organized through an open-access web portal to support texture rendering, user experience design, and robotic touch sensing. PCA of the adjective ratings identifies four perceptual axes—roughness, compliance, friction, and thermal cues—highlighting how multimodal cues map to human texture perception and enabling more authentic multisensory rendering.

Abstract

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.

SENS3: Multisensory Database of Finger-Surface Interactions and Corresponding Sensations

TL;DR

SENS3 addresses the challenge of delivering realistic touch by providing a comprehensive multisensory database of finger-surface interactions. It records visual, auditory, and tactile data from 50 surfaces explored with four exploratory procedures, alongside skin temperature and heat flux measurements, and couples these with psychophysical adjective ratings from 13 participants. The data are collected with a custom apparatus and organized through an open-access web portal to support texture rendering, user experience design, and robotic touch sensing. PCA of the adjective ratings identifies four perceptual axes—roughness, compliance, friction, and thermal cues—highlighting how multimodal cues map to human texture perception and enabling more authentic multisensory rendering.

Abstract

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.
Paper Structure (9 sections, 3 figures, 3 tables)

This paper contains 9 sections, 3 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Existing Haptic Texture Databases
  3. SENS3 Database
  4. Selected surfaces & data collection apparatus
  5. Data collection apparatus
  6. Data collection procedure
  7. Collected data
  8. Results of the perceptual experiments
  9. Discussion

Figures (3)

  • Figure 1: Recorded surfaces in https://www.sens3.netSENS3 database. The material categories are color-coded; each category's surface count is indicated in the brackets.
  • Figure 2: Data recording apparatus: 1. Cameras, 2. data acquisition board, 3. heat flux sensor, 4. microphone, 5. linear stage, 6. position sensor, 7. armrest, 8. force sensor, 9. accelerometer, 10. selection of surfaces.
  • Figure 3: Example recordings from two participants while interacting with two different surfaces: metal and foam. The sliding data comprises only a 5-second segment from the complete recording for a clear visualization. The dashed lines on the sliding plots highlight one [0.2-0.4 N, 0-33 mm/s] force-speed pair region for each of the measurements. The adjective ratings are normalized based on the maximum and minimum value reported by the participant across all surfaces.