Data-driven sparse skin stimulation can convey social touch information to humans

TL;DR

This study demonstrates that sparse, data-driven skin stimulation can effectively convey social touch signals to humans, enabling remote social interaction with minimal hardware complexity.

Contribution

The paper introduces a novel approach using a soft wearable sensor array and an algorithm to transmit social touch cues through sparse haptic signals.

Findings

Users can distinguish social meanings from sparse haptic signals

The system performs comparably to direct human touch in conveying social cues

Low-resolution, low-force device effectively communicates social touch

Abstract

During social interactions, people use auditory, visual, and haptic cues to convey their thoughts, emotions, and intentions. Due to weight, energy, and other hardware constraints, it is difficult to create devices that completely capture the complexity of human touch. Here we explore whether a sparse representation of human touch is sufficient to convey social touch signals. To test this we collected a dataset of social touch interactions using a soft wearable pressure sensor array, developed an algorithm to map recorded data to an array of actuators, then applied our algorithm to create signals that drive an array of normal indentation actuators placed on the arm. Using this wearable, low-resolution, low-force device, we find that users are able to distinguish the intended social meaning, and compare performance to results based on direct human touch. As online communication becomes more prevalent, such systems to convey haptic signals could allow for improved distant socializing and empathetic remote human-human interaction.