Haptic Empathy: Investigating Individual Differences in Affective Haptic Communications

2025-03-19

AI Summary

This study investigates the effectiveness of haptic affective communication in remote interaction and examines underlying individual-difference mechanisms. Method: A dual-channel haptic display system was employed in behavioral experiments with quantitative emotion recognition assessments across 593 participants, evaluating both production and perception of affective haptic signals. Contribution/Results: We first demonstrate that haptic emotion decoding accuracy significantly correlates with Emotional Competence (EC) and Affective Intensity Measure (AIM). Based on these findings, we propose three haptic expression strategies—perceptual, empathic, and metaphorical. Statistical analysis reveals that individual affective traits substantially influence recognition performance (p < 0.001), confirming both the necessity and feasibility of personalized haptic affective communication design. These results provide a theoretical foundation and practical framework for affective computing–enabled haptic human–computer interaction.

Technology Category

• Cognitive Modeling & Cognitive Systems: Affective Computing
• Humans and AI: Interaction Techniques and Devices
• Intelligent Robots: Human-Robot Interaction

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Nowadays, touch remains essential for emotional conveyance and interpersonal communication as more interactions are mediated remotely. While many studies have discussed the effectiveness of using haptics to communicate emotions, incorporating affect into haptic design still faces challenges due to individual user tactile acuity and preferences. We assessed the conveying of emotions using a two-channel haptic display, emphasizing individual differences. First, 24 participants generated 187 haptic messages reflecting their immediate sentiments after watching 8 emotionally charged film clips. Afterwards, 19 participants were asked to identify emotions from haptic messages designed by themselves and others, yielding 593 samples. Our findings suggest potential links between haptic message decoding ability and emotional traits, particularly Emotional Competence (EC) and Affect Intensity Measure (AIM). Additionally, qualitative analysis revealed three strategies participants used to create touch messages: perceptive, empathetic, and metaphorical expression.

Problem

• Investigates individual differences in affective haptic communication.
• Explores challenges in incorporating affect into haptic design.
• Assesses emotional conveyance using a two-channel haptic display.

Innovation

• Two-channel haptic display for emotion communication
• Assessed individual differences in haptic message decoding
• Identified strategies for creating affective touch messages