TY - GEN
T1 - Haptic Empathy
T2 - 2025 CHI Conference on Human Factors in Computing Systems, CHI 2025
AU - Ju, Yulan
AU - Meng, Xiaru
AU - Taguchi, Harunobu
AU - Gunasekaran, Tamil Selvan
AU - Hoppe, Matthias
AU - Ishikawa, Hironori
AU - Tanaka, Yoshihiro
AU - Pai, Yun Suen
AU - Minamizawa, Kouta
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2025/4/26
Y1 - 2025/4/26
N2 - 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.
AB - 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.
KW - affective computing
KW - emotion encoding
KW - emotion expression
KW - emotion recognition
KW - haptic interfaces
KW - vibration
UR - https://www.scopus.com/pages/publications/105005763209
UR - https://www.scopus.com/inward/citedby.url?scp=105005763209&partnerID=8YFLogxK
U2 - 10.1145/3706598.3714139
DO - 10.1145/3706598.3714139
M3 - Conference contribution
AN - SCOPUS:105005763209
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2025 - Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 26 April 2025 through 1 May 2025
ER -