Heart Rate and Facial Expression Data Influence the Ease of Communication in a Remote Work Set-Up
Remote communication is challenging compared with face-to-face communication because of the limited social cues. Computer systems built to address this problem could enable individuals to share facial expressions, which are available in face-to-face communication, or biosignals such as heart rate. Currently, many people are unfamiliar with the advantages of sharing such signals online, and clarification of the associated benefits is necessary. To compare the effects of heart rate and facial expression data on the ease of communication, we exposed 20 pairs of participants to a remote work simulation. In this experiment, one participant made contact with their remote partner on the basis of heart rate or facial expression data. Although participants evaluated the heart rate and facial expression data as being similarly useful on average, we found the following differences. Recipients of the contact evaluated the heart rate data as more effective, likely because the recipient's status was more accurately discriminated by the sender. Senders evaluated the facial expression data as more effective, likely because the many parameters were easily interpreted and quickly updated. Thus, heart rate and facial expression data may increase the ease of remote communication, particularly for the recipient and the sender, respectively.
Authors
- Kazunori Iwata (ORCID: https://orcid.org/0000-0002-2638-7288)
- Aki Kimura
- Katsuaki Kojima (ORCID: https://orcid.org/0000-0003-4157-6682)
- Wataru Sasaki (ORCID: https://orcid.org/0000-0003-1126-9569)
- Kazushi Mimura (ORCID: https://orcid.org/0000-0002-0763-4925)
- Takeaki Shimokawa (ORCID: https://orcid.org/0009-0006-4440-2070)
- Kensuke Ueda
- Yuna Takamori
Institutions
- Mitsubishi Electric (Japan) (JP)
- Hiroshima City University (JP)
Publication Details
- Journal
- IEEE Transactions on Affective Computing
- Published
- 2025-06-30
- DOI
- https://doi.org/10.1109/taffc.2025.3584315
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00