Cyberoception: Finding A Painlessly-Measurable New Sense In The Cyberworld Towards Emotion-awareness In Computing
Tadashi Okoshi, Zexiong Gao, Yi Zhen Tan, Takumi Karasawa, Takeshi Miki, Wataru Sasaki, Rajesh Krishna Balan
Abstract
In Affective computing, recognizing users' emotions accurately is the basis of affective human-computer interaction. Understanding users' interoception contributes to a better understanding of individually different emotional abilities, which is essential for achieving inter-individually accurate emotion estimation. However, existing interoception measurement methods, such as the heart rate discrimination task, have several limitations, including their dependence on a well-controlled laboratory environment and precision apparatus, making monitoring users' interoception challenging. This study aims to determine other forms of data that can explain users' interoceptive or similar states in their real-world lives and propose a novel hypothetical concept "cyberoception," a new sense (1) which has properties similar to interoception in terms of the correlation with other emotion-related abilities, and (2) which can be measured only by the sensors embedded inside commodity smartphone devices in users' daily lives. Results from a 10-day-long in-lab/in-the-wild hybrid experiment reveal a specific cyberoception type "Turn On" (users' subjective sensory perception about the frequency of turning-on behavior on their smartphones), significantly related to participants' emotional valence. We anticipate that cyberoception to serve as a fundamental building block for developing more "emotion-aware", user-friendly applications and services.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Builds on1
Related papers
- Exploring the Emotional Effects of Enhanced Interoception via Heartbeat-Synchronized Haptic FeedbackMinsol Michelle Kim, Nathan W. Whitmore, Phoebe Chua, Serena Pei et al.UbiComp 2026 · 1 citation
- Technical Design Space Analysis for Unobtrusive Driver Emotion Assessment Using Multi-Domain ContextDavid Bethge, Luis Falconeri Coelho, Thomas Kosch, Satiyabooshan Murugaboopathy et al.UbiComp 2023 · 16 citations
- Inward VR: Toward a Qualitative Method for Investigating Interoceptive Awareness in VRAlexander C. Haley, Don Thorpe, Alex Pelletier, Svetlana Yarosh et al.IEEE VR 2023 · 11 citations
- Interoceptive Interaction: An Embodied Metaphor Inspired Approach to Designing for MeditationClaudia Daudén Roquet, Corina SasCHI 2021 · 55 citations
- Affective State Prediction from Smartphone Touch and Sensor Data in the WildRafael Wampfler, Severin Klingler, Barbara Solenthaler, Victor R. Schinazi et al.CHI 2022 · 31 citations
