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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2504.16378 |
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| _version_ | 1866908333378633728 |
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| author | Okoshi, Tadashi Gao, Zexiong Zhen, Tan Yi Karasawa, Takumi Miki, Takeshi Sasaki, Wataru Balan, Rajesh K. |
| author_facet | Okoshi, Tadashi Gao, Zexiong Zhen, Tan Yi Karasawa, Takumi Miki, Takeshi Sasaki, Wataru Balan, Rajesh K. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_16378 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cyberoception: Finding a Painlessly-Measurable New Sense in the Cyberworld Towards Emotion-Awareness in Computing Okoshi, Tadashi Gao, Zexiong Zhen, Tan Yi Karasawa, Takumi Miki, Takeshi Sasaki, Wataru Balan, Rajesh K. Human-Computer Interaction Artificial Intelligence 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. |
| title | Cyberoception: Finding a Painlessly-Measurable New Sense in the Cyberworld Towards Emotion-Awareness in Computing |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2504.16378 |