DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 이의진 | - |
dc.contributor.author | Kang, Soowon | - |
dc.contributor.author | 강수원 | - |
dc.date.accessioned | 2024-07-26T19:31:00Z | - |
dc.date.available | 2024-07-26T19:31:00Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1047410&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/320983 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 전산학부, 2023.8,[vi, 124 p. :] | - |
dc.description.abstract | Recent studies in emotional intelligence or affective computing have a great interest in interpreting human behaviors and mental health by leveraging mobile and wearable sensor datasets from daily contexts. For this, it is crucial to build and make available for public use such large-scale and in-the-wild datasets that include an appropriate number of affective state labels. However, there is a lack of open datasets collected in real-world contexts with affective and cognitive state labels such as emotion, stress, and attention. In this work, we first validate the self-reported emotion labels obtained via the mobile experience sampling method~(ESM) that is commonly used to measure people's affective states by randomly requesting self-report responses. Next, we release an initial in-the-wild naturalistic dataset of smartphone use, wearable sensing, and self-reported affect states. We supplement three additional datasets and examine the cross-dataset generalizability among them. Finally, we discuss the implications and contributions of the collected datasets that can help to advance the research and development of affective computing, emotional intelligence, and attention management domains. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | 감성 컴퓨팅▼a경험 표집▼a센서 데이터 분석▼a모바일 시스템▼a사회적 컴퓨팅▼a인간-컴퓨터 상호작용 | - |
dc.subject | Affective computing▼aExperience sampling▼aSensor data analysis▼aMobile system▼aSocial computing▼aHuman-computer interaction | - |
dc.title | Modeling human affective states by collecting mobile multimodal datasets in the wild | - |
dc.title.alternative | 실제 환경에서의 모바일 멀티모달 데이터셋 수집을 통한 인간 감성 상태 모델링 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전산학부, | - |
dc.contributor.alternativeauthor | Lee, Uichin | - |
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