Related papers: Understanding Human Daily Experience Through Continuous Sensing: ETRI Lifelog Dataset 2024

Understanding Human Daily Experience Through Continuous Sensing: ETRI Lifelog Dataset 2024

URL: http://arxiv.org/abs/2508.03698v1
Date: Fri, 18 Jul 2025 00:51:42 GMT
Title: Understanding Human Daily Experience Through Continuous Sensing: ETRI Lifelog Dataset 2024
Authors: Se Won Oh, Hyuntae Jeong, Seungeun Chung, Jeong Mook Lim, Kyoung Ju Noh, Sunkyung Lee, Gyuwon Jung,
Abstract summary: We introduce the ETRI Lifelog dataset 2024, detailing its structure and presenting potential applications.<n>This comprehensive lifelog dataset is expected to provide a foundational resource for exploring meaningful insights into human daily life and lifestyle patterns.
Score: 2.6953508724475967
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Improving human health and well-being requires an accurate and effective understanding of an individual's physical and mental state throughout daily life. To support this goal, we utilized smartphones, smartwatches, and sleep sensors to collect data passively and continuously for 24 hours a day, with minimal interference to participants' usual behavior, enabling us to gather quantitative data on daily behaviors and sleep activities across multiple days. Additionally, we gathered subjective self-reports of participants' fatigue, stress, and sleep quality through surveys conducted immediately before and after sleep. This comprehensive lifelog dataset is expected to provide a foundational resource for exploring meaningful insights into human daily life and lifestyle patterns, and a portion of the data has been anonymized and made publicly available for further research. In this paper, we introduce the ETRI Lifelog Dataset 2024, detailing its structure and presenting potential applications, such as using machine learning models to predict sleep quality and stress.

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