mlsanityData to 7 Oct 2026

PixleepFlow: A Pixel-Based Lifelog Framework for Predicting Sleep Quality and Stress Level

arXiv 2502.17469 ↗First posted 13 Feb 2025eess.SP cs.AI cs.LGcited by 3

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Abstract (arXiv)

The analysis of lifelogs can yield valuable insights into an individual's daily life, particularly with regard to their health and well-being. The accurate assessment of quality of life is necessitated by the use of diverse sensors and precise synchronization. To rectify this issue, this study proposes the image-based sleep quality and stress level estimation flow (PixleepFlow). PixleepFlow employs a conversion methodology into composite image data to examine sleep patterns and their impact on overall health. Experiments were conducted using lifelog datasets to ascertain the optimal combination of data formats. In addition, we identified which sensor information has the greatest influence on the quality of life through Explainable Artificial Intelligence(XAI). As a result, PixleepFlow produced more significant results than various data formats. This study was part of a written-based competition, and the additional findings from the lifelog dataset are detailed in Section Section IV. More information about PixleepFlow can be found at https://github.com/seongjiko/Pixleep.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 5 of its 14 references that are in the map. First posted on arXiv 13 Feb 2025.

Builds on

5 of 14 references.

References · 5

  1. 2017Squeeze-and-Excitation Networkscited by 4,763
  2. 2016Aggregated Residual Transformations for Deep Neural Networkscited by 2,540
  3. 2020Sharpness-Aware Minimization for Efficiently Improving Generalizationcited by 1,404
  4. 2019Full-Gradient Representation for Neural Network Visualizationcited by 189
  5. 2024Human Understanding AI Paper Challenge 2024 -- Dataset Designcited by 2

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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025Understanding Human Daily Experience Through Continuous Sensing: ETRI Lifelog Dataset 2024cited by 1
  2. 2025MIS-LSTM: Multichannel Image-Sequence LSTM for Sleep Quality and Stress Predictioncited by 0
  3. 2025Subject-Adaptive Sparse Linear Models for Interpretable Personalized Health Prediction from Multimodal Lifelog Datacited by 0