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Updated: Sep 24, 2025

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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Lifelog Retrieval From Daily Digital Data: Narrative Review.

Ricardo Ribeiro1, Alina Trifan1, António J R Neves1

  • 1Institute of Electronics and Informatics Engineering of Aveiro, University of Aveiro, Aveiro, Portugal.

JMIR Mhealth and Uhealth
|May 2, 2022
PubMed
Summary
This summary is machine-generated.

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Lifelogging uses sensor data from personal devices to create digital memories for memory augmentation and support. This review explores lifelogging data, methods, and applications for understanding personal experiences.

Area of Science:

  • Lifelogging and Digital Memory Studies
  • Human-Computer Interaction
  • Personal Informatics

Background:

  • Ubiquitous sensors in personal devices (smartphones, wearables) enable real-time data acquisition (images, audio, location, physiological signals).
  • This data, termed lifelog data, facilitates analysis of personal experiences and behaviors through lifelogging.
  • Decreasing sensor costs and increasing availability have driven the growth of lifelogging research.

Purpose of the Study:

  • To present a narrative review of lifelogging literature from the past decade.
  • To analyze lifelogging applications for information retrieval, memory support, and augmentation.
  • To provide researchers with an overview of data types, methodologies, and applications in lifelogging.

Main Methods:

Keywords:
computer visionevent segmentationimage retrievalinformation retrievallifeloglifeloggingmobile phonesignal processing

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  • Conducted a narrative review using Google Scholar and Scopus databases with lifelogging keywords.
  • Screened 411 retrieved publications, fully reviewing 114 and manually including 30.
  • Selected 113 publications for the review based on content analysis.

    • Main Results:

    • Lifelogs show potential as powerful tools for memory retrieval and understanding individual experiences.
    • Numerous computational tools exist for diverse lifelogging applications, utilizing multimodal data.
    • Visual lifelogs are a prominent data source, with various processing approaches and algorithms identified.

    Conclusions:

    • Lifelogging systems offer benefits for memory augmentation and support for individuals with memory impairments.
    • Lifelog data analysis can generate digital memories serving as surrogate memory.
    • Contextual information extracted from lifelogs enhances understanding of daily life events, experiences, and behaviors.