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Workflow for health-related and brain data lifecycle.

Petr Brůha1, Roman Mouček1,2, Jaromír Salamon1

  • 1Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Pilsen, Czech Republic.

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Integrating physical and brain health data offers a novel approach to precisely identify lifestyle-related health issues. This enables better interpretation of overall health, improving quality and length of life.

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Area of Science:

  • Integrative health sciences
  • Biomedical data science
  • Neuroscience and public health

Background:

  • Poor lifestyle choices are linked to chronic diseases and diminished physical and mental fitness.
  • Current health assessments rarely integrate physical and brain activity data for comprehensive analysis.
  • Analyzing these combined datasets can lead to earlier identification and management of lifestyle-induced health problems.

Purpose of the Study:

  • To explore best practices for collecting, annotating, analyzing, and evaluating integrated physical and brain health data.
  • To demonstrate the development of an automated workflow system for managing such data.
  • To highlight the potential of combined data for improving human healthspan and lifespan.

Main Methods:

  • Overview of global best practices for data reproducibility, including data lifecycle models and FAIR principles.
  • Development and implementation of an automated workflow system (Body in Numbers pilot system).
  • Integration of physical parameters, health risk factors, motivation levels, and electrophysiological brain activity data.

Main Results:

  • Established a framework for reproducible collection and analysis of combined health data.
  • Developed a pilot system demonstrating an automated workflow for data processing and evaluation.
  • Showcased the unique integration of physical and electrophysiological data for health insights.

Conclusions:

  • Combined physical and brain health data analysis provides a robust basis for understanding overall health.
  • Adoption of best practices and automated systems enhances data reproducibility and scientific collaboration.
  • The Body in Numbers system offers a model for future integrated health data research and application.