A framework for relating natural movement to length and quality of life in human and non-human animals

Iain Hunter, Raz Leib

Research output: Contribution to journalArticlepeer-review

Abstract

Natural movement is clearly related to health, however, it is also highly complex and difficult to measure. Most attempts to measure it focus on functional movements in humans, and while this a valid and popular approach, assays focussed on particular movements cannot capture the range of natural movement that occurs outside them. It is also difficult to use current techniques to compare movement across animal species. Interspecies comparison may be useful for identifying conserved biomechanical and/ or computational principles of movement that could inform human and veterinary medicine, plus several other fields of research. It is therefore important that research develops a system for quantifying movement in freely moving animals in natural environments and relating it to length and quality of life (LQOL). The present text proposes a novel theoretical framework for doing so, based on screening movement ability (MA). MA is calculated from three major variables – Movement Quality, Movement Complexity, and Movement Quantity. These may represent the most important components of movement as it relates to LQOL, and offer insight into how and why differences in the relationship between movement and LQOL occur. A constrained version of the framework is validated in Drosophila, which suggests that MA may indeed represent a useful new paradigm for understanding the relationship between movement and length and quality of life.

Original languageEnglish
Article number111649
JournalJournal of Theoretical Biology
Volume576
DOIs
StatePublished - 7 Jan 2024
Externally publishedYes

Keywords

  • Biomechanics
  • Complexity
  • Lifespan
  • Locomotion
  • Model

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics

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