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Biotensegrity is the super-stability hypothesis for biologyUnder a Creative Commons license
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Highlights
- •
The biotensegrity concept is based on a fundamental set of self-organizing principles.
•Tensegrity structures are the physical representations of invisible force-vectors.
•Living organisms as intrinsically-stable tensegrity frameworks.
•The closed-chain kinematics of tensegrity replaces the contrived machine/lever model.
•Super-stability as a general mathematical framework for biological transformations.
Abstract
Biotensegrity models living systems in ways that were inconceivable in the past but has taken some time to become widely accepted because of its challenges to generally accepted wisdom. Orthodox biomechanics is essentially based on mechanistic models from the seventeenth century and allowed over-simplified representations of anatomy and motion to persist to the present day, with the approximations and assumptions inherent within its methods routinely overlooked. Living organisms, however, are hugely complex, intrinsically indeterminate and exist in states that are far from equilibrium, and although their simplification within the machine model has enabled great progress in the mapping of structure to function — and benefitted our healthcare systems in remarkable ways — it has also obfuscated the foundational basis for stability, motion and life itself.
In contrast, biotensegrity is a conceptual framework that is founded on a fundamental set of self-organizing principles and includes all the complexities of life — at every heterarchical level from viruses to vertebrates and molecules to the whole organism — with stability and motion controlled from within the structure itself and the homeostatic algorithm of super-stability. Here, anatomy is no longer reduced to a set of discrete parts but becomes the physical representation of a hugely complex pattern of interacting force vectors, and which are themselves organized within a complex tensegrity configuration that enables each part of the system to adapt to its locally-changing environment in the most energy-efficient way — from embryo to adult — and remain intrinsically stable throughout.
Keywords
Algorithm
Anatomy
Biomechanics
Framework
Hierarchy
Homeostasis
Kinematics
Data availability
No data was used for the research described in the article.
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This article is part of a special issue entitled: Design in Nature published in BioSystems.
© 2025 The Authors. Published by Elsevier B.V.