Vol. 123, No. 1 (Supplement) 2018
Supplement abstract

The graph theory applied to the study of the human locomotor system: a simulated amputation changes the characteristics of the system

Daniele Della Posta
Università degli Studi Di Firenze, DMSC, Firenze, Italia
Massimo Gulisano
Università degli Studi Di Firenze, DMSC, Firenze, Italia
Ferdinando Paternostro
Università degli Studi Di Firenze, DMSC, Firenze, Italia
Ugo Santosuosso
Università degli Studi Di Firenze, DMSC, Firenze, Italia
Cristiana Veltro
Università degli Studi Di Firenze, DMSC, Firenze, Italia
Piergiorgio Francia
Università degli Studi Di Firenze, DMSC, Firenze, Italia

Published 2018-12-30

Keywords

  • Locomotor system,
  • Graph theory,
  • Tensegrity,
  • Diabetes

How to Cite

Della Posta, D., Gulisano, M., Paternostro, F., Santosuosso, U., Veltro, C., & Francia, P. (2018). The graph theory applied to the study of the human locomotor system: a simulated amputation changes the characteristics of the system. Italian Journal of Anatomy and Embryology, 123(1), 76. https://doi.org/10.13128/ijae-11378

Abstract

The study of the relationships between the different structures of the human locomotor system still to date raises great interest. In fact, the human body networks and in particular the myofascial system “myofascial system network” underlie posture and movement and new knowledge could be useful and applied to many fields such as medicine and prosthetics. The hypothesis of this study was to verify the possibility of creating a structural network represent- ing the human locomotor system as well as to study and describe the relationship between the different structures considered.

The graph theory was applied to a network of 2339 body parts (nodes) and 7310 links, rep- resenting the locomotor system. The open source platform software Cytoscape was used for data entry (nodes and links) as well as for debugging. In addition, the “Network Analyzer” plugin was used for the descriptive statistics of the network obtained. In order to achieve a better rendering, the results of the network parameters gained were then imported into Gephi (www.Gephi.org).

At the end of this procedure, we obtained a image of a human being in an orthostatic posi- tion with a precise distribution of the nodes and links.

By simulating the common amputations at the level of the foot and leg (as for necrotic com- plications of diabetes) the balance between the parts and the whole structure of the graph are profoundly modified.

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