Research output per year
Research output per year
Emahnuel Troisi Lopez, Pierpaolo Sorrentino, Marianna Liparoti, Roberta Minino, Arianna Polverino, Antonella Romano, Anna Carotenuto, Enrico Amico, Giuseppe Sorrentino*
Research output: Contribution to journal › Article › peer-review
Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body elements. Network science can be a useful approach to describe movement as a whole and to extract features that are relevant to understanding both its complex physiology and the pathophysiology of movement disorders. Here, we propose to represent human movement as a network (that we named the kinectome), where nodes represent body points, and edges are defined as the correlations of the accelerations between each pair of them. We applied this framework to healthy individuals and patients with Parkinson's disease, observing that the patients’ kinectomes display less symmetrical patterns as compared to healthy controls. Furthermore, we used the kinectomes to successfully identify both healthy and diseased subjects using short gait recordings. Finally, we highlighted topological features that predict the individual clinical impairment in patients. Our results define a novel approach to study human movement. While deceptively simple, this approach is well-grounded, and represents a powerful tool that may be applied to a wide spectrum of frameworks.
Original language | English |
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Pages (from-to) | 247-261 |
Number of pages | 15 |
Journal | Annals of the New York Academy of Sciences |
Volume | 1516 |
Issue number | 1 |
Early online date | 15 Jul 2022 |
DOIs | |
Publication status | Published - Oct 2022 |
Research output: Working paper/Preprint › Preprint