TY - JOUR
T1 - The kinectome
T2 - A comprehensive kinematic map of human motion in health and disease
AU - Troisi Lopez, Emahnuel
AU - Sorrentino, Pierpaolo
AU - Liparoti, Marianna
AU - Minino, Roberta
AU - Polverino, Arianna
AU - Romano, Antonella
AU - Carotenuto, Anna
AU - Amico, Enrico
AU - Sorrentino, Giuseppe
N1 - Copyright:
© 2022 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals LLC on behalf of New York Academy of Sciences.
PY - 2022/10
Y1 - 2022/10
N2 - 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.
AB - 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.
KW - gait analysis
KW - movement pattern
KW - network
KW - Parkinson's disease
UR - https://www.scopus.com/pages/publications/85139880730
U2 - 10.1111/nyas.14860
DO - 10.1111/nyas.14860
M3 - Article
C2 - 35838306
AN - SCOPUS:85139880730
SN - 0077-8923
VL - 1516
SP - 247
EP - 261
JO - Annals of the New York Academy of Sciences
JF - Annals of the New York Academy of Sciences
IS - 1
ER -