The aim of the study was to develop a database of biomechanical data for multiple gait tasks. This database will be used to create a real-time gait pattern classifier that will be implemented in a new-generation active knee prosthesis. With this intent, we collected kinematic and kinetic data of 40 subjects performing 16 gait tasks, categorized as periodic and transient motions. We analyzed four distinct sub-populations, differentiated by age and gender. As the classifier will be based also on inertial data, we chose to synthesize these signals within the motion capture environment. To assess the effects of gender and age we performed a correlation analysis on the signals used as input of the classifier. The results obtained indicate that there is no need to differentiate into four distinct classes for the development of the classifier. Sample data of the dataset are made publicly available.

Collection of Kinematic and Kinetic Data of Young and Adult, Male and Female Subjects Performing Periodic and Transient Gait Tasks for Gait Pattern Recognition

Mistretta, Paolo
;
Marchesini, Cecilia;Tagliapietra, Luca;Menegatti, Emanuele;Petrone, Nicola
2020

Abstract

The aim of the study was to develop a database of biomechanical data for multiple gait tasks. This database will be used to create a real-time gait pattern classifier that will be implemented in a new-generation active knee prosthesis. With this intent, we collected kinematic and kinetic data of 40 subjects performing 16 gait tasks, categorized as periodic and transient motions. We analyzed four distinct sub-populations, differentiated by age and gender. As the classifier will be based also on inertial data, we chose to synthesize these signals within the motion capture environment. To assess the effects of gender and age we performed a correlation analysis on the signals used as input of the classifier. The results obtained indicate that there is no need to differentiate into four distinct classes for the development of the classifier. Sample data of the dataset are made publicly available.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/3347333
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact