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Faculdade de Motricidade Humana, Portugal

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1 Papers

Relevant Elderly Gait Features for Functional Fitness Level Grouping

Topics: Motion and Tracking; Pattern Recognition; Biosignal Acquisition, Analysis and Processing

Authors: Marta S. Santos ¹ , Vera Moniz-Pereira ² , André Lourenço ³ , Ana Fred ⁴ and António P. Veloso ²

Affiliations: ¹ Instituto Telecomunicações, Portugal , ² Univ Tecn Lisboa, Portugal , ³ Instituto de Telecomunicações and Instituto Superior de Engenharia de Lisboa, Portugal , ⁴ Instituto de Telecomunicações, Portugal

Digital Object Identifier: 10.5220/0004726001530160

Proceedings of PhyCS 2014, ISBN: 978-989-758-006-2

Quick Abstract

Locomotor tasks characterization plays an important role in trying to improve the quality of life of a growing elderly population. This paper focuses on this matter by trying to characterize the locomotion of two population groups with different functional fitness levels (high or low) while executing three different tasks - gait, stair ascent and stair descent. Features were extracted from gait data, and feature selection methods were used in order to get the set of features that allow differentiation between functional fitness level. Unsupervised learning was used to validate the sets obtained and, ultimately, indicated that it is possible to distinguish the two population groups. The sets of best discriminate features for each task are identified and thoroughly analysed.

Related Ontology Subjects/Areas/Topics (18)

Applications	Data Manipulation	Neurocomputing
Artificial Intelligence	Health Engineering and Technology Applications	Neurotechnology, Electronics and Informatics
Biomedical Engineering	Human-Computer Interaction	Pattern Recognition
Biomedical Signal Processing	Methodologies and Methods	Physiological Computing Systems
Biosignal Acquisition, Analysis and Processing	Motion and Tracking	Sensor Networks
Computer Vision, Visualization and Computer Graphics	Motion, Tracking and Stereo Vision	Soft Computing