Authors:
Asma Hassani
;
Alexandre Kubicki
;
Vincent Brost
and
Fan Yang
Affiliation:
University of Burgundy, France
Keyword(s):
Geriatric Health, TUG Test, Autonomy Assessment, Kinect, Spatio-temporal Movement Parameter Extraction, 3D Real-time Video Processing.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Medical Image Applications
Abstract:
In this paper, we present experiments on the design of a novel movement analysis system for real-time balance
assessment in the frail elderly. Using the Microsoft Kinect sensors, we capture TUG (Timed Up and Go) tests
and mainly analyze the transfer from sitting-to-standing and back-to-sitting which represent two of the most
commonly executed human movements. Nine spatio-temporal parameters were extracted from recorded joint
positions by 3D skeletal sequence processing. In order to validate and evaluate the developed system, practical
test experiences have been performed on ten healthy young subjects, who were asked to realize the TUG in
three different conditions: normal, cognitive and motor. Obtained results showed good measurement reliability
and reproducibility with important precision. In addition, we observed that even for young healthy subjects,
there is a significant difference of movement parameter between normal condition and cognitive condition,
which represents a stimulat
ing result in the dual task paradigm field. This preliminary study opens a new
research and development way for geriatric health which implies multiple aspects: user-friendly, hygiene,
low-cost, home-based environment, and automatic autonomy assessment.
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