Authors:
Chiara Martini
1
;
Nicoletta Noceti
1
;
Manuela Chessa
1
;
Annalisa Barla
1
;
Alberto Cella
2
;
Gian Andrea Rollandi
2
;
Alberto Pilotto
2
;
Alessandro Verri
1
and
Francesca Odone
1
Affiliations:
1
Università degli Studi di Genova, Italy
;
2
E.O. Ospedali Galliera, Italy
Keyword(s):
Visual Computing, Skeleton Data, Motility Index, Frailty, Aging.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
;
Video Surveillance and Event Detection
Abstract:
The accurate estimation of frailty is an important objective to assess the overall well-being and to predict
the risk of mortality of elderly. Such evaluation is commonly based on subjective quantities both from self-reported
outcomes and occasional physicians evaluations, leading to possibly biased results. An objective and
continuous frailty screening tool may be more appropriate for routine assessment. In this paper, we present a
data driven method to evaluate one of the main aspect contributing to the frailty estimation, i.e. the motility
of the subject. To this aim, we define a motility index, estimated following a visual computing approach
analysing streams of RGB-D data. We provide an extensive experimental assessment performed on two sets
of data acquired in a sensorised facility located within a local hospital. The results are in good agreement with
the assessment manually performed by the physicians, nicely showing the potential of our approach.