DocumentCode :
3684885
Title :
Clustering-based limb identification for pressure ulcer risk assessment
Author :
M. Baran Pouyan;M. Nourani;M. Pompeo
Author_Institution :
Quality of Life Technology Laboratory, The University of Texas at Dallas, Richardson, 75080, USA
fYear :
2015
Firstpage :
4230
Lastpage :
4233
Abstract :
Bedridden patients have a high risk of developing pressure ulcers. Risk assessment for pressure ulceration is critical for preventive care. For a reliable assessment, we need to identify and track the limbs continuously and accurately. In this paper, we propose a method to identify body limbs using a pressure mat. Three prevalent sleep postures (supine, left and right postures) are considered. Then, predefined number of limbs (body parts) are identified by applying Fuzzy C-Means (FCM) clustering on key attributes. We collected data from 10 adult subjects and achieved average accuracy of 93.2% for 10 limbs in supine and 7 limbs in left/right postures.
Keywords :
"Accuracy","Risk management","Conferences","Clustering algorithms","Pressure sensors","Head","Wounds"
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
ISSN :
1094-687X
Electronic_ISBN :
1558-4615
Type :
conf
DOI :
10.1109/EMBC.2015.7319328
Filename :
7319328
Link To Document :
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