title: Clustering-based limb identification for pressure ulcer risk assessment.
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.
authors.forename: M
authors.initials: M
authors.lastname: Baran Pouyan
authors.forename: M
authors.initials: M
authors.lastname: Nourani
authors.forename: M
authors.initials: M
authors.lastname: Pompeo
mesh_terms: D000328:Adult; D000465:Algorithms; D016000:Cluster Analysis; D005121:Extremities / Q000473:pathology*; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015233:Models, Statistical; D016011:Normal Distribution; D011187:Posture; D011312:Pressure; D003668:Pressure Ulcer / Q000175:diagnosis* / Q000517:prevention & control*; D015995:Prevalence; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D012890:Sleep; D016683:Supine Position