title: Analysis and comparison of sleeping posture classification methods using pressure sensitive bed system.
abstract: Pressure ulcers are common problems for bedridden patients. Caregivers need to reposition the sleeping posture of a patient every two hours in order to reduce the risk of getting ulcers. This study presents the use of Kurtosis and skewness estimation, principal component analysis (PCA) and support vector machines (SVMs) for sleeping posture classification using cost-effective pressure sensitive mattress that can help caregivers to make correct sleeping posture changes for the prevention of pressure ulcers.
authors: ICT-Enabled Healthcare Program, Industrial Technology Research Institute, ITRI South, No. 31, Gongye 2nd Rd., Annan District, Tainan City 70955, Taiwan, R.O.C. shiacj@itri.org.tw
authors: C C
authors: CC
authors: Hsia
authors: K J
authors: KJ
authors: Liou
authors: A P W
authors: AP
authors: Aung
authors: V
authors: V
authors: Foo
authors: W
authors: W
authors: Huang
authors: J
authors: J
authors: Biswas
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001513:Beds; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D008365:Manometry / Q000295:instrumentation* / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011187:Posture / Q000502:physiology*; D011312:Pressure; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012890:Sleep / Q000502:physiology*