title: Accelerometric signals in automatic balance assessment.
abstract: The paper presents the automatic computer-aided balance assessment system for supporting and monitoring the diagnosis and rehabilitation process of patients with limited mobility or disabled in home environment. The system has adopted seven Berg Balance Scale activities. The assessment approach is based on the accelerometric signals acquired by the inertial sensors worn by the patient. Several specific, mostly medium frequency features of signals are introduced and discussed. The reduction of the feature vector has been performed using the multilevel Fisher's linear discriminant. The classification employs the multilayer perceptron artificial neural network. The direct assessment effectiveness ranges from 75% to 94% for various activities.
authors.affiliation: Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland. Electronic address: pawel.badura@polsl.pl.
authors.forename: Pawel
authors.initials: P
authors.lastname: Badura
mesh_terms: D061725:Accelerometry / Q000379:methods*; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010808:Physical Examination / Q000379:methods*; D004856:Postural Balance / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014724:Vestibular Function Tests / Q000379:methods*
keywords: Ambient assisted living; Balance assessment; Computer-aided diagnosis; Feature extraction