title: Attractor-shape descriptors for balance impairment assessment in Parkinson's disease.
abstract: In this paper, we propose a computational framework using high-dimensional shape descriptors of reconstructed attractors of center-of-pressure (CoP) tracings collected from subjects with Parkinson's disease while performing dynamical posture shifts, to quantitatively assess balance impairment. Using a dataset collected from 60 subjects, we demonstrated that the proposed method outperforms traditional methods, such as dynamical shift indices and use of chaotic invariants, in assessment of balance impairment.
authors.forename: Anirudh
authors.initials: A
authors.lastname: Som
authors.forename: Narayanan
authors.initials: N
authors.lastname: Krishnamurthi
authors.forename: Vinay
authors.initials: V
authors.lastname: Venkataraman
authors.forename: Pavan
authors.initials: P
authors.lastname: Turaga
mesh_terms: D000368:Aged; D019295:Computational Biology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000175:diagnosis* / Q000503:physiopathology*; D004856:Postural Balance; D011312:Pressure; D012815:Signal Processing, Computer-Assisted