Sarah J Ozinga1,2, Andre G Machado1,3, Mandy Miller Koop1, Anson B Rosenfeldt1,3, Jay L Alberts1,3. 1. Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA. 2. Department of Chemical and Biomedical Engineering, Cleveland State University, Cleveland, Ohio, USA. 3. Center for Neurological Restoration, Cleveland Clinic, Cleveland, Ohio, USA.
Abstract
BACKGROUND: A significant gap remains in the ability to effectively characterize postural instability in individuals with Parkinson's disease. Clinical evaluation of postural declines is largely subjective, whereas objective biomechanical approaches are expensive and time consuming, thus limiting clinical adoption. Recent advances in mobile devices present an opportunity to address the gap in the quantification of postural stability. The aim of this project was to determine whether kinematic data measured by hardware within a tablet device, a 3rd generation iPad, was of sufficient quantity and quality to characterize postural stability. METHODS: Seventeen patients and 17 age-matched controls completed six balance conditions under altered surface, stance, and vision. Simultaneous kinematic measurements were gathered from a three-dimensional motion capture system and tablet. RESULTS: The motion capture system and tablet provided similar measures of stability across groups. In particular, within the patient population, correlation between the two systems for peak-to-peak, normalized path length, root mean square, 95% volume, and total power values ranged from 0.66 to 1.00. Kinematic data from five balance conditions--double-leg stance with eyes open on a foam surface, double-leg stance with eyes closed on firm and foam surfaces, and tandem stance on firm and foam surfaces--were capable of discriminating patients from controls. CONCLUSIONS: The hardware within the tablet provides data of sufficient accuracy for the quantification of postural stability in patients with Parkinson's disease. The objectivity, portability, and ease of use of this device make it ideal for use in clinical environments lacking sophisticated biomechanical systems.
BACKGROUND: A significant gap remains in the ability to effectively characterize postural instability in individuals with Parkinson's disease. Clinical evaluation of postural declines is largely subjective, whereas objective biomechanical approaches are expensive and time consuming, thus limiting clinical adoption. Recent advances in mobile devices present an opportunity to address the gap in the quantification of postural stability. The aim of this project was to determine whether kinematic data measured by hardware within a tablet device, a 3rd generation iPad, was of sufficient quantity and quality to characterize postural stability. METHODS: Seventeen patients and 17 age-matched controls completed six balance conditions under altered surface, stance, and vision. Simultaneous kinematic measurements were gathered from a three-dimensional motion capture system and tablet. RESULTS: The motion capture system and tablet provided similar measures of stability across groups. In particular, within the patient population, correlation between the two systems for peak-to-peak, normalized path length, root mean square, 95% volume, and total power values ranged from 0.66 to 1.00. Kinematic data from five balance conditions--double-leg stance with eyes open on a foam surface, double-leg stance with eyes closed on firm and foam surfaces, and tandem stance on firm and foam surfaces--were capable of discriminating patients from controls. CONCLUSIONS: The hardware within the tablet provides data of sufficient accuracy for the quantification of postural stability in patients with Parkinson's disease. The objectivity, portability, and ease of use of this device make it ideal for use in clinical environments lacking sophisticated biomechanical systems.
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Authors: Alberto J Espay; Paolo Bonato; Fatta B Nahab; Walter Maetzler; John M Dean; Jochen Klucken; Bjoern M Eskofier; Aristide Merola; Fay Horak; Anthony E Lang; Ralf Reilmann; Joe Giuffrida; Alice Nieuwboer; Malcolm Horne; Max A Little; Irene Litvan; Tanya Simuni; E Ray Dorsey; Michelle A Burack; Ken Kubota; Anita Kamondi; Catarina Godinho; Jean-Francois Daneault; Georgia Mitsi; Lothar Krinke; Jeffery M Hausdorff; Bastiaan R Bloem; Spyros Papapetropoulos Journal: Mov Disord Date: 2016-04-29 Impact factor: 10.338
Authors: Jay L Alberts; Anson B Rosenfeldt; Cielita Lopez-Lennon; Erin Suttman; A Elizabeth Jansen; Peter B Imrey; Leland E Dibble Journal: Phys Ther Date: 2021-11-01