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Quantification of postural stability in Parkinson’s disease patients utilizing mobile technology

J.L. Alberts, M.M. Koop, S.M. Linder, T. Dey, S.J. Ozinga (Cleveland, OH, USA)

Meeting: 2016 International Congress

Abstract Number: 543

Keywords: Gait disorders: Clinical features, Locomotion, Motor control, Posture

Session Information

Date: Tuesday, June 21, 2016

Session Title: Technology

Session Time: 12:30pm-2:00pm

Location: Exhibit Hall located in Hall B, Level 2

Objective: To validate the use of a mobile device and an associated biomechanical outcome to objectively quantify postural stability in Parkinson’s disease (PD) patients.

Background: Postural instability is a hallmark of PD and is often refractory to medication and deep brain stimulation. Rapid and objective metrics that accurately characterize postural stability are necessary for the development of effective fall risk stratification models and treatment algorithms to more effectively aid in the pharmacological, post-surgical and behavioral treatment of postural instability.

Methods: An iPad/iPhone mobile application was developed that utilized the built-in accelerometer and gyroscope to gather biomechanical acceleration and rotational data to characterize patient’s movement of the center of mass in the medial-lateral (ML) and anterior-posterior (AP) planes and trunk rotation (TR). Twenty-seven PD patients and 27 age-matched controls completed balance tasks in which the support surface, stance, and vision were altered. Postural stability metrics quantifying peak-to-peak (P2P) of sway acceleration in each movement direction were compared between groups. The P2P value in each direction for each patient across all trials was expressed as a normalized value of the control data in order to identify PD patients with severe postural instability (percentile value of postural instability greater than 95th percentile of controls). Lastly, the normalized P2P data in all three directions were combined to create a single balance metric, Cleveland Clinic-Postural Stability Index (CC-PSI), to quantify postural instability.

Results: Patients with PD showed significantly greater postural instability compared to the control group across all balance conditions shown by the CC-PSI metric (p<0.01 for all tests). Additionally, within the PD group, postural instability increased across all sway directions as sensorimotor integration became more challenging as the difficulty of the postural stability task increased.

Conclusions: Overall, the CC-PSI, which can be rapidly derived using a mobile device, provides an unbiased and systematic metric for the quantification of postural stability in PD patients. The ease of data acquisition and processing make the CC-PSI ideally suited to better understand specific postural stability declines in PD patients and assisting in its treatment.

To cite this abstract in AMA style:

J.L. Alberts, M.M. Koop, S.M. Linder, T. Dey, S.J. Ozinga. Quantification of postural stability in Parkinson’s disease patients utilizing mobile technology [abstract]. Mov Disord. 2016; 31 (suppl 2). https://www.mdsabstracts.org/abstract/quantification-of-postural-stability-in-parkinsons-disease-patients-utilizing-mobile-technology/. Accessed June 15, 2025.
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