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Related Experiment Videos

Quantifying turning behavior and gait in Parkinson's disease using mobile technology.

Mandy Miller Koop1, Sarah J Ozinga1, Anson B Rosenfeldt1

  • 1Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States.

IBRO Reports
|August 24, 2018
PubMed
Summary

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Mobile sensors can objectively measure Parkinson's disease (PD) gait improvements with medication. The Cleveland Clinic Mobility and Balance app provides clinicians with reliable data for better PD symptom management.

Area of Science:

  • Biomedical Engineering
  • Neurology
  • Rehabilitation Science

Background:

  • Gait and balance impairments in Parkinson's disease (PD) are challenging to treat.
  • Objective gait analysis is vital for managing PD symptoms.
  • Traditional assessments often lack quantitative precision.

Purpose of the Study:

  • To assess if mobile inertial measurement unit (IMU) biomechanical metrics can detect anti-Parkinsonian medication effects during the Timed Up and Go (TUG) Test.
  • To develop the Cleveland Clinic Mobility and Balance (CC-MB) application for objective TUG reporting.
  • To provide clinicians with a tool for quantitative mobility assessment in PD.

Main Methods:

  • Thirty people with PD (pwPD) performed the TUG test On and Off anti-PD medication.
Keywords:
AP, anterior-posteriorCC-MB, Clinic Mobility and Balance ApplicationConsumer electronics deviceICC, IntraClass Correlation CoefficientIMU, inertial monitoring unitML, medial-lateralNJS, Normalized jerk scoresPD, Parkinson’s diseaseParkinson’s diseaseRMS, root mean squareSTW, Sit-to-WalkTTS, Turn-to-SitTUG, Timed-Up-And-Go-TestTimed Up and GoV, verticalcvCadence, coefficient of variation for cadencepwPD, people with Parkinson’s disease

Related Experiment Videos

  • A mobile device captured 3D acceleration and rotation data to analyze center of mass movement.
  • TUG trials were segmented into Sit-to-Walk, Gait, Turning, and Stand-to-Sit phases.

    • Main Results:

    • Significant medication-related improvements observed in motor scores, trial time, walking dynamics (normalized jerk), and turning velocity (p < 0.05).
    • Sit-to-Walk and Stand-to-Sit phases showed no significant medication effects.
    • Trial time and turn velocity demonstrated excellent test-retest reliability (ICC 0.83-0.96).

    Conclusions:

    • A mobile device platform can provide reliable, quantitative gait and turning measures during the TUG.
    • The CC-MB application successfully detected significant improvements in pwPD due to anti-Parkinsonian medication.
    • This low-cost, user-friendly tool offers immediate objective reports, suitable for clinical and remote use.