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Assessing Walking Adaptability in Parkinson's Disease: "The Interactive Walkway"
Daphne J Geerse1,2, Melvyn Roerdink2, Johan Marinus1
1Department of Neurology, Leiden University Medical Center, Leiden, Netherlands.
Frontiers in Neurology
|January 12, 2019
Summary
The Interactive Walkway offers a comprehensive assessment of walking ability in Parkinson's disease (PD), providing valuable insights beyond traditional clinical tests. This advanced tool aids in understanding complex walking impairments and potential fall risks.
Area of Science:
- Neurology
- Biomechanics
- Rehabilitation Science
Background:
- Parkinson's disease (PD) significantly impairs walking ability, affecting stepping, balance, and adaptation.
- Current clinical tests often assess walking in isolation, failing to capture complex, real-world functional deficits.
Purpose of the Study:
- To evaluate the added value of the Interactive Walkway for assessing walking ability in Parkinson's disease.
- To compare Interactive Walkway measures with traditional clinical tests for validity and discriminative power, particularly for freezing of gait.
Main Methods:
- Assessed validity of Interactive Walkway measures for unconstrained, adaptive, and dual-task walking in people with PD.
- Correlated Interactive Walkway outcomes with standard clinical walking test scores.
- Evaluated the ability of Interactive Walkway measures to differentiate individuals with and without freezing of gait.
Main Results:
- Interactive Walkway measures demonstrated significant differences between Parkinson's patients (freezers and non-freezers) and healthy controls.
- Most Interactive Walkway outcomes showed weak to moderate correlations with clinical test scores.
- Adaptive walking measures from the Interactive Walkway showed slightly superior discrimination of freezing of gait compared to clinical tests.
Conclusions:
- The Interactive Walkway provides a comprehensive assessment of walking, integrating key aspects of gait relevant to daily life in Parkinson's disease.
- This technology holds potential for assessing fall risk and informing personalized fall prevention strategies in PD and other mobility-impaired populations.