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Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data
Katrin Trentzsch1, Benjamin Melzer1,2, Heidi Stölzer-Hutsch1
1Center of Clinical Neuroscience, Neurological Clinic, University Hospital Carl Gustav Carus, TU Dresden, Fetscherstr. 74, 01307 Dresden, Germany.
Brain Sciences
|November 27, 2021
Summary
This study explored using accelerometers to measure walking distance for people with multiple sclerosis (pwMS). While promising, accuracy varied, with some pwMS showing errors over 20%.
Area of Science:
- Biomedical Engineering
- Rehabilitation Science
- Neurology
Background:
- Gait impairment significantly impacts daily life for people with multiple sclerosis (pwMS).
- Accurate monitoring of ambulatory function is crucial for managing disease progression.
- Traditional 2-minute walk tests using odometers may have questionable measurement precision.
Purpose of the Study:
- To evaluate the validity of a digital measurement method using accelerometers as an alternative to odometer-based distance tracking.
- To assess the accuracy of two developed algorithms for calculating walking distance in pwMS.
Main Methods:
- Developed two algorithms utilizing data from six Opal accelerometers (Mobility Lab system).
- Compared algorithm-derived distances against gold-standard odometer measurements from 562 pwMS during 2-minute walk tests.
- Analyzed measurement errors and agreement levels (correlation coefficients).
Main Results:
- 48.4% of pwMS showed <5% relative measurement error; 25.8% showed up to 10% error.
- 25.8% of pwMS exhibited >20% measurement error, often due to complex gait alterations.
- Both algorithms demonstrated favorable agreement with the odometer (r = 0.884 and r = 0.980).
Conclusions:
- Accelerometer-based gait analysis shows potential for measuring walking distance in pwMS.
- Algorithm performance is moderate, with significant variability influenced by pathological gait patterns.
- Further system improvements are needed to enhance accuracy for all pwMS.
