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Gait characterization in rare bone diseases in a real-world environment - A comparative controlled study
Sascha Fink1, Michael Suppanz2, Johannes Oberzaucher3
1Institute of Human Movement Science, Sport and Health, University of Graz, Schubertstrasse 1/III, Graz 8010, Austria; Institute for applied Human movement Science, Carinthia University of Applied Sciences, Europastraße 4, Villach 9524, Austria; Institute for applied research on Aging, Carinthia University of Applied Sciences, Europastraße 4, Villach 9524, Austria.
Smartphone sensors can detect gait changes in rare bone diseases (RBD). This technology aids in monitoring mobility challenges and informing future management strategies for individuals with RBD.
Area of Science:
- Biomedical Engineering
- Rehabilitation Science
- Digital Health
Background:
- Rare bone diseases (RBD) significantly impact quality of life, often causing mobility challenges.
- Traditional gait analysis requires specialized labs, posing accessibility issues for individuals with RBD.
- Smartphone sensors offer a potential solution for remote and accessible gait monitoring.
Purpose of the Study:
- To identify smartphone sensor-derived variables capable of differentiating individuals with RBD from healthy controls.
- To explore the feasibility of using built-in smartphone sensors for gait analysis in a real-world setting.
Main Methods:
- A cross-sectional study included 18 participants (9 healthy, 9 with RBD), matched for age and sex.
- The Phyphox app collected accelerometer and gyroscope data at 60 Hz during a 15-minute walk.
- Gait parameters analyzed included temporal measures (cadence, stride time) and nonlinear dynamics (Lyapunov exponent, sample entropy).
Main Results:
- Nonlinear gait parameters, specifically the largest Lyapunov exponent (LLE) and sample entropy (SE) of the z-axis, significantly distinguished between RBD patients and controls (p=0.04 and p=0.01, respectively).
- These parameters reflect balance control and gait regularity, demonstrating sensitivity to subtle gait alterations.
Conclusions:
- Smartphone sensors can effectively monitor gait in individuals with rare bone diseases.
- This approach allows for the detection of subtle gait pattern changes, informing assessment and management strategies.
- Remote monitoring via smartphones holds promise for larger cohort studies and improved patient care.
