Related Experiment Video
Updated: Aug 6, 2026
07:51
Video Movement Analysis Using Smartphones (ViMAS): A Pilot Study
Published on: March 14, 2017
Smartphone-based vestibular & gait analysis for remote fall risk assessment
Eugene Rezk1,2,3,4, Marion Luschin-Ebengreuth4,5, Hannes Kaufmann1
1Virtual and Augmented Reality Group, Institute for Visual Computing and Human-Centered Technology, Faculty of Informatics, TU Vienna, Vienna, Austria.
Frontiers in Digital Health
|July 23, 2026
Summary
This study proposes a smartphone-based framework for assessing vestibular function and gait stability, aiding in early fall risk identification. The technology integrates eye tracking and motion analysis for accessible screening, particularly for neurologic patients.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Digital Health
Background:
- Dizziness and vertigo are common clinical complaints and significant fall risk factors, especially in neurologic and neuroorthopedic populations.
- Current diagnostic tools like video-oculography (VOG) and motion analysis are often inaccessible due to cost and complexity.
- Early identification of balance and gait impairments is crucial for effective fall prevention strategies.
Purpose of the Study:
- To propose a conceptual framework for smartphone-based assessment of vestibular function and gait stability.
- To enable accessible and scalable screening for fall risk, particularly in resource-constrained settings.
- To lay the methodological foundation for future clinical validation of mobile health solutions.
Main Methods:
- Integration of near-infrared eye tracking and inertial measurement unit (IMU)-based motion analysis within a smartphone.
- Extraction of oculomotor features (vestibulo-ocular behavior) and biomechanical features (gait stability metrics like Triangular Area Variability and inter-limb symmetry).
- Utilizing virtual anatomical reference points and sacral motion projection for biomechanical stability analysis.
Main Results:
- A conceptual framework is presented, outlining the integration of advanced sensing technologies on a smartphone.
- Methods for extracting key oculomotor and biomechanical features relevant to balance and gait are described.
- The framework provides a structured approach for developing mobile applications for fall risk assessment.
Conclusions:
- The proposed framework offers a foundation for developing accessible, smartphone-based tools for screening vestibular function and gait stability.
- This approach has the potential to significantly contribute to fall prevention research and clinical practice, especially in vulnerable populations.
- Future studies are needed for clinical validation and real-world data collection to confirm the efficacy of this mobile health solution.
