To propose a conceptual framework for smartphone-based assessment of vestibular function and gait stability to support fall-related screening.
Approach:
Framework Development: Integration of near-infrared eye tracking with inertial measurement unit (IMU)-based motion analysis within a smartphone-based sensing environment.
Feature Extraction: Methods for extracting oculomotor and biomechanical features, including vestibulo-ocular behavior and gait stability metrics.
Biomechanical Stability Description: Introduction of virtual anatomical reference points and projection of sacral motion onto the interpatellar axis.
Key Findings:
Dizziness and vertigo are major clinical burdens and risk factors for falls.
Current diagnostic tools like video-oculography (VOG) are limited by cost and complexity.
Smartphone-based assessments can provide accessible alternatives for fall risk evaluation, utilizing metrics such as Triangular Area Variability (TAV) and inter-limb symmetry.
Interpretation:
The framework aims to facilitate early identification of balance-related impairments using mobile technology; however, it is conceptual and lacks clinical validation.
Limitations:
The proposed framework is conceptual and does not include clinical validation or real-world data.
Accessibility and effectiveness in diverse populations have not been tested.
Conclusion:
The framework provides a structured methodological foundation for future studies on smartphone-based fall risk assessment.
