Smartphone-based vestibular & gait analysis for remote fall risk assessment

Dizziness and vertigo are among the most common reasons for clinical consultation worldwide and represent key risk factors for falls, particularly in neurologic and neuroorthopedic patient populations. Early identification of balance and gait impairments is therefore relevant for fall prevention. However, access to established diagnostic tools such as video-oculography (VOG) and motion analysis systems remains limited due to cost, technical complexity, and the need for specialized personnel, especially in resource-constrained settings. This work proposes a conceptual framework for smartphone-based assessment of vestibular function and gait stability, aimed at supporting fall-related screening concepts. The approach is designed to integrate near-infrared eye tracking with inertial measurement unit (IMU)-based motion analysis within a unified smartphone-based sensing environment, enabling mobile and scalable applications. The framework outlines methods for extracting oculomotor and biomechanical features, including vestibulo-ocular behavior and gait stability metrics such as Triangular Area Variability (TAV) and inter-limb symmetry. In addition, it introduces the use of virtual anatomical reference points (S1, $P_L$ , $P_R$ ) and the projection of sacral motion onto the interpatellar axis to describe biomechanical stability. As a conceptual contribution, this work does not include clinical validation or real-world data but provides a structured methodological foundation for future studies. The proposed framework is intended to support the development of accessible, smartphone-based screening and monitoring approaches for the early identification of balance-related impairments, thereby contributing to fall prevention research in neurologic and neuroorthopedic populations.