Comparative evaluation of a smartphone-based inertial measurement approach for quantitative gait analysis

Quantitative gait analysis is an important tool in clinical assessment and biomechanical research. Vision-based motion capture systems used in dedicated gait laboratories are considered the reference standard, providing highly accurate kinematic measurements, but they require specialized infrastructure and controlled environments. As a result, wearable inertial sensor systems have become a practical alternative for clinical and everyday gait assessment. This study presents a comparative evaluation of a smartphone-based gait analysis method and a clinically established wearable inertial system. Gait recordings representing healthy, mildly asymmetric, and impaired walking patterns were analysed using both approaches. The comparison focused on clinically relevant parameters, including cadence, swing-phase duration symmetry, and vertical acceleration symmetry. The smartphone-based method employs median-based statistics and robust outlier rejection to enhance reliability under non-ideal measurement conditions. For healthy and mildly asymmetric gait, both systems produced comparable parameter estimates. In gait patterns with pronounced imbalance, the smartphone-based method detected larger deviations, indicating enhanced sensitivity to asymmetry and pathological alterations, highlighting the benefits of robust statistical modelling when gait data deviate from Gaussian distributions. These findings demonstrate a strong level of agreement between the proposed smartphone-based method and a clinically established wearable inertial system while supporting the practical applicability and robustness of the approach for quantitative gait assessment. The method provides gait parameters comparable to those obtained with a wearable reference system while maintaining stable performance across different walking conditions. Its low instrumentation requirements and applicability outside laboratory settings make it suitable for rehabilitation follow-up, fall risk assessment, and repeated gait evaluation over time.