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.

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Publication Details

Journal
Medical Engineering & Physics
Published
2026-07-17
DOI
https://doi.org/10.1088/1873-4030/ae8c43
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
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article

Comparative Evaluation of a Smartphone-Based Inertial Measurement Approach for Quantitative Gait Analysis

Gracián Triviño, Erdoğan Kavlak, Fatma Nur Altin
Medical Engineering & Physics
Balance, Gait, and Falls Prevention
article

Comparative Evaluation of a Smartphone-Based Inertial Measurement Approach for Quantitative Gait Analysis

Gracián Triviño, Erdoğan Kavlak, Fatma Nur Altin
article en

Abstract

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.

Medical Engineering & Physics
Pamukkale University (TR), Adnan Menderes University (TR)
Openalex Percentile: Top 4%
Balance, Gait, and Falls Prevention
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