Psychometric Characteristics of Smartphone-Based Gait Analyses in Chronic Health Conditions: A Systematic Review

TL;DR

This review evaluates how well smartphones can assess gait in people with chronic conditions, finding them promising but needing better standardization.

Contribution

The study systematically reviews psychometric properties of smartphone-based gait analysis for chronic conditions, highlighting variability and gaps in reliability.

Findings

Smartphone apps showed moderate-to-strong validity compared to gold-standard systems for gait speed and stride length.

Reliability varied widely, with ICCs ranging from 0.53 to 0.95 for spatiotemporal parameters.

Feasibility was rated positively in 94% of studies, emphasizing smartphone advantages in diverse settings.

Abstract

Background: Chronic health conditions frequently result in gait disturbances, impacting quality of life and mobility. Smartphone-based gait analysis has emerged as a promising alternative to traditional methods, offering accessibility, cost effectiveness, and portability. This systematic review evaluates smartphone-based inertial measurement units’ validity, reliability, and sensitivity for assessing gait parameters in individuals with chronic conditions. Methods: A comprehensive literature search in Web of Science, PubMed, Google Scholar, and SportDiscus identified 54 eligible studies. Results: Validity was evaluated in 70% of the included studies, with results showing moderate-to-strong associations between smartphone apps and gold-standard systems (e.g., Vicon), particularly for parameters such as gait speed and stride length (e.g., r = 0.42–0.97). However, variability was evident across studies depending on the health condition, measurement protocols, and device placement. Reliability, examined in only 27% of the included studies, displayed a similar trend, with intraclass correlation coefficients (ICCs) ranging from moderate (ICC = 0.53) to excellent (ICC = 0.95) for spatiotemporal parameters. Sensitivity and specificity metrics were explored in 41% and 35% of the included studies, respectively, with several applications achieving over 90% accuracy in detecting gait abnormalities. Feasibility was rated positively in 94% of the included studies, emphasising the practical advantages of smartphones in diverse settings. Conclusions: The findings of this systematic review endorse the clinical potential of smartphones for remote and real-world gait analysis, while highlighting the need for standardised methodologies. Future research should adopt a more comprehensive approach to psychometric evaluation, ensuring that reliability aspects are adequately explored. Additionally, long-term studies are needed to assess the effectiveness of smartphone-based technologies in supporting the personalised treatment and proactive management of chronic conditions.

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