Smartphone Clinical Practice in Gait Analysis

By Sarah A. Curran, PhD

Smartphones have revolutionized clinical practice through enhancement of communication with colleagues and patients, information access, and workflow efficiency for healthcare providers. With the continuous evolution of technology, smartphones have increasingly been used for assessing gait—providing a convenient and accessible way to monitor mobility, balance, and walking patterns. Gait assessment using smartphones typically involves using built-in sensors, such as accelerometers, gyroscopes, and magnetometers, which can capture detailed motion data. In essence, the use of smartphones for gait assessment has been linked to a growing body of research with several studies providing evidence supporting its validity and reliability, as well as application to a range of conditions. In a review of wearable devices and smartphones for gait analysis, Muro-de-la-Herran et al¹ found that smartphone sensors, particularly accelerometers and gyroscopes, were able to reliably capture gait parameters such as step length, cadence, and velocity. They concluded that smartphones could be a valid alternative to more traditional motion capture systems for basic gait assessment in non-laboratory settings.

Storm et al² validated the use of smartphone accelerometers to estimate spatiotemporal gait parameters in a group of healthy individuals. The authors found, when worn at the waist, smartphones provided estimates of gait speed, step length, and cadence with accuracy comparable to clinical tools such as the GAITRite system (CIR Systems, Inc.; New Jersey, USA), a commonly used gait analysis tool in rehabilitation. These findings are further supported by a most recent study by Tao and colleagues³ who developed a WeChat mini-program (MobileGait) and used smartphone sensors to determine reliability and validity with healthy individuals, and to demonstrate the impact on gait parameters during single-task and dual-task walking in a cohort of cerebral small vessel disease patients. Additional studies have been undertaken in other patient populations, which includes the risk of falls prediction in older adults. Using smartphone sensors, Del Din et al⁴ demonstrated that gait characteristics measured correlated well with clinical fall risk assessments, such as the Timed Up and Go test. Such findings can serve as a cost-effective and scalable solution for early detection of fall risk. Likewise, Su et al⁵ investigated the potential of smartphone-based gait analysis to monitor Parkinson’s disease progression. They showed that smartphone sensors could detect subtle changes in gait related to disease severity, such as reduced stride time and variability during single-task and dual-task conditions, making it a valuable tool for monitoring functional symptoms and outcomes.

While these studies are not an exhaustive list, they do collectively demonstrate that smartphones, with their ubiquitous availability and advanced sensor technology, are a practical and effective tool for gait assessment across a range of settings and populations. As technology evolves and becomes more accessible, so will our ability to work with it to enhance our patient assessments and outcomes, as well as to monitor rehabilitation.

Prof. Sarah A. Curran, PhD, Professor of Podiatric Medicine and Rehabilitation, School of Sport and Health Sciences, Cardiff Metropolitan University, UK