Footprint detection method for spatiotemporal gait parameters on the GAITRite walkway: a validation study

This paper presents the development and reliability assessment of an algorithm for gait footprint detection on a pressure-sensitive walkway. The detected footprints enable the calculation of spatiotemporal gait parameters on the GAITRite\u00ae walkway, providing clinicians with quantitative data to support objective gait analysis. Six healthy adults (mean age: 28 \u00b1 6.94 years) performed a total of 360 walking trials, with 32 spatiotemporal parameters analyzed. The comparison was performed against the previous GAITRite algorithm, which is considered the gold standard for clinical gait analysis. The new algorithm improves the robustness of the calculation while preserving a footprint visualization that more closely reflects the actual shape of the foot. Reliability was assessed using Intraclass Correlation Coefficients (ICC 2,1),while agreement was evaluated with Bland-Altman plots and percentage of errors. Results demonstrated excellent reliability for all parameters (ICC \\(> 0.75\\))minimal mean bias and clinically acceptable percentage errors (\\(<30\\%\\)) for all the parameters. However, the parameter foot progression angles exhibited higher percentage errors (left: 66.36\\%, right: 67.02\\%), attributed to differences in footprint detection and progression axis computation between the algorithm versions. Nevertheless, the new algorithm values maintain strong agreement with those of the previous version, ensuring consistency and validity in clinical and research applications, while potentially offering a more natural representation of foot orientation.