KineFeet, a Novel Depth Camera-Based Web Application for Diagnosing Foot Kinematics Alterations
-
Fitri Anestherita
,
Angela Bibiana Maria Tulaar
,
Maria Regina Rachmawati
,
Em Yunir
,
Dante Saksono Harbuwono
,
Retno Asti Werdhani
,
Ahmad Yanuar Safri
,
Muhammad Febrian Rachmadi
,
Muhammad Hanif Nadhif
,
Azwien Niezam Hawalie Marzuki
,
Luh Karunia Wahyuni
,
Nelfidayani .
,
Boya Nugraha
Abstract
Introduction: Altered foot kinematics during walking, including reduced tibial inclination (the angle between the tibia and a vertical line during gait), as well as medial longitudinal arch (MLA) flattening and first metatarsophalangeal (MTP1) extension angle, have been linked to various musculoskeletal disorders. Such abnormalities can have significant clinical implications; therefore, it is crucial to accurately identify them.
Materials and Methods: We aimed to assess the diagnostic accuracy of KineFeet, a web-based application that employs a depth camera technique to detect foot kinematic changes for human gait analysis. KineFeet software, version 1.3 and Kinovea gait analysis software, version 2023.1.2 were used to diagnose altered foot kinematics in 89 healthy participants in this cross-sectional study. The main kinematic parameters investigated were the ankle inclination angle at terminal stance (AI_TSt), the MLA angle at terminal stance (MLA_TSt), and the MTP1 angle 1 at maximal hallux extension (MTP_HE). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the receiver operating characteristic (ROC) area under the curve (AUC) were computed.
Results: KineFeet showed excellent diagnostic performance. AI_TSt had a sensitivity of 88.23% and a specificity of 95.83%, with PPV and NPV values of 83.33% and 97.18%, respectively (AUC=0.97). MLA_TSt and MTP_HE also had high discriminative abilities, with sensitivities of 79.54% and 79.00%, specificities of 95.55% and 91.30%, and attributed AUCs of 0.94 and 0.91, respectively.
Conclusion: KineFeet can accurately detect foot kinematic deformities during human gait. Its high diagnostic accuracy makes it a promising screening and evaluation tool. Further studies on human gait pathologies are warranted.
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| Issue | Vol 20 No 1 (2026) | |
| Section | Research Article(s) | |
| DOI | https://doi.org/10.18502/jmr.v20i1.21025 | |
| Keywords | ||
| Gait analysis Foot Computer-assisted diagnosis Kinematics | ||
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