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Development of Mobile Application Based on AI for Predicting the Suitable Height of High Heels

Min-Shiuan Lee, Bor-Shyh Lin, Hsin-Lung Wu

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed

    Abstract:

    As high heels become increasingly popular in everyday attire, their impact on foot and lower limb health has garnered widespread attention. Wearing high heels of inappropriate height over a long period can cause damage to an individual's ankles, knees, and spine. This study developed a mobile application based on YOLOv8, aimed at providing users with personalized recommendations for the maximum height of high heels, thereby reducing the health risks associated with long-term wear of high heels. Compared to the previous generation system we developed, this generation's system simplifies the analytical process and has a lightweight model that has been ported to mobile devices, greatly enhancing usability and privacy. We validate and discuss the experimental results to confirm that our system has improved predictive capabilities. The error of the proposed system is only a mean absolute error of 0.76 cm. Users only need to record a video of their elevated heels and input it into the mobile application to measure the maximum height of high heels, thus minimizing the damage to lower limb health caused by high heels.

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