Flatfoot Detection in an Indian Population: Validation of Morphological Indices Using a Diagnostic Device

Flatfoot, or pes planus, is a condition where the foot’s arch collapses, leading to complications such as pain, gait abnormalities, and an increased risk of injury. Accurate and early diagnosis is critical for effective treatment. Traditional diagnostic methods, including radiographic imaging, footprint analysis, and plantar pressure measurement, often require specialized equipment and are subjective. This study proposes a novel diagnostic device that captures 2D plantar foot images to calculate key morphological indices, including the Staheli Index, Clark’s Angle, and Chippaux–Smirak Index, for flatfoot detection. The device, designed with off-the-shelf components, includes a transparent toughened glass platform and LED illumination to capture images using web cameras. A Python-based application was developed for image acquisition, segmentation, and stitching. The device was tested on 55 participants aged 18–28, and the extracted morphological indices were validated against established thresholds for flatfoot diagnosis. The results showed that the Staheli Index, Chippaux–Smirak Index, and Clark’s Angle reliably detected flatfoot in participants. The study highlights the potential of this device for non-invasive, accurate, and rapid flatfoot diagnosis. Future advancements in deep learning could enhance its capabilities, making it a valuable tool for proactive healthcare in foot deformity detection.