Development of an automated foot contact area measurement program for podoscopes using ChatGPT-4: a case report.

Abstract

Accurate measurement of the foot contact area is crucial for diagnosing pes planus (flatfoot) and pes cavus (high arch), which significantly affect pressure distribution across the plantar surface. This study aimed to develop a program using ChatGPT-4 to automate foot contact area measurements using a podoscope, thereby enhancing diagnostic precision. A 53-year-old female volunteer stood on a podoscope to capture images of her feet, which were processed to isolate the foot contours and measure the contact areas. A program developed utilizing ChatCPT-4 was designed to outline the feet, detect contact areas, and calculate their sizes and ratios. The results demonstrated clear visualization of foot contours with automated calculation of the contact area and its ratio to the total foot area. The entire foot area measured 1,091,381.00 pixels, with a contact area of 604,252.50 pixels. The ratio of the ground contact area to the entire foot area was calculated as 55.37%. This method, which employs advanced image-processing techniques powered by ChatGPT-4, demonstrates the potential for integrating artificial intelligence into clinical applications. This approach could improve diagnostic precision and patient outcomes through personalized treatment strategies.