Embedded foot plantar classification system using Raspberry Pi

摘要

Foot plantar classification is crucial to prevent dangers to patient's health that originated from an abnormal type of foot. When patients comprehend their type of foot, they will be able to form personal insole to prevent a hazard. On the contrary, some patients who ignore their risk will possibly have the problem. We design the system to classify type of foot by measuring foot pressure and foot curvature. For the software, we use webcams to capture the foot images that will be further processed by Raspberry Pi with OpenCV and color coding which correspond to foot pressure. For the hardware system, we use the component which is inexpensive and easily available. The hardware structure is composed of steel as a base where the transparent acrylic plate and glossy white paper is placed on. The black polypropylene sheet covering on the uppermost is used to block light from outside. Aligned on the side of the transparent acrylic plate LED strip is used for light source for the system. Underneath the steel base there are four webcams which is used to record feet images (two webcams for each foot). The images are sent to Raspberry Pi for image processing and displaying. The system is able to classify three types of the foot for patients including normal foot, high arch foot, and flat foot.