Innovations within the medical device sector are constantly and rapidly emerging due to increasing demand, especially for orthosis systems, which usually constitute built rigids with low comfort, due mainly to the standardized production process. This article reports the design process of a plantar orthosis system from the application of Theory of Inventive Problem Solving (TRIZ) tools, known as generic parameters, matrix of contradictions, and inventive principles. The final orthosis is integrated by four modules or components (1 central and 3 movables) and customers can buy only the required ones, reducing cost in unnecessary parts. The plantar orthosis was defined based on three engineering parameters that delimited the design work by developing a customizable system that is capable of performing simultaneous functions and whose manufacture could be standardized. We identified the existence of a technical contradiction between the engineering parameters, customization, and standardization, which was solved by the inventive principles of segmentation, inversion, transition to a new dimension, and porous materials. A modular design with four components was accomplished, molds are built for each component in a machining center and injected using granulated ethylene vinyl acetate copolymer. The positions of the movable components are configured through a bolt-hole assembly mechanism to the central component, which is a flat perforated plantar base. The novelty in the design here presented is elated to supports that constitute the orthosis, which are interchangeable and adjustable to the pathological and morphological needs of each patient.

The anatomical structure of the foot can be assessed by examining the plantar footprint for orthopedic intervention. In fact, there is a relationship between a specific type of foot and multiple musculoskeletal disorders, which are among the main ailments affecting the lower extremities, where its accurate classification is essential for early diagnosis. This work aims to develop a method for accurately classifying the plantar footprint and hindfoot, specifically concerning the sagittal plane. A custom image dataset was created, comprising 603 RGB plantar images that were modified and augmented. Six state-of-the-art models have been trained and evaluated: swin_tiny_patch4_window7_224, convnextv2_tiny, deit3_base_patch16_224, xception41, inception-v4, and efficientnet_b0. Among them, the swin_tiny_patch4_window7_224 model achieved 98.013% accuracy, demonstrating its potential as a reliable and low-cost tool for clinical screening and diagnosis of foot-related conditions.