Semnan University Press Journal of Modeling and Simulation in Electrical and Electronics Engineering 2821-0786 5 4 2025 12 01 Design and Validation of a Pressure-Based Insole for the Quantitative Assessment of Gait Abnormalities 1 8 10241 10.22075/mseee.2025.37831.1214 EN Maryam Farivar Technical and Vocational Training Organization, Isfahan, Iran. Hadi Soltanizadeh Electrical and Computer Engineering Faculty, Semnan University, Semnan, Iran. Mohammad Zahrayee Shahid Beheshti University, Medical Science, Tehran, Iran. Journal Article 2025 05 24 This study presents the design and validation of a wearable in-shoe system for real-time monitoring and quantitative analysis of plantar pressure distribution during walking. The system incorporates ten force-sensitive resistor (FSR) sensors strategically placed at key anatomical regions of each foot, enabling high-resolution pressure mapping. Data acquisition and wireless transmission are managed via an ESP32 microcontroller using TCP/IP protocol, with onboard microSD storage for redundancy. A custom graphical user interface (GUI), developed in Delphi, enables live visualization and recording. It also supports signal processing techniques, including dynamic time warping (DTW) for temporal alignment and signal averaging for noise reduction. Experimental trials were conducted on four adult participants (aged 22–45), including one individual with a normal gait and three with abnormal patterns, such as internal rotation, external rotation, and supination. Each participant completed multiple walking trials on a treadmill at a constant speed for a duration of 1 minute under standardized footwear conditions. The results confirmed that the system achieved high accuracy in distinguishing gait abnormalities, validated through quantitative metrics and visual pressure profiles. The proposed system provides a low-cost, portable, and clinically relevant solution for early detection of gait disorders and long-term rehabilitation monitoring. Its modular architecture and real-time performance demonstrate its potential as an effective tool for both clinical and remote rehabilitation monitoring. https://mseee.semnan.ac.ir/article_10241_68b6e0792dbdfaf28a26950ec28ad3c6.pdf