FootSense is a foot pressure-sensing system built using an array of load cells placed at key pressure points across a foot mat or insole (heel, arch, and forefoot/toe regions). As a person stands or walks on the mat, the load cells measure the force exerted at each point in real time. This data is read and processed by a Speed Studio microcontroller, which: Collects pressure readings from each load cell continuously Compares the distribution pattern across the foot to known healthy pressure profiles Identifies abnormal patterns associated with specific conditions, including: Flat feet / arch issues — detected via abnormal pressure in the arch region Uneven weight distribution — detected via asymmetry between left/right or front/back pressure zones Diabetic foot pressure ulcer risk — detected via sustained high-pressure concentration at specific points General gait abnormalities — detected via irregular pressure shifts during walking When an abnormal pattern is detected, the system can alert the user, allowing them to seek further evaluation or adjust their posture/footwear before the issue worsens. The combination of low-cost load cells and a compact microcontroller makes Foot Sense significantly cheaper and more accessible than clinical pressure-mapping systems, while still providing useful, actionable insights. 

Inspiration: Foot Sense was inspired by the gap between expensive clinical foot-pressure diagnostics and the lack of any affordable home-monitoring alternative — particularly for diabetic patients, where early detection of pressure points can prevent serious complications like ulcers and infections. System components: Gel insole with embedded FSR pressure sensors, an external module (ESP32 + MPU6050 IMU) for processing and motion sensing, and a mobile app for visualization and analysis. 3D printed parts: Custom enclosure for the electronics, an insole sensor support layer, a wire routing channel, and a protective sensor layer — all designed for durability and comfort. Optional feedback: Vibration motor for real-time alerts when an unsafe gait pattern is detected. Use cases: Injury prevention and recovery, posture correction, and athletic training/performance insights.