| Summary: | Heel-strike (HS) and toe-off (TO) events are crucial in gait analysis, assessing various parameters like gait cycle time, stance time, swing time, single support time, and double support time. These metrics aid in diagnosing medical conditions and post-surgery biomechanical stability. However, current evaluation methods often rely on costly laboratory setups, limiting accessibility. We propose an innovative approach using wearable sensor technology, integrating an Inertial Measurement Unit (IMU) sensor (MPU6050) and the NodeMCU microcontroller (ESP8266). Our primary goal is to accurately detect HS and TO events during normal human gait analysis. We employ two MPU6050 sensors on both shanks, collecting gait signals as participants walk a 40-meter distance. The collected data is wirelessly transmitted by the ESP8266 microcontroller to the 'Blynk' IoT application through a Wi-Fi module. The Blynk app displays precise timing (in seconds) of HS and TO events on a smartphone, offering insights into biomechanical stability and disease diagnosis. This project emphasizes continuous gait monitoring through IoT integration, enabling more flexible and accessible gait analysis with wearable sensors. Our results demonstrate the promising applications of this approach in research, enhancing understanding and accessibility of human gait dynamics. © 2023 IEEE.
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