Running Gait Posture Optimization Using Embedded IoT Sensor Shoes

Running is an essential human exercise that one has access to anytime and anywhere. Compared to its easy accessibility, running carries a risk of developing running related injury (RRI). RRI is caused by many factors, such as anthropometric and personal physical data, injury history, training analysis, footwear, and anatomic malalignment. In order to reduce the occurrence rate of RRI, the document suggests a running gait monitoring wearable IoT device and Mobile application. While several research papers have discussed how to monitor the running gait posture by using motion capture, they overlooked one crucial part; the motion-capturing system is restricted by time and space. This research proposes a running gait monitoring system using an Inertial Measurement Unit (IMU) sensor and Force Sensitive Resistor (FSR). Using these sensors, the IoT cloud platform processes streams of the sensor data using algorithms to extract kinematic parameters. Users are able to monitor the angle of their foot and the initial contact location on the foot for each step while running. Providing innovative application visualizes analyzed feature extraction running gait data and receives the level of training intensity of running for the user. This paper aims to provide support for runners to reduce the occurrence rate of RRI and visualization of the analyzed running gait data received from the wearable IoT device.