Estimation of Gait Parameters based on Motion Sensor Data

Recently, the spreading application of intelligent mobile devices with integrated sensors such as inertial measurement units (IMU) has attracted the interest of the researchers for designing gait analysis methods based on the captured sensor data. This paper focuses on designing a system which can evaluate the walking ability and the physical agility level of normal people and people with Parkinson's disease or stroke. The motion signal is collected by three wearable MPU9250 sensors located on both ankles and the center of the waist. Three test scenarios, including 10 meters walking test (10MWT), Time up and go test (TUGT) and Dual-task walking (DTW), are designed in this paper. The results, which concluded time parameters such as standing up time and turning back time as well as walking parameters such as stride length and stride frequency, showed good consistency and high accuracy with Vicon device.