On the Utilization of Commodity Devices for Efficient Gait Asymmetry Detection

This work explores the feasibility and accuracy of using mobile phone's Inertial Measurement Unit (IMU) sensors to detect gait asymmetries between the lower limbs in a real-world environment. The primary objective is to develop a cost-effective and easily accessible method for identifying gait events that can aid in early diagnosis and monitoring of conditions that affect gait, such as stroke. A 10-second walk test was used for gait assessments with a single phone, positioned in the front thigh pants pockets, first from the right leg and then the left leg. The phone accelerometer and gyroscope data were recorded at 20 Hz in three trials of four gait strategies. The system is based on a mobile application for reading the onboard IMU sensor data and a cloud platform for data manipulation. The system identifies gait cycle events and can detect inconsistencies between right and left leg gait cycles. Our findings suggest that commodity devices can be a viable alternative for gait asymmetry detection, offering a solution for easy and reliable gaits assessments and remote patient monitoring. Future work will involve validation against Gold Standard methods and stroke patients” assessment.