DUO-GAIT: A Gait Dataset for Walking under Dual-Task and Fatigue Conditions with Inertial Measurement Units

This dataset is associated with a data descriptor that is currently under peer review. 

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In recent years, there has been a growing interest to develop and evaluate gait analysis algorithms based on inertial measurement unit (IMU) data, which has important implications including sports, assessment of diseases, and rehabilitation. Multi-tasking and physical fatigue are two relevant aspects of daily life gait monitoring, but there is a lack of publicly available datasets to support the development and testing of methods using a mobile IMU setup. We present a dataset consisting of 6-minute walks under single- (only walking) and dual-task (walking while performing a cognitive task) conditions in non-fatigued and fatigued states from sixteen healthy adults. Especially, nine IMUs were placed on the head, chest, lower back, wrists, legs, and feet to record under each of the above-mentioned conditions. The dataset also includes a rich set of spatio-temporal gait parameters that capture the aspects of pace, symmetry, and variability, as well as additional study-related information to support further analysis. This dataset can serve as a foundation for future research on gait monitoring in free-living environments.