Well-established connections exist between increased gait variability and greater fall likelihood in human movement. Therefore, the assessment of gait symmetry can facilitate clinicians' decision-making in the treatment and evaluation of the progression of several diseases. This study proposed a workflow that used two self-developed inertial sensing measurement units (IMU) to collect the lower limb gait data of five subjects and then extracted the gait characteristic parameters to quantify the running process during a single-task condition and a dual-task condition, which requires additional cognitive loads (counting numbers backward). The results showed that the absolute value of the symmetry index under dual-task conditions (0.207±0.032) was greater than that of single-task conditions (0.149±0.109). The variability indices of the legs were reduced and the outliers of the asymmetry indices were significantly higher in the dual-task gait. This study revealed changes in gait symmetry and variability under dual-task gait conditions and found that human gait improved under dual-task conditions at high speeds, which can be instructive for gait quality improvement. In the future, the experimental conditions will be extended to include single-gait mode as well as walk-run and run-walk cross-gait modes to further validate the relationship between dual-task conditions and changes in gait characteristics.
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