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Abstract
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OBJECTIVE: This study aims to validate the reliability and validity of gait analysis using smartphones in a controlled environment.
METHODS: Thirty healthy adults attached smartphones to the waist and thigh, while an inertial measurement unit was fixed at the shank as a reference device; each participant was asked to walk six gait cycles at self-selected low, normal, and high speeds. Thirty-five cerebral small vessel disease patients were recruited to attach the smartphone to the thigh, performing single-task (ST), cognitive dual-task (DT(1)), and physical dual-task walking (DT(2)) to obtain gait parameters.
RESULTS: The results from the healthy group indicate that, regardless of whether attached to the thigh or waist, the smartphones calculated gait parameters with good reliability (ICC(2,1) > 0.75) across three different walking speeds. There were no significant differences in the gait parameters between the smartphone attached to the thigh and the IMU across all three walking speeds (P > 0.05). However, significant differences were observed between the smartphone at the waist and the IMU during the stance phase, swing phase, stance time, and stride length at high speeds (P < 0.05). At the same time, measurements of other gait parameters were similar (P > 0.05). Patients demonstrated significant differences in the cadence, stride time, stance phase, swing phase, stance time, stride length, and walking speed between ST and DT(1) (P < 0.05). Significant differences were observed in the stance phase, swing phase, stride length, and walking speed between ST and DT(2) (P < 0.05).
CONCLUSIONS: This study demonstrates the feasibility of using built-in smartphone sensors for gait analysis in a controlled environment.
Language: en |