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Background: Gait analysis is essential for diagnosing movement abnormalities, assessing therapy effectiveness, and optimizing athletic performance. Conventional gait laboratories using force platforms and multi-camera systems are expensive and require controlled laboratory environments. Inertial Measurement Unit (IMU) technologies such as Fitknees®, a wireless motion-sensing system, provide a portable and affordable alternative for real-time gait analysis. The primary objective was to evaluate the validity of Fitknees and its test-retest reliability against the video-based motion analysis system Kinovea.Methods: A cross-sectional comparison study was conducted in healthy adults. Validity analysis was performed on 12 participants (5 females, 7 males; aged 20–35 years), while 24 participants (10 females, 14 males) aged 23-51 years were included in the reliability analysis. Four Fitknees® sensors were positioned above and below both knees to capture lower-limb motion. Sensor data were transmitted wirelessly to a mobile application via Bluetooth while participants completed a 6-meter walking test at a self-selected speed. Temporal gait parameters, including stride time, stance time, and swing time, were recorded. These measurements were compared with corresponding values obtained from frame-by-frame analysis in Kinovea. For reliability assessment, participants completed four repeated gait trials, and measurement consistency was evaluated using Pearson correlation coefficients.Results: Fitknees® demonstrated excellent validity for left stride time compared with Kinovea (r = 0.937, p < 0.001). Moderate positive correlations were observed for stance time on both limbs (r = 0.641–0.627, p < 0.05). Although correlations for swing time were lower, the system showed moderate to high test–retest reliability across temporal parameters, as measured by the Pearson correlation coefficient. ranging from 0.54 to 0.79. These findings indicate that Fitknees® can reliably capture key temporal characteristics of gait.Conclusion: Fitknees® demonstrated strong validity for stride time and moderate validity for stance time, with consistent reliability across repeated gait trials. The results support the potential of wearable IMU-based systems for objective gait assessment, offering a portable alternative to traditional motion analysis approaches. Further refinement of sensor placement and signal processing algorithms may improve the detection of dynamic gait phases such as swing time.
Published in: International Journal of Physiotherapy
Volume 13, Issue 1