کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6207208 | 1265655 | 2011 | 5 صفحه PDF | دانلود رایگان |
In human motion analysis, in situ calibration of the force plate is necessary to improve the accuracy of the measured ground reaction force (GRF) and center of pressure (COP). Few existing devices are capable of both static and dynamic calibration of the usually non-linear GRF and COP errors, while are also easy to move and/or set up without damaging the building. The current study developed a small device (160 cm Ã 88 cm Ã 43 cm) with a mass of 50 kg, equipped with auxiliary wheels and fixing suction pads for rapid deployment and easy set-up. A PC-based controller enabled quick movement and accurate positioning of the applied force to the calibration point. Static calibration at 100 validation points and dynamic calibration of a force plate were performed using the device. After correction by an artificial neural network (ANN) trained with the static data from another 121 points, the mean errors for the GRF were all reduced from a maximum of 0.64% to less than 0.01%, while those for the COP were all reduced from a maximum of about 1.37 mm to less than 0.04 mm. For dynamic calibration, the mean errors for the GRF were reduced from a maximum of 0.46% to less than 0.28%, while those for the COP were reduced from a maximum of 0.95 mm to less than 0.11 mm. The results suggest that the calibration device with the ANN method will be useful for obtaining more accurate GRF and COP measurements in human motion analysis.
Journal: Gait & Posture - Volume 33, Issue 4, April 2011, Pages 701-705