Measurement of Force Parametersfor the Human Gait Study

Abstract

The study focuses on the fabrication of shoe sensors (MSS) that provides important information about the dynamic movement of the lower limbs. In this study the kinematic model of human lower limbs was analyzed to know and detect the changes during human gait phase, that occurs when walking, based on the GRF. The sensors number, sensor type and location of sensors was chosen to proceed on the MSS device. The algorithm was developed based on COP that is able to detect the gait phase by means of three sensors. The standard deviation and mean for COPy and vGRF values are expressed on the basis of walk of the five testees. It includes 4 gait phases: initial contact IC (1), mid-stance MS (2), terminal stance TS (3), and swing (4), the gait cycle detection is expressed as an average value. The experimental work is conducted to estimate the manufactured shoe sensor device and to detect the gait phase algorithm and compare it to an F-Socket sensor device (FSS). The results of the MSS device fabrication were (MS - mean value was 9.49 ± 2.76%, TS - mean value was 29.46 ± 4.95% and the swing mean value was 62.50 ± 1.60%) and the pressure result (255.629 KPа) while the result of the (FSS) device were (MS - mean value was 10.98 ± 1.74%, TS - mean value was 30.43 ± 2.32 %, and the swing mean value was 60.69 ± 1.74 %) and the pressure result (259.618 KPа) respectively, the test results showed that the results obtained from the (MSS) device are close to the readings obtained by using the (FSS) device, this shows the (MSS) device accuracy of this study despite the fact that it has simple design and inexpensive.