Osteoarthritis sufferers commonly have first metatarsophalangeal joint (MTPJ) problems in which articular surfaces are changed permanently due to fatigue. Therefore, medical devices for early diagnosis would increase the opportunity for prevention of disease progression. In previous studies on stiffness of the first MTPJ many details, although functionally of great importance, have not been fully considered including: design and size of the device, tribology consideration, and errors from device. Therefore, the motivation of our research was to enhance the device design by reducing the size of the device, and device design was enhanced by minimizing measurement errors through development of a new ergonomic left and right foot instrument located medial to the first MTPJ (instead of beneath the foot). The first MTPJ stiffness (N mm/kg radian) measurement was taken on 28 subjects with two replicates per subject by the same tester. The first MTPJ stiffness ranged from 3.49 to 14.42 N mm/kg radian with the mean (SD) value of 8.28 (3.15) N mm/kg radian for the left feet and 3.91 to 11.90 N mm/kg radian with the mean (SD) value of 7.65 (2.07) N mm/kg radian for the right feet. Reliability evaluation was measured using intraclass correlation coefficient and described an excellent reliability between two tests.

No abstract

This paper addresses the stability and tracking control problem of quadrotor unmanned flying vehicle (UAV) in the presence of uncertainty. Adaptive autonomous sliding mode tracking system is designed by combining robust and adaptive control theory. Lyapunov analysis shows that the proposed algorithms can guarantee asymptotic convergence of the tracking error of the linear and angular motion dynamics of the vehicle. Compared with other existing adaptive backstepping design, the proposed method is very simple and easy to implement on an actual system as it does not require multiple design steps without augmented signals and a priori known bound of the uncertainty. To illustrate the theoretical argument, evaluation results on custom made quadrotor UAV system are presented for real-time applications.

In this paper, we deal with the stability and tracking control problem of quadrotor unmanned aerial vehicle (UAV) in the presence of the modeling error and disturbance uncertainty. The flight tracking control system combines classical proportional-derivative (PD) like term with robust and adaptive control term. Lyapunov method is used to design and show the asymptotic behavior of the linear and angular states of the vehicle. In contrast with other existing adaptive backstepping design, the proposed design is very simple and easy to implement as it does not require multiple design steps without using augmented signals and known bound of the uncertainty. Various experimental results on quadrotor UAV system are presented to demonstrate the effectiveness of the proposed design for real-time application.Index Terms-Quadrotor Unmanned Aerial Vehicle; Lyapunov Method; Robust Adaptive Control.

In this paper, a vision guidance system for automated weed detection robot is presented. The developed vision system use series of image processing techniques to detect the inter-row space between the crops and then calculate the current pose and orientation with the help of Hough transform. The dynamic model is used for evolution of values over time and to predict the changes in pose and orientation from frame to frame. The vision system is implemented and simulated in Matlab, and it is observed that the developed system successfully detects and calculates the pose and orientation of the crop boundaries on both real and synthetic images.