Possibility of Application of the User Interface of a Conventional Smartphone for Communication of Graphical Information with a Special HW/SW Device

This article is focused on enhancement of HW/SW device by cooperation with a smartphone interface. The device was a programmable Lego Mindstorms Education EV3 set in the form of a robot designed to solve the Rubik’s Cube. The aim of the research was to replace the built-in color sensor with a camera that would allow the cube scanning process to be accelerated. Two approaches were chosen to meet the goal: the NXTcam camera, accessible as an accessory to expand the set, and the camera built into the smartphone. The use of NXTcam led to better scan time, but this result was prone to external influences. The camera on the smartphone sped up the scanning process to 57% of the original time. The impact of external factors on the outcome was significantly lower, compared to NXTcam. In the experiment, the cube solving process was observed in natural light, with addition distractive light source and in artificial light

Estimation of Quasi-Stiffness of the Human Hip in the Stance Phase of Walking

This work presents a framework for selection of subject-specific quasi-stiffness of hip orthoses and exoskeletons, and other devices that are intended to emulate the biological performance of this joint during walking. The hip joint exhibits linear moment-angular excursion behavior in both the extension and flexion stages of the resilient loading-unloading phase that consists of terminal stance and initial swing phases. Here, we establish statistical models that can closely estimate the slope of linear fits to the moment-angle graph of the hip in this phase, termed as the quasi-stiffness of the hip. Employing an inverse dynamics analysis, we identify a series of parameters that can capture the nearly linear hip quasi-stiffnesses in the resilient loading phase. We then employ regression analysis on experimental moment-angle data of 216 gait trials across 26 human adults walking over a wide range of gait speeds (0.75–2.63 m/s) to obtain a set of general-form statistical models that estimate the hip quasi-stiffnesses using body weight and height, gait speed, and hip excursion. We show that the general-form models can closely estimate the hip quasi-stiffness in the extension (R(2) = 92%) and flexion portions (R(2) = 89%) of the resilient loading phase of the gait. We further simplify the general-form models and present a set of stature-based models that can estimate the hip quasi-stiffness for the preferred gait speed using only body weight and height with an average error of 27% for the extension stage and 37% for the flexion stage