Bend and Moisture Effects on the Performance of a U-Shaped Slotted Wearable Antenna for Off-Body Communications in an Industrial Scientific Medical (ISM) 2.4 GHz Band.

In recent years, the study and design of wearable antennas have been empowered given the success of Wireless Body Area Networks (WBAN) for healthcare and medical purposes. This work analyses a flexible textile antenna whose performance can be optimised by the careful selection of the substrate thickness of the textile material, and by varying the antenna's geometrical shape. After considering these parameters, several arrangements of antennas were simulated using the Computer Simulation Technology software (CST). The results of the simulations were compared to the experimental prototypes manufactured on a flexible felt material for a range of thicknesses and curvatures of the antenna substrate. Such antenna designs can be utilised in off-body communications and ISM applications.

Analysis of Water, Ethanol, and Fructose Mixtures Using Nondestructive Resonant Spectroscopy of Mechanical Vibrations and a Grouping Genetic Algorithm.

A new haptic sensor that is based on vibration produced by mechanical excitation from a clock coupled to a resonant cavity is presented. This sensor is intended to determine the chemical composition of liquid mixtures in a completely non-destructive method. In this case, a set of 23 samples of water, ethanol, and fructose mixtures has been used to simulate different kinds of alcoholic beverage. The spectral information from the vibrational absorption bands of liquid samples is analyzed by a Grouping Genetic Algorithm. An Extreme Learning Machine implements the fitness function that is able to classify the mixtures according to the concentration of ethanol and fructose. The 23 samples range from 0%⁻13% by volume of ethanol and from 0⁻3 g/L of fructose, all of them with different concentration. The new technique achieves an average classification accuracy of 96%.