Abstract

Abstract
In this article we present a smart textile system for the continuous monitoring of cardiorespiratory signals, produced and integrated with an industrial embroidery unit. The design of a T-shirt system, having embedded textile sensors and interconnects and custom designed circuit for data collection and Bluetooth transmission is presented. The performance of skin-contact textile electrodes, having distinctive electrical characteristics and surface morphologies, was characterized by measurements of signal to noise ratio, under dry and moisture conditions. The influence of the electrodes size and the wear resistance were addressed. Results of an electrocardiogram acquisition with a subject wearing the T-shirt and display on a smartphone are also shown. The presented smart textile systems exhibit good performance and versatility for custom demand production.

Abstract
One of the currently available treatments for aortic aneurysms is endovascular aneurysm repair (EVAR). In spite of major advances in the operating techniques, complications still occur and lifelong surveillance is recommended. In order to reduce and even eliminate the commonly used surveillance imaging exams, as well as to reduce follow-up costs, new technological solutions are being pursued. In this paper, we describe the development, including design and performance characterization, of a flexible remote pressure measurement system based on inductive-coupling for post-EVAR monitoring purposes. The telemetry system architecture and operation are described and main performance characteristics discussed. The implantable sensor details are provided and its model is presented. Simulations with the reading circuit and the sensor's model were performed and compared with measurements carried out with air and a phantom as media, in order to characterize the telemetry system and validate the models. The transfer characteristic curve (pressure versus frequency) of the monitoring system was obtained with measurements performed with the sensor inside a controlled pressure vacuum chamber. Additional experimental results which proof the system functionality were obtained within a hydraulic test bench that emulates the aorta. Several innovative aspects, when compared to the state of the art, both in the sensor and in the telemetry system were achieved.

Abstract
A new methodology for fault detection on wearable medical devices is proposed. The main strategy relies on correctly classifying the captured physiological signals, in order to distinguish whether the actual cause is a wearer health abnormality or a system functional flaw. Data fusion techniques, namely fuzzy logic, are employed to process the captured data, like the electrocardiogram and blood pressure, to increase the trust levels with which diagnostics are made. Concerning the wearer condition, additional information is provided after classifying the set of signals into normal or abnormal (e.g. arrhythmia, chest angina, and stroke). As for the monitoring system, once an abnormal situation is detected in its operation or in the sensors, a set of tests is run to check if actually the wearer shows a degradation of his health condition or if the system is reporting erroneous values.

Abstract
The present work addresses the development of a smart orchard irrigation system (SOIS) that performs the estimation of orchard evapotranspiration and the estimation of the soil salinization risk. Measurements of heat transfer are made to compute tree transpiration rate and soil water evaporation. The soil electrical conductivity is measured to compute the soil salinization risk. An inferential fuzzy algorithm is used to process data. This paper describes the physical principles underlining these estimations, the architecture of the data acquisition interface, and the construction and characterization of the probes used to perform the temperature measurements. The preliminary results shown here address the experimental evaluation of the performance of the probes inserted in the trees. Relative measurements with a precision of 0.2 degrees C were obtained which are in agreement with the minimum required for these applications.

Abstract
Wearable vital signals monitoring systems are promoting new assistance approaches in the healthcare system and are essential for the future connected health paradigm. The present work addresses the design of a cardiac and coronary monitoring system taking into consideration dependability and autonomy issues. A fuzzy logic approach is used to determine, in case deviations in the captured electrocardiogram are detected, whether these are occurring in the patient or in the system. As for autonomy, the use of data compression versus extra data processing balance is analysed to find operating conditions for which compression is worth to be used.