Over the last few years, the gap between FPGA and ASIC performance levels have been narrowed due to the constant development of FPGA technology. The high performance, together with lower development costs and a shorter time-to-market, turns FPGA based platforms attractive for a huge range of applications, among them, Time-to-Digital Converters (TDCs). It is therefore important to analyse the evolution of FPGA-based TDCs, to better understand where the research efforts should be focused in the near future. This work presents and discusses the improvements on the FPGA-based TDC research, aiming to be a starting point for new studies on this field, with some guidelines for future research. A state-of-the-art literature review on FPGA-based TDC is presented, aiming to categorize and discuss the existing architectures. This discussion addresses architectures characteristics, limitations and areas of application.

High-resolution pull-in-based microelectromechanical system (MEMS) inclinometers are presented in this paper. Pull-in is characterized by the sudden loss of stability in electrostatically actuated parallel-plate structures, and since pull-in voltage is stable and easy to measure, it enables an effective transduction mechanism that does not require complex and stable capacitive readout electronics. The MEMS devices used to test the novel architecture have differential actuation electrodes resulting in two pull-in voltages that change differentially with applied acceleration. Dedicated MEMS microstructures with extra proof mass show high sensitivity; 269 mV/° with a nonlinearity <;0.5% FS (Full Scale of ±23°). The measured noise is limited by the actuation mechanism, setting the sensor's resolution at 75 $\mu$ °; high above state-of-the-art MEMS devices. [2014-0156].

Several devices and measurement approaches have recently been developed to perform ballistocardiogram (BCG) and seismocardiogram (SCG) measurements. The development of a wireless acquisition system (hardware and software), incorporating a novel high-resolution micro-electro-mechanical system (MEMS) accelerometer for SCG and BCG signals acquisition and data treatment is presented in this paper. A small accelerometer, with a sensitivity of up to 0.164 µs/µg and a noise density below 6.5 µg/ $\sqrt{\mathrm{Hz}}$ is presented and used in a wireless acquisition system for BCG and SCG measurement applications. The wireless acquisition system also incorporates electrocardiogram (ECG) signals acquisition, and the developed software enables the real-time acquisition and visualization of SCG and ECG signals (sensor positioned on chest). It then calculates metrics related to cardiac performance as well as the correlation of data from previously performed sessions with echocardiogram (ECHO) parameters. A preliminarily clinical study of over 22 subjects (including healthy subjects and cardiovascular patients) was performed to test the capability of the developed system. Data correlation between this measurement system and echocardiogram exams is also performed. The high resolution of the MEMS accelerometer used provides a better signal for SCG wave recognition, enabling a more consistent study of the diagnostic capability of this technique in clinical analysis.

An open-source tool that allows for a fast and precise analytical calculation of multi-layer planar coils self-inductance, without any geometry limitation is proposed here. The process of designing and simulating planar coils to achieve reliable results is commonly limited on accuracy and or geometry, or are too time-consuming and expensive, thus a tool to speed up this design process is desired. The model is based on Grover equations, valid for any geometry. The validation of the tool was performed through the comparison with experimental measurements, Finite Element Model (FEM) simulations, and the main analytical methods usually used in literature, with errors registered to be below $2.5\%$, when compared to standard FEM simulations, and when compared to experimental measurements they are below $10\%$ in the case of the 1-layer coils, and below $5\%$ in the 2-layer coils (without taking into consideration the coil connectors). The proposed model offers a new approach to the calculation of the self-inductance of planar coils of several layers that combines precision, speed, independence of geometry, easy interaction, and no need for extra resources.

This study aimed to evaluate a clothing prototype that incorporates sensors for the evaluation of pressure, temperature, and humidity for the prevention of pressure injuries, namely regarding physical and comfort requirements. A mixed-method approach was used with concurrent quantitative and qualitative data triangulation. A structured questionnaire was applied before a focus group of experts to evaluate the sensor prototypes. Data were analyzed using descriptive and inferential statistics and the discourse of the collective subject, followed by method integration and meta-inferences. Nine nurses, experts in this topic, aged 32.66 ± 6.28 years and with a time of profession of 10.88 ± 6.19 years, participated in the study. Prototype A presented low evaluation in stiffness (1.56 ± 1.01) and roughness (2.11 ± 1.17). Prototype B showed smaller values in dimension (2.77 ± 0.83) and stiffness (3.00 ± 1.22). Embroidery was assessed as inadequate in terms of stiffness (1.88 ± 1.05) and roughness (2.44 ± 1.01). The results from the questionnaires and focus groups’ show low adequacy as to stiffness, roughness, and comfort. The participants highlighted the need for improvements regarding stiffness and comfort, suggesting new proposals for the development of sensors for clothing. The main conclusions are that Prototype A presented the lowest average scores relative to rigidity (1.56 ± 1.01), considered inadequate. This dimension of Prototype B was evaluated as slightly adequate (2.77 ± 0.83). The rigidity (1.88 ± 1.05) of Prototype A + B + embroidery was evaluated as inadequate. The prototype revealed clothing sensors with low adequacy regarding the physical requirements, such as stiffness or roughness. Improvements are needed regarding the stiffness and roughness for the safety and comfort characteristics of the device evaluated.