Respiration monitoring is a very important indicator of health status. It can be used as a marker in the recognition of a variety of diseases, such as sleep apnea, asthma or cardiac arrest. The purpose of the present study is to overcome limitations of the current state of the art in the field of respiration monitoring systems. Our goal was the development of a lightweight handheld device with portable operation and low power consumption. The proposed approach includes a textile capacitive sensor with interdigitated electrodes embroidered into the facemask, integrated with readout electronics. Readout electronics is based on the direct interface of the capacitive sensor and a microcontroller through just one analog and one digital pin. The microcontroller board and sensor are powered by a smartphone or PC through a USB cable. The developed mobile application for the Android™ operating system offers reliable data acquisition and acts as a bridge for data transfer to the remote server. The embroidered sensor was initially tested in a humidity-controlled chamber connected to a commercial impedance analyzer. Finally, in situ testing with 10 volunteering subjects confirmed stable operation with reliable respiration monitoring.

In recent years, advancements in technology are constantly driving the miniaturization of electronic devices, not only in the renowned domain of Internet-of-Things but also in other fields such as that of flexible and textile electronics. As the latter forms a great ecosystem for new devices, that could be functional such as heating garments or sensory, many suppliers have already started producing and bringing to market conductive threads that can be used by researchers and the mass public for their work. However, to date, no extensive characterization has been carried out with respect to the electrical performance of such threads and that is what this article is aiming to amend. Four commercially available threads by two different suppliers were put under test, to establish their limitations in terms of maximum power handling, both continuous and instantaneous. They were subsequently examined at a microscopic scale as well, to verify any potential caveats in their design, and any hidden limitations. A preliminary profile for each of the four threads was successfully established.

Accurate modeling of electrochemical sources is very important to predict how a source will perform in specific applications related to the load or environmental parameters. A Randles circuit is considered as a reliable equivalent electrical circuit in studying and modeling various electrochemical systems and processes. The classical parameter estimation approach based on use of software packages (ZSim, MEISP, LEVMW, and so on) requires high computational performance processing units, decreasing the reliability as proper maintenance actions can be delayed because of offline analysis. Advancing the state of the art, we propose a low-complexity approach for embedded hardware-based parameter estimation of the Randles circuit. Our noniterative method uses only the measured real and imaginary parts of impedance, with numerical approximation of the first derivative of real/imaginary part quotient, to create closed-form expressions with a unique solution. The initial estimated values are available from partial dataset (after measurement at only three frequencies). Moreover, it is not software platform-specific, which enables a high level of portability. The presented method is verified with theoretical, numerical, and experimental analysis, with more than 1000 datasets. We also demonstrated the applicability in parameter estimation of the Randles circuit of a Li-ion battery. Finally, we verified suitability for embedded hardware platforms, with deployment on a microcontroller-based platform with a clock speed of 16 MHz and 8 kB of SRAM. Reliable parameter estimation processing of a 100-point dataset was performed in just 106 ms with 1% relative error, requiring less than 53 mJ of energy.

In recent years, after the ongoing success in the creation of portable electronic devices, an increasing effort has been put in creating wearable devices capable of sensing multiple parameters while being imperceptible to the user. A field that has recently gained attention due to this is that of textile electronics. For this purpose, one of the most commonly used materials is conductive threads, capable of sustaining an electrical connection, while at the same time being part of a garment. As research on the performance and stability of such threads is scarce, the aim of this work is to study the effects of tension on readily available conductive threads and to verify their suitability and reliability for e-textile applications. After testing seven commercially available threads, this study demonstrates that the nominal parameters provided by the manufacturers are not in line with experimentation, and that both embroidery and washing have an impact on their performance.

Electrical Impedance Spectroscopy has been widely used in the modeling and analysis of the various electrochemical and energy storage systems. Parameter estimation of the equivalent electrical circuit is usually performed with PC-based software platforms which are not commonly available onsite. Such an approach introduces lag between measurement and maintenance actions. In this paper, we present method for in-situ parameter estimation of the Randles circuit (R-RC equivalent model). Our method overcomes the shortcoming of the iterative and PC-based estimation approaches, since there is no need for an initial guess provided by the user. The low complexity of our approach enables the implementation on cost-effective microcontroller-based portable systems. The proposed method has been validated with simulations and with experimentally obtained data. In the simulation part we used both the noiseless and noisy data, while in the experimental part we used impedance data obtained from a dummy circuit created with discrete components, as well as bioimpedance of apple slices. Obtained results are compared with desktop based MEISP software. Finally, reliable and accurate estimations with a board based on the ATmega2560 microcontroller confirmed the hypothesis of suitability for implementation on embedded hardware.

In this paper we present a processing-efficient method for parameter estimation of a Randles circuit. As our approach is not iterative, it does not require for an initial guess of model parameters to be provided. The low-complexity of the provided set of closed-form expressions enables the implementation on microcontroller-based platforms. The presented approach is verified with simulations (using both noiseless data and data with noise) and with experimentally obtained data (Randles circuit made from discrete components; impedance of microfluidic platform for isomalt detection; impedance of Panasonic 18650PF Li-ion Battery). Additionally, it was implemented on a microcontroller board based on ATmega2560 microcontroller with available 256 kB of flash memory, 8 kB of SRAM and clock speed of 16 MHz. Reliable and accurate estimations of such implementations confirmed the suitability of this work for low-cost embedded hardware.