One of the main objectives of research into intrabody communication (IBC) is the characterization of the human body as a transmission medium for electrical signals. However, such characterization is strongly influenced by the conditions under which the experiments are performed. In addition, the outcomes reported in the literature vary according to the measurement method used, frequently making comparisons among them unfeasible. Further studies are still required in order to establish a methodology for IBC characterization and design. In this paper, both galvanic and capacitive coupling setups have been implemented and a comprehensive set of measurements has been carried out by analyzing fundamental IBC parameters such as optimum frequency range, maximum channel length, and type of electrodes, among others. Consequently, practical conclusions regarding the experimental conditions that optimize IBC performance for each coupling technique have been obtained.

Modeling of intrabody communication (IBC) entails the understanding of the interaction between electromagnetic fields and living tissues. At the same time, an accurate model can provide practical hints toward the deployment of an efficient and secure communication channel for body sensor networks. In the literature, two main IBC coupling techniques have been proposed: galvanic and capacitive coupling. Nevertheless, models that are able to emulate both coupling approaches have not been reported so far. In this paper, a simple model based on a distributed parameter structure with the flexibility to adapt to both galvanic and capacitive coupling has been proposed. In addition, experimental results for both coupling methods were acquired by means of two harmonized measurement setups. The model simulations have been subsequently compared with the experimental data, not only to show their validity but also to revise the practical frequency operation range for both techniques. Finally, the model, along with the experimental results, has also allowed us to provide some practical rules to optimally tackle IBC design.

Galvanic coupling in intrabody communication (IBC) is a technique that couples low-power and low-frequency voltages and currents into the human body, which acts as a transmission medium, and thus constitutes a promising approach in the design of personal health devices. Despite important advances being made during recent years, the investigation of relevant galvanic IBC parameters, including the influence of human tissues and different electrode configurations, still requires further research efforts. The objective of this work is to disclose knowledge into IBC galvanic coupling transmission mechanisms by using a realistic 3-D finite element model of the human arm. Unlike other computational models for IBC, we have modeled the differential configuration of the galvanic coupling as a four-port network in order to analyze the electric field distribution and current density through different tissues. This has allowed us to provide an insight into signal transmission paths through the human body, showing them to be considerably dependent on variables such as frequency and inter-electrode distance. In addition, other important variables, for example bioimpedance and pathloss, have also been analyzed. Finally, experimental measurements were also carried out for the sake of validation, demonstrating the reliability of the model to emulate in general forms some of the behaviors observed in practice.

Significance: The need for increasingly energy-efficient and miniaturized bio-devices for ubiquitous health monitoring has paved the way for considerable advances in the investigation of techniques such as intrabody communication (IBC), which uses human tissues as a transmission medium. However, IBC still poses technical challenges regarding the measurement of the actual gain through the human body. The heterogeneity of experimental setups and conditions used together with the inherent uncertainty caused by the human body make the measurement process even more difficult. Goal: The objective of this study, focused on galvanic coupling IBC, is to study the influence of different measurement equipments and conditions on the IBC channel. Methods : Different experimental setups have been proposed in order to analyze key issues such as grounding, load resistance, type of measurement device and effect of cables. In order to avoid the uncertainty caused by the human body, an IBC electric circuit phantom mimicking both human bioimpedance and gain has been designed. Given the low-frequency operation of galvanic coupling, a frequency range between 10 kHz and 1 MHz has been selected. Results : The correspondence between simulated and experimental results obtained with the electric phantom have allowed us to discriminate the effects caused by the measurement equipment. Conclusion: This study has helped us obtain useful considerations about optimal setups for galvanic-type IBC as well as to identify some of the main causes of discrepancy in the literature.

The COVID-19 outbreak has spread extensively around the world. Loss of smell and taste have emerged as main predictors for COVID-19. The objective of our study is to develop a comprehensive machine learning (ML) modelling framework to assess the predictive value of smell and taste disorders, along with other symptoms, in COVID-19 infection. A multicenter case-control study was performed, in which suspected cases for COVID-19, who were tested by real-time reverse-transcription polymerase chain reaction (RT-PCR), informed about the presence and severity of their symptoms using visual analog scales (VAS). ML algorithms were applied to the collected data to predict a COVID-19 diagnosis using a 50-fold cross-validation scheme by randomly splitting the patients in training (75%) and testing datasets (25%). A total of 777 patients were included. Loss of smell and taste were found to be the symptoms with higher odds ratios of 6.21 and 2.42 for COVID-19 positivity. The ML algorithms applied reached an average accuracy of 80%, a sensitivity of 82%, and a specificity of 78% when using VAS to predict a COVID-19 diagnosis. This study concludes that smell and taste disorders are accurate predictors, with ML algorithms constituting helpful tools for COVID-19 diagnostic prediction.

Intrabody communication (IBC) is a wireless communication technology using the human body to develop body area networks (BANs) for remote and ubiquitous monitoring. IBC uses living tissues as a transmission medium, achieving power‐saving and miniaturized transceivers, making communications more robust against external interference and attacks on the privacy of transmitted data. Due to these advantages, IBC has been included as a third physical layer in the IEEE 802.15.6 standard for wireless body area networks (WBANs) designated as Human Body Communication (HBC). Further research is needed to compare both methods depending on the characteristics of IBC application. Challenges remain for an optimal deployment of IBC technology, such as the effect of long‐term use in the human body, communication optimization through more realistic models, the influence of both anthropometric characteristics and the subject’s movement on the transmission performance, standardization of communications, and development of small‐size and energy‐efficient prototypes with increased data rate. The purpose of this work is to provide an in‐depth overview of recent advances and future challenges in human body/intrabody communication for wireless communications and mobile computing.