A full-head model to investigate intra and extracochlear electric fields in cochlear implant stimulation.

OBJECTIVE: Despite the widespread use and technical improvement of cochlear implant (CI) devices over past decades, further research into the bioelectric bases of CI stimulation is still needed. Various stimulation modes implemented by different CI manufacturers coexist, but their true clinical benefit remains unclear, probably due to the high inter-subject variability reported, which makes the prediction of CI outcomes and the optimal fitting of stimulation parameters challenging. A highly detailed full head model that includes a cochlea and an electrode array is developed in this study to emulate intracochlear voltages and extracochlear current pathways through the head in CI stimulation. APPROACH: Simulations based on the finite element method were conducted under monopolar, bipolar, tripolar, and partial tripolar modes, as well as for apical, medial, and basal electrodes. Variables simulated included: intracochlear voltages, electric field (EF) decay, electric potentials at the scalp and extracochlear currents through the head. To better understand CI side effects such as facial nerve stimulation, caused by spurious current leakage out from the cochlea, special emphasis is given to the analysis of the EF over the facial nerve. MAIN RESULTS: The model reasonably predicts EF magnitudes and trends previously reported in CI users. New relevant extracochlear current pathways through the head and brain tissues have been identified. Simulated results also show differences in the magnitude and distribution of the EF through different segments of the facial nerve upon different stimulation modes and electrodes, dependent on nerve and bone tissue conductivities. SIGNIFICANCE: Full head models prove useful tools to model intra and extracochlear EFs in CI stimulation. Our findings could prove useful in the design of future experimental studies to contrast FNS mechanisms upon stimulation of different electrodes and CI modes. The full-head model developed is freely available for the CI community for further research and use.

Addressing the sources of inter-subject variability in E-field parameters in anodal tDCS stimulation over motor cortical network.

BACKGROUND: Although tDCS constitutes a non-invasive neuromodulation technique with promising results in a great variety of applications, its clinical implementation is compromised by the high inter-subject variability reported. This study aims to analyze the inter-subject variability in electric fields (E-fields) over regions of the cortical motor network under two electrode montages: the classical C3Fp2 and an alternative P3F3, which confines more the Efield over this region. Methods: Computational models of the head of 98 healthy subjects were developed to simulate the E-field under both montages. E-field parameters such as magnitude, focality and orientation were calculated over three regions of interest (ROI): M1S1, SMA and preSMA. The role of anatomical characteristics as a source of inter-subject variability on E-field parameters was addressed using linear mixed-effect models. Results: P3F3 showed a more confined E-field distribution over M1S1 than C3Fp2; the latter elicited higher E-fields over supplementary motor areas. Both montages showed high inter-subject variability, especially for the normal component over C3Fp2. Skin, bone and CSF ROI volumes showed a negative association with E-field magnitude irrespective of montage. Grey matter volume and montage were the main sources of variability for focality. The curvature of gyri was found to be significantly associated with the variability of normal E-fields. Conclusions: Computational modelling proves useful in the assessment of E-field variability. Our simulations predict significant differences in E-field magnitude and focality for C3Fp2 and P3F3. However, anatomical characteristics were also found to be significant sources of E-field variability irrespective of electrode montage. .

Comparative Study of the Impact of Human Leukocyte Antigens on Renal Transplant Survival in Andalusia and the United States.

Renal transplantation is the treatment of choice for patients suffering from chronic renal disease, one of the leading causes of death worldwide. Among the biological barriers that may increase the risk of acute renal graft rejection is the presence of human leukocyte antigen (HLA) incompatibilities between donor and recipient. This work presents a comparative study of the influence of HLA incompatibilities on renal transplantation survival in the Andalusian (South of Spain) and United States (US) population. The main objective is to analyse the extent to which results about the influence of different factors on renal graft survival can be generalised to different populations. The Kaplan-Meier estimator and the Cox model have been used to identify and quantify the impact on the survival probability of HLA incompatibilities, both in isolation and in conjunction with other factors associated with the donor and recipient. According to the results obtained, HLA incompatibilities considered in isolation have negligible impact on renal survival in the Andalusian population and a moderate impact in the US population. Grouping by HLA score presents some similarities for both populations, while the sum of all HLA scores (aHLA) only has an impact on the US population. Finally, the graft survival probability of the two populations differs when aHLA is considered in conjunction with blood type. The results suggest that the disparities in the renal graft survival probability between the two populations under study are due not only to biological and transplantation-associated factors, but also to social-health factors and ethnic heterogeneity between populations.

A Sensor-Based mHealth Platform for Remote Monitoring and Intervention of Frailty Patients at Home.

Frailty syndrome is an independent risk factor for serious health episodes, disability, hospitalization, falls, loss of mobility, and cardiovascular disease. Its high reversibility demands personalized interventions among which exercise programs are highly efficient to contribute to its delay. Information technology-based solutions to support frailty have been recently approached, but most of them are focused on assessment and not on intervention. This paper describes a sensor-based mHealth platform integrated in a service-based architecture inside the FRAIL project towards the remote monitoring and intervention of pre-frail and frail patients at home. The aim of this platform is constituting an efficient and scalable system for reducing both the impact of aging and the advance of frailty syndrome. Among the results of this work are: (1) the development of elderly-focused sensors and platform; (2) a technical validation process of the sensor devices and the mHealth platform with young adults; and (3) an assessment of usability and acceptability of the devices with a set of pre-frail and frail patients. After the promising results obtained, future steps of this work involve performing a clinical validation in order to quantify the impact of the platform on health outcomes of frail patients.

Internet of things in health: Requirements, issues, and gaps.

BACKGROUND AND OBJECTIVES: The Internet of Things (IoT) paradigm has been extensively applied to several sectors in the last years, ranging from industry to smart cities. In the health domain, IoT makes possible new scenarios of healthcare delivery as well as collecting and processing health data in real time from sensors in order to make informed decisions. However, this domain is complex and presents several technological challenges. Despite the extensive literature about this topic, the application of IoT in healthcare scarcely covers requirements of this sector. METHODS: A literature review from January 2010 to February 2021 was performed resulting in 12,108 articles. After filtering by title, abstract, and content, 86 were eligible and examined according to three requirement themes: data lifecycle; trust, security, and privacy; and human-related issues. RESULTS: The analysis of the reviewed literature shows that most approaches consider IoT application in healthcare merely as in any other domain (industry, smart cities…), with no regard of the specific requirements of this domain. CONCLUSIONS: Future efforts in this matter should be aligned with the specific requirements and needs of the health domain, so that exploiting the capabilities of the IoT paradigm may represent a meaningful step forward in the application of this technology in healthcare.

Effects of genetics and altitude on lung function.

OBJECTIVES: The aim of this work is to present a review on the impact of genetics and altitude on lung function from classic and recent studies. DATA SOURCE: A systematic search has been carried out in different databases of scientific studies, using keywords related to lung volumes, spirometry, altitude and genetics. RESULTS: The results of this work have been structured into three parts. First, the relationship between genes and lung function. Next, a review of the genetic predispositions related to respiratory adaptation of people who inhabit high-altitude regions for millennia. Finally, temporary effects and long-term acclimatisation on respiratory physiology at high altitude are presented. CONCLUSIONS: The works focused on the influence of genetics and altitude on lung function are currently of interest in terms of studying the interactions between genetic, epigenetic and environmental factors in the configuration of the pathophysiological adaptation patterns.

Special Issue "Body Sensors Networks for E-Health Applications".

Body Sensor Networks (BSN) have emerged as a particularization of Wireless Sensor Networks (WSN) in the context of body monitoring environments, closely linked to healthcare applications. These networks are made up of smart biomedical sensors that allow the monitoring of physiological parameters and serve as the basis for e-Health applications. This Special Issue collects some of the latest developments in the field of BSN related to new developments in biomedical sensor technologies, the design and experimental characterization of on-body/in-body antennas and new communication protocols for BSN, including some review studies.

Sensor Technologies to Manage the Physiological Traits of Chronic Pain: A Review.

Non-oncologic chronic pain is a common high-morbidity impairment worldwide and acknowledged as a condition with significant incidence on quality of life. Pain intensity is largely perceived as a subjective experience, what makes challenging its objective measurement. However, the physiological traces of pain make possible its correlation with vital signs, such as heart rate variability, skin conductance, electromyogram, etc., or health performance metrics derived from daily activity monitoring or facial expressions, which can be acquired with diverse sensor technologies and multisensory approaches. As the assessment and management of pain are essential issues for a wide range of clinical disorders and treatments, this paper reviews different sensor-based approaches applied to the objective evaluation of non-oncological chronic pain. The space of available technologies and resources aimed at pain assessment represent a diversified set of alternatives that can be exploited to address the multidimensional nature of pain.

Smart Bioimpedance Spectroscopy Device for Body Composition Estimation.

The purpose of this work is to describe a first approach to a smart bioimpedance spectroscopy device for its application to the estimation of body composition. The proposed device is capable of carrying out bioimpedance measurements in multiple configurable frequencies, processing the data to obtain the modulus and the bioimpedance phase in each of the frequencies, and transmitting the processed information wirelessly. Another novelty of this work is a new algorithm for the identification of Cole model parameters, which is the basis of body composition estimation through bioimpedance spectroscopy analysis. Against other proposals, the main advantages of the proposed method are its robustness against parasitic effects by employing an extended version of Cole model with phase delay and three dispersions, its simplicity and low computational load. The results obtained in a validation study with respiratory patients show the accuracy and feasibility of the proposed technology for bioimpedance measurements. The precision and validity of the algorithm was also proven in a validation study with peritoneal dialysis patients. The proposed method was the most accurate compared with other existing algorithms. Moreover, in those cases affected by parasitic effects the proposed algorithm provided better approximations to the bioimpedance values than a reference device.

Lessons Learned about the Design and Active Characterization of On-Body Antennas in the 2.4 GHz Frequency Band.

This work addresses the design and experimental characterization of on-body antennas, which play an essential role within Body Sensor Networks. Four antenna designs were selected from a set of eighteen antenna choices and finally implemented for both passive and active measurements. The issues raised during the process of this work (requirements study, technology selection, development and optimization of antennas, impedance matching, unbalanced to balanced transformation, passive and active characterization, off-body and on-body configurations, etc.) were studied and solved, driving a methodology for the characterization of on-body antennas, including transceiver effects. Despite the influence of the body, the antennas showed appropriate results for an in-door environment. Another novelty is the proposal and validation of a phantom to emulate human experimentation. The differences between experimental and simulated results highlight a set of circumstances to be taken into account during the design process of an on-body antenna: more comprehensive simulation schemes to take into account the hardware effects and a custom design process that considers the application for which the device will be used, as well as the effects that can be caused by the human body.

Smart Vest for Respiratory Rate Monitoring of COPD Patients Based on Non-Contact Capacitive Sensing.

In this paper, a first approach to the design of a portable device for non-contact monitoring of respiratory rate by capacitive sensing is presented. The sensing system is integrated into a smart vest for an untethered, low-cost and comfortable breathing monitoring of Chronic Obstructive Pulmonary Disease (COPD) patients during the rest period between respiratory rehabilitation exercises at home. To provide an extensible solution to the remote monitoring using this sensor and other devices, the design and preliminary development of an e-Health platform based on the Internet of Medical Things (IoMT) paradigm is also presented. In order to validate the proposed solution, two quasi-experimental studies have been developed, comparing the estimations with respect to the golden standard. In a first study with healthy subjects, the mean value of the respiratory rate error, the standard deviation of the error and the correlation coefficient were 0.01 breaths per minute (bpm), 0.97 bpm and 0.995 (p < 0.00001), respectively. In a second study with COPD patients, the values were −0.14 bpm, 0.28 bpm and 0.9988 (p < 0.0000001), respectively. The results for the rest period show the technical and functional feasibility of the prototype and serve as a preliminary validation of the device for respiratory rate monitoring of patients with COPD.

A Parametric Computational Analysis Into Galvanic Coupling Intrabody Communication.

Intrabody Communication (IBC) uses the human body tissues as transmission media for electrical signals to interconnect personal health devices in wireless body area networks. The main goal of this work is to conduct a computational analysis covering some bioelectric issues that still have not been fully explained, such as the modeling of skin-electrode impedance, the differences associated with the use of constant voltage, or current excitation modes, or the influence on attenuation of the subject's anthropometrical and bioelectric properties. With this aim, a computational finite element model has been developed, allowing the IBC channel attenuation as well as the electric field and current density through arm tissues to be computed as a function of these parameters. As a conclusion, this parametric analysis has in turn permitted us to disclose some knowledge about the causes and effects of the above-mentioned issues, thus, explaining and complementing previous results reported in the literature.

A Machine-to-Machine protocol benchmark for eHealth applications - Use case: Respiratory rehabilitation.

BACKGROUND: M2M (Machine-to-Machine) communications represent one of the main pillars of the new paradigm of the Internet of Things (IoT), and is making possible new opportunities for the eHealth business. Nevertheless, the large number of M2M protocols currently available hinders the election of a suitable solution that satisfies the requirements that can demand eHealth applications. OBJECTIVES: In the first place, to develop a tool that provides a benchmarking analysis in order to objectively select among the most relevant M2M protocols for eHealth solutions. In the second place, to validate the tool with a particular use case: the respiratory rehabilitation. METHODS: A software tool, called Distributed Computing Framework (DFC), has been designed and developed to execute the benchmarking tests and facilitate the deployment in environments with a large number of machines, with independence of the protocol and performance metrics selected. RESULTS: DDS, MQTT, CoAP, JMS, AMQP and XMPP protocols were evaluated considering different specific performance metrics, including CPU usage, memory usage, bandwidth consumption, latency and jitter. The results obtained allowed to validate a case of use: respiratory rehabilitation of chronic obstructive pulmonary disease (COPD) patients in two scenarios with different types of requirement: Home-Based and Ambulatory. CONCLUSIONS: The results of the benchmark comparison can guide eHealth developers in the choice of M2M technologies. In this regard, the framework presented is a simple and powerful tool for the deployment of benchmark tests under specific environments and conditions.

Measurement Issues in Galvanic Intrabody Communication: Influence of Experimental Setup.

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.

A distributed approach to alarm management in chronic kidney disease.

This paper presents the feasibility study of using a distributed approach for the management of alarms from chronic kidney disease patients. In a first place, the key issues regarding alarm definition, classification, and prioritization according to available normalization efforts are analyzed for the main scenarios addressed in hemodialysis. Then, the middleware proposed for alarm management is described, which follows the publish/subscribe pattern, and supports the Object Management Group data distribution service (DDS) standard. This standard facilitates the real-time monitoring of the exchanged information, as well as the scalability and interoperability of the solution developed regarding the different stakeholders and resources involved. Finally, the results section shows, through the proof of concept studied, the viability of DDS for the activation of emergency protocols in terms of alarm prioritization and personalization, as well as some remarks about security, privacy, and real-time communication performance.

Galvanic coupling transmission in intrabody communication: a finite element approach.

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.

SoM: a smart sensor for human activity monitoring and assisted healthy ageing.

This paper presents the hardware and software design and implementation of a low-cost, wearable, and unobstructive intelligent accelerometer sensor for the monitoring of human physical activities. In order to promote healthy lifestyles to elders for an active, independent, and healthy ageing, as well as for the early detection of psychomotor abnormalities, the activity monitoring is performed in a holistic manner in the same device through different approaches: 1) a classification of the level of activity that allows to establish patterns of behavior; 2) a daily activity living classifier that is able to distinguish activities such as climbing or descending stairs using a simple method to decouple the gravitational acceleration components of the motion components; and 3) an estimation of metabolic expenditure independent of the activity performed and the anthropometric characteristics of the user. Experimental results have demonstrated the feasibility of the prototype and the proposed algorithms.

Distributed circuit modeling of galvanic and capacitive coupling for intrabody communication.

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.

Personalization and adaptation to the medium and context in a fall detection system.

The main objective of this paper is to present a distributed processing architecture that explicitly integrates capabilities for its continuous adaptation to the medium, the context, and the user. This architecture is applied to a falling detection system through: 1) an optimization module that finds the optimal operation parameters for the detection algorithms of the system devices; 2) a distributed processing architecture that provides capabilities for remote firmware update of the smart sensors. The smart sensor also provides an estimation of activities of daily living (ADL), which results very useful in monitoring of the elderly and patients with chronic diseases. The developed experiments have demonstrated the feasibility of the system and specifically, the accuracy of the proposed algorithms and procedures (100% success for impact detection, 100% sensitivity and 95.68% specificity rates for fall detection, and 100% success for ADL level classification). Although the experiments have been developed with a cohort of young volunteers, the personalization and adaption mechanisms of the proposed architecture related to the concepts of "design for all" and "design space" will significantly ease the adaptation of the system for its application to the elderly.

Study of attenuation and dispersion through the skin in intrabody communications systems.

Intrabody communication (IBC) is a technique that uses the human body as a transmission medium for electrical signals to connect wireless body sensors, e.g., in biomedical monitoring systems. In this paper, we propose a simple, but accurate propagation model through the skin based on a distributed-parameter circuit in order to obtain general expressions that could assist in the design of IBC systems. In addition, the model is based on the major electrophysiological properties of the skin. We have found the attenuation and dispersion parameters and they have been successfully compared with several published results, thus showing the tuning capability of the model to different experimental conditions. Finally, we have evaluated different digital modulation schemes in order to assess the tradeoffs between symbol rate, bit error rate, and distance between electrodes of the skin communication channel.