Remotely Powered Two-Wire Cooperative Sensors for Bioimpedance Imaging Wearables.

Bioimpedance imaging aims to generate a 3D map of the resistivity and permittivity of biological tissue from multiple impedance channels measured with electrodes applied to the skin. When the electrodes are distributed around the body (for example, by delineating a cross section of the chest or a limb), bioimpedance imaging is called electrical impedance tomography (EIT) and results in functional 2D images. Conventional EIT systems rely on individually cabling each electrode to master electronics in a star configuration. This approach works well for rack-mounted equipment; however, the bulkiness of the cabling is unsuitable for a wearable system. Previously presented cooperative sensors solve this cabling problem using active (dry) electrodes connected via a two-wire parallel bus. The bus can be implemented with two unshielded wires or even two conductive textile layers, thus replacing the cumbersome wiring of the conventional star arrangement. Prior research demonstrated cooperative sensors for measuring bioimpedances, successfully realizing a measurement reference signal, sensor synchronization, and data transfer though still relying on individual batteries to power the sensors. Subsequent research using cooperative sensors for biopotential measurements proposed a method to remove batteries from the sensors and have the central unit supply power over the two-wire bus. Building from our previous research, this paper presents the application of this method to the measurement of bioimpedances. Two different approaches are discussed, one using discrete, commercially available components, and the other with an application-specific integrated circuit (ASIC). The initial experimental results reveal that both approaches are feasible, but the ASIC approach offers advantages for medical safety, as well as lower power consumption and a smaller size.

Remotely Powered Two-Wire Cooperative Sensors for Biopotential Imaging Wearables.

Biopotential imaging (e.g., ECGi, EEGi, EMGi) processes multiple potential signals, each requiring an electrode applied to the body's skin. Conventional approaches based on individual wiring of each electrode are not suitable for wearable systems. Cooperative sensors solve the wiring problem since they consist of active (dry) electrodes connected by a two-wire parallel bus that can be implemented, for example, as a textile spacer with both sides made conductive. As a result, the cumbersome wiring of the classical star arrangement is replaced by a seamless solution. Previous work has shown that potential reference, current return, synchronization, and data transfer functions can all be implemented on a two-wire parallel bus while keeping the noise of the measured biopotentials within the limits specified by medical standards. We present the addition of the power supply function to the two-wire bus. Two approaches are discussed. One of them has been implemented with commercially available components and the other with an ASIC. Initial experimental results show that both approaches are feasible, but the ASIC approach better addresses medical safety concerns and offers other advantages, such as lower power consumption, more sensors on the two-wire bus, and smaller size.

Evaluation of a Wearable System for Fetal ECG Monitoring Using Cooperative Sensors.

Fetal electrocardiography (fECG) has gotten widespread interest in the last years as technology for fetal monitoring. Compared to cardiotocography (CTG), the current state of the art, it can be designed in smaller formfactor and is thus suited for long-term and unsupervised monitoring. In the present study we evaluated a wearable system which is based on CSEM's cooperative sensors, a versatile technology that allows for the measurement of multiple biosignals and an easy integration into a garment or patch. The system was tested on 25 patients with singleton pregnancies and an age of gestation ≥ 37 weeks. To reject unreliable fetal heart rate (fHR) estimations, the signal processing algorithm provides a signal quality index. In 12 out of 21 patients available for analysis, a good performance of fHR estimations was obtained with a mean absolute error < 5 bpm and an acceptance rate >70%. However, the remaining 9 patients showed low acceptance rates and high errors. Besides investigating the source of these high errors, future work includes the investigating improved signal processing algorithms, different body positions and the use of dry electrodes. Clinical Relevance - The aim of this work is to develop a wearable system that can be offered in hospitals as an alternative to cardiotocography, or as a home monitoring tool for at risk fetuses, in the era of evolving telemedicine.

A Wearable Stethoscope for Long-Term Ambulatory Respiratory Health Monitoring.

Lung sounds acquired by stethoscopes are extensively used in diagnosing and differentiating respiratory diseases. Although an extensive know-how has been built to interpret these sounds and identify diseases associated with certain patterns, its effective use is limited to individual experience of practitioners. This user-dependency manifests itself as a factor impeding the digital transformation of this valuable diagnostic tool, which can improve patient outcomes by continuous long-term respiratory monitoring under real-life conditions. Particularly patients suffering from respiratory diseases with progressive nature, such as chronic obstructive pulmonary diseases, are expected to benefit from long-term monitoring. Recently, the COVID-19 pandemic has also shown the lack of respiratory monitoring systems which are ready to deploy in operational conditions while requiring minimal patient education. To address particularly the latter subject, in this article, we present a sound acquisition module which can be integrated into a dedicated garment; thus, minimizing the role of the patient for positioning the stethoscope and applying the appropriate pressure. We have implemented a diaphragm-less acousto-electric transducer by stacking a silicone rubber and a piezoelectric film to capture thoracic sounds with minimum attenuation. Furthermore, we benchmarked our device with an electronic stethoscope widely used in clinical practice to quantify its performance.

ECG-Quality Assessment of Dry-Electrode Cooperative Sensors.

Classical approaches for measuring high-quality ECG require the use of gel electrodes and individually shielded cables, which limit patient comfort, especially in long-term use. We recently introduced a novel sensing architecture-so-called cooperative sensors-that allow the use of active dry electrodes connected by two unshielded wires. The aim of this work is to qualitatively evaluate an ECG recorded with a dry-electrode cooperative-sensor system. To that end, preliminary observations were made on three healthy subjects. The ECGs were concurrently recorded with cooperative sensors and a gold-standard 12-lead ECG device during a stress test on a stationary bicycle. First experimental measurements demonstrated the reliability of the approach for a wearable 12-lead ECG monitoring system tested in real settings.

Multimodal remote chest monitoring system with wearable sensors: a validation study in healthy subjects.

OBJECTIVE: Development of wearable medical technology for remote monitoring of patients suffering from chronic lung diseases may improve the care, therapy and outcome of these patients. APPROACH: A multimodal system using wearable sensors for the acquisition of multiple biosignals (electrical bioimpedance of the chest for electrical impedance tomography and respiratory rate assessment, peripheral oxygen saturation, chest sounds, electrocardiography for heart rate measurement, body activity, and posture) was developed and validated in a prospective, monocentric study on 50 healthy subjects. The subjects were studied under different types of ventilation (tidal and deep breathing, forced full expiration maneuver) and during increased body activity and posture changes. The major goals were to assess the functionality by determining the presence and plausibility of the signals, comfort of wearing and safety of the vest. MAIN RESULTS: All intended signals were recorded. Streaming of selected signals and wireless download of complete data sets were functional. Electrical impedance tomography recordings revealed good to excellent quality of detection of ventilation-related impedance changes in 34 out of 50 participants. Respiratory and heart rates were reliably detected and generally in physiological ranges. Peripheral oxygen saturation values were unphysiologically low. The chest sound recordings did not show waveforms allowing meaningful analysis of lung sounds. Body activity and posture were correctly identified. The comfort of wearing and the vest properties were positively rated. No adverse events occurred. SIGNIFICANCE: Albeit the full functionality of the current vest design was not established, the study confirmed the feasibility of remote functional chest monitoring with a marked increase in clinically relevant information compared to existing systems.

Wearable Sensors for Frequency-Multiplexed EIT and Multilead ECG Data Acquisition.

This paper presents a wearable sensor architecture for frequency-multiplexed electrical impedance tomography (EIT) and synchronous multilead electrocardiogram (ECG) data acquisition. The system is based on a novel electronic sensing architecture, called cooperative sensors, that significantly reduces the cabling complexity and enables flexible EIT stimulation and measurement patterns. The cooperative-sensor architecture was initially designed for ECG and has been extended for multichannel bioimpedance measurement. This approach allows for an adjustable EIT stimulation pattern via frequency-division multiplexing. This paper also shows a calibration procedure as well as EIT system noise performance assessment. Preliminary measurements on a healthy volunteer showed the ability of the wearable system to measure EIT data synchronously with multilead ECG. Ventilation-related and heartbeat-related EIT images were reconstructed, demonstrating the feasibility of the proposed architecture for noninvasive cardiovascular monitoring.

Two-Wire Bus Combining Full Duplex Body-Sensor Network and Multilead Biopotential Measurements.

Classical approaches to make high-quality measurements of biopotential signals require the use of shielded or multiwire cables connecting the electrodes to a central unit in a star arrangement. As a consequence, increasing the number of leads increases cabling and connector complexity, which is not only limiting the patient comfort but is also anticipated as the main limiting factor to future miniaturization and cost reduction of tomorrow's wearables. We have recently introduced a novel sensing architecture that significantly reduces the cabling complexity by eliminating shielded or multiwire cables and by allowing simple connectors, thanks to a bus arrangement. In this architecture, electrodes are replaced by so-called cooperative sensors that require synchronous operation for systems larger than two sensors. This paper presents a novel full duplex body-sensor network based on a simple two-wire bus that combines biopotential measurements, synchronization, and gathering of data in a single cooperative sensor with a throughput up to 2 Mb/s. When compared to others, the suggested approach is advantageous as it keeps the cabling complexity at its minimum and does not require every sensor to be equipped with wireless communication capabilities. First experimental measurements demonstrated the reliability of the approach for a wearable 12-lead electrocardiogram monitoring system tested in real-life scenario.

Electrical impedance tomography (EIT) for quantification of pulmonary edema in acute lung injury.

BACKGROUND: Assessment of pulmonary edema is a key factor in monitoring and guidance of therapy in critically ill patients. To date, methods available at the bedside for estimating the physiologic correlate of pulmonary edema, extravascular lung water, often are unreliable or require invasive measurements. The aim of the present study was to develop a novel approach to reliably assess extravascular lung water by making use of the functional imaging capabilities of electrical impedance tomography. METHODS: Thirty domestic pigs were anesthetized and randomized to three different groups. Group 1 was a sham group with no lung injury. Group 2 had acute lung injury induced by saline lavage. Group 3 had vascular lung injury induced by intravenous injection of oleic acid. A novel, noninvasive technique using changes in thoracic electrical impedance with lateral body rotation was used to measure a new metric, the lung water ratioEIT, which reflects total extravascular lung water. The lung water ratioEIT was compared with postmortem gravimetric lung water analysis and transcardiopulmonary thermodilution measurements. RESULTS: A significant correlation was found between extravascular lung water as measured by postmortem gravimetric analysis and electrical impedance tomography (r = 0.80; p < 0.05). Significant changes after lung injury were found in groups 2 and 3 in extravascular lung water derived from transcardiopulmonary thermodilution as well as in measurements derived by lung water ratioEIT. CONCLUSIONS: Extravascular lung water could be determined noninvasively by assessing characteristic changes observed on electrical impedance tomograms during lateral body rotation. The novel lung water ratioEIT holds promise to become a noninvasive bedside measure of pulmonary edema.

Influence of heart motion on cardiac output estimation by means of electrical impedance tomography: a case study.

Electrical impedance tomography (EIT) is a non-invasive imaging technique that can measure cardiac-related intra-thoracic impedance changes. EIT-based cardiac output estimation relies on the assumption that the amplitude of the impedance change in the ventricular region is representative of stroke volume (SV). However, other factors such as heart motion can significantly affect this ventricular impedance change. In the present case study, a magnetic resonance imaging-based dynamic bio-impedance model fitting the morphology of a single male subject was built. Simulations were performed to evaluate the contribution of heart motion and its influence on EIT-based SV estimation. Myocardial deformation was found to be the main contributor to the ventricular impedance change (56%). However, motion-induced impedance changes showed a strong correlation (r = 0.978) with left ventricular volume. We explained this by the quasi-incompressibility of blood and myocardium. As a result, EIT achieved excellent accuracy in estimating a wide range of simulated SV values (error distribution of 0.57 ± 2.19 ml (1.02 ± 2.62%) and correlation of r = 0.996 after a two-point calibration was applied to convert impedance values to millilitres). As the model was based on one single subject, the strong correlation found between motion-induced changes and ventricular volume remains to be verified in larger datasets.

Aortic blood pressure measured via EIT: investigation of different measurement settings.

Electrical impedance tomography (EIT) allows the measurement of intra-thoracic impedance changes related to cardiovascular activity. As a safe and low-cost imaging modality, EIT is an appealing candidate for non-invasive and continuous haemodynamic monitoring. EIT has recently been shown to allow the assessment of aortic blood pressure via the estimation of the aortic pulse arrival time (PAT). However, finding the aortic signal within EIT image sequences is a challenging task: the signal has a small amplitude and is difficult to locate due to the small size of the aorta and the inherent low spatial resolution of EIT. In order to most reliably detect the aortic signal, our objective was to understand the effect of EIT measurement settings (electrode belt placement, reconstruction algorithm). This paper investigates the influence of three transversal belt placements and two commonly-used difference reconstruction algorithms (Gauss-Newton and GREIT) on the measurement of aortic signals in view of aortic blood pressure estimation via EIT. A magnetic resonance imaging based three-dimensional finite element model of the haemodynamic bio-impedance properties of the human thorax was created. Two simulation experiments were performed with the aim to (1) evaluate the timing error in aortic PAT estimation and (2) quantify the strength of the aortic signal in each pixel of the EIT image sequences. Both experiments reveal better performance for images reconstructed with Gauss-Newton (with a noise figure of 0.5 or above) and a belt placement at the height of the heart or higher. According to the noise-free scenarios simulated, the uncertainty in the analysis of the aortic EIT signal is expected to induce blood pressure errors of at least ± 1.4 mmHg.

Synchronization and communication of cooperative sensors.

Cooperative sensors are an emerging technology consisting of autonomous sensor units working in concert to measure physiological signals requiring distant sensing points, such as biopotential (e.g., ECG) or bioimpedance (e.g., EIT). Their advantage with respect to the state-of-the-art technology is that they do not require shielded and even insulated cables to measure best quality biopotential or bioimpedance signals. Moreover, as all sensors are simply connected to a single electrical connection (which can be for instance a conductive vest) there is no connecting limitation to the miniaturization of the system or to its extension to large numbers of sensors. This results in an increase of wearability and comfort, as well as in a decrease of costs and integration challenges. However, cooperative sensors must communicate to be synchronized and to centralize the data. This paper presents possible communication strategies and focuses on the implementation of one of them that is particularly well suited for biopotential and bioimpedance measurements.