Analysis of Consistency of Transthoracic Bioimpedance Measurements Acquired with Dry Carbon Black PDMS Electrodes, Adhesive Electrodes, and Wet Textile Electrodes

The detection of intrathoracic volume retention could be crucial to the early detection of decompensated heart failure (HF). Transthoracic Bioimpedance (TBI) measurement is an indirect, promising approach to assessing intrathoracic fluid volume. Gel-based adhesive electrodes can produce skin irritation, as the patient needs to place them daily in the same spots. Textile electrodes can reduce skin irritation; however, they inconveniently require wetting before each use and provide poor adherence to the skin. Previously, we developed waterproof reusable dry carbon black polydimethylsiloxane (CB/PDMS) electrodes that exhibited a good response to motion artifacts. We examined whether these CB/PDMS electrodes were suitable sensing components to be embedded into a monitoring vest for measuring TBI and the electrocardiogram (ECG). We recruited N = 20 subjects to collect TBI and ECG data. The TBI parameters were different between the various types of electrodes. Inter-subject variability for copper-mesh CB/PDMS electrodes and Ag/AgCl electrodes was lower compared to textile electrodes, and the intra-subject variability was similar between the copper-mesh CB/PDMS and Ag/AgCl. We concluded that the copper mesh CB/PDMS (CM/CB/PDMS) electrodes are a suitable alternative for textile electrodes for TBI measurements, but with the benefit of better skin adherence and without the requirement of wetting the electrodes, which can often be forgotten by the stressed HF subjects

Bioimpedance-Based Heart Failure Deterioration Prediction Using a Prototype Fluid Accumulation Vest-Mobile Phone Dyad: An Observational Study

BACKGROUND: Recurrent heart failure (HF) events are common in patients discharged after acute decompensated heart failure (ADHF). New patient-centered technologies are needed to aid in detecting HF decompensation. Transthoracic bioimpedance noninvasively measures pulmonary fluid retention. OBJECTIVE: The objectives of our study were to (1) determine whether transthoracic bioimpedance can be measured daily with a novel, noninvasive, wearable fluid accumulation vest (FAV) and transmitted using a mobile phone and (2) establish whether an automated algorithm analyzing daily thoracic bioimpedance values would predict recurrent HF events. METHODS: We prospectively enrolled patients admitted for ADHF. Participants were trained to use a FAV-mobile phone dyad and asked to transmit bioimpedance measurements for 45 consecutive days. We examined the performance of an algorithm analyzing changes in transthoracic bioimpedance as a predictor of HF events (HF readmission, diuretic uptitration) over a 75-day follow-up. RESULTS: We observed 64 HF events (18 HF readmissions and 46 diuretic uptitrations) in the 106 participants (67 years; 63.2%, 67/106, male; 48.1%, 51/106, with prior HF) who completed follow-up. History of HF was the only clinical or laboratory factor related to recurrent HF events (P=.04). Among study participants with sufficient FAV data (n=57), an algorithm analyzing thoracic bioimpedance showed 87% sensitivity (95% CI 82-92), 70% specificity (95% CI 68-72), and 72% accuracy (95% CI 70-74) for identifying recurrent HF events. CONCLUSIONS: Patients discharged after ADHF can measure and transmit daily transthoracic bioimpedance using a FAV-mobile phone dyad. Algorithms analyzing thoracic bioimpedance may help identify patients at risk for recurrent HF events after hospital discharge. Sert Kuniyoshi, Joseph Rock, Theo E Meyer, David D McManus. Originally published in JMIR Cardio (http://cardio.jmir.org), 13.03.2017

Machine Learning Model Based on Transthoracic Bioimpedance and Heart Rate Variability for Lung Fluid Accumulation Detection: Prospective Clinical Study

BACKGROUND: Accumulation of excess body fluid and autonomic dysregulation are clinically important characteristics of acute decompensated heart failure. We hypothesized that transthoracic bioimpedance, a noninvasive, simple method for measuring fluid retention in lungs, and heart rate variability, an assessment of autonomic function, can be used for detection of fluid accumulation in patients with acute decompensated heart failure. OBJECTIVE: We aimed to evaluate the performance of transthoracic bioimpedance and heart rate variability parameters obtained using a fluid accumulation vest with carbon black-polydimethylsiloxane dry electrodes in a prospective clinical study (System for Heart Failure Identification Using an External Lung Fluid Device; SHIELD). METHODS: We computed 15 parameters: 8 were calculated from the model to fit Cole-Cole plots from transthoracic bioimpedance measurements (extracellular, intracellular, intracellular-extracellular difference, and intracellular-extracellular parallel circuit resistances as well as fitting error, resonance frequency, tissue heterogeneity, and cellular membrane capacitance), and 7 were based on linear (mean heart rate, low-frequency components of heart rate variability, high-frequency components of heart rate variability, normalized low-frequency components of heart rate variability, normalized high-frequency components of heart rate variability) and nonlinear (principal dynamic mode index of sympathetic function, and principal dynamic mode index of parasympathetic function) analysis of heart rate variability. We compared the values of these parameters between 3 participant data sets: control (n=32, patients who did not have heart failure), baseline (n=23, patients with acute decompensated heart failure taken at the time of admittance to the hospital), and discharge (n=17, patients with acute decompensated heart failure taken at the time of discharge from hospital). We used several machine learning approaches to classify participants with fluid accumulation (baseline) and without fluid accumulation (control and discharge), termed with fluid and without fluid groups, respectively. RESULTS: Among the 15 parameters, 3 transthoracic bioimpedance (extracellular resistance, R0; difference in extracellular-intracellular resistance, R0 - Rinfinity, and tissue heterogeneity, alpha) and 3 heart rate variability (high-frequency, normalized low-frequency, and normalized high-frequency components) parameters were found to be the most discriminatory between groups (patients with and patients without heart failure). R0 and R0 - Rinfinity had significantly lower values for patients with heart failure than for those without heart failure (R0: P=.006; R0 - Rinfinity: P=.001), indicating that a higher volume of fluids accumulated in the lungs of patients with heart failure. A cubic support vector machine model using the 5 parameters achieved an accuracy of 92% for with fluid and without fluid group classification. The transthoracic bioimpedance parameters were related to intra- and extracellular fluid, whereas the heart rate variability parameters were mostly related to sympathetic activation. CONCLUSIONS: This is useful, for instance, for an in-home diagnostic wearable to detect fluid accumulation. Results suggest that fluid accumulation, and subsequently acute decompensated heart failure detection, could be performed using transthoracic bioimpedance and heart rate variability measurements acquired with a wearable vest. Emily Ensom, Eric Ding, Anna Hayes, Jarno Riistama, Chad Darling, David McManus, Ki H. Chon. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 27.08.2020

Characterisation of wearable and implantable physiological measurement devices

Electrodes are an important part of any biopotential measurement application. The electrodes will be in direct galvanic contact with the skin or tissue of the measurement subject. The interface between the electrode and electrolyte has a complicated structure involving both physical and chemical processes and reactions. The thesis revises the complex interface in terms of reactions occurring at the interface, the formation and structure of the double layer at the interface, electrode potential, and various electrical equivalent interface models. The artefacts occurring at the interface are also introduced and possibilities to reduce them are discussed. A relation between the artefacts and electrode materials is established through electrochemical noise measurements performed with several metallic electrodes as well as with textile electrodes. The electrochemical noise arising from the interface as a function of time reflects the stabilisation time of the current electrode--electrolyte interface. The electrochemical noise will reduce as time from the application of the electrode on the subject elapses. The time the interface needs to reach its steady state is called the stabilisation time of the electrode. Electrode materials that possess a short stabilisation time are the most suitable ones for applications where artefacts are probable. Such applications are the ones that involve e.g. motion or deformation of the skin of the subject. Noise measurements were conducted with gold (Au), silver (Ag), silver-silver-chloride (Ag/ AgCl), platinum (Pt), stainless steel (AISI 316L), and textile (silver and copper yarns as conductive material) electrodes. The results show that Ag/AgCl electrodes have the shortest stabilisation time or, alternatively, least noise in the biopotential measurement applications. Stainless steel electrodes also showed good performance in terms of low electrochemical interface noise. It was also verified that all the electrodes will exhibit an equivalent noise level despite of the material as time elapses 10 minutes or more from the application of the electrodes on the electrolyte. Based on the measurement results, optimal materials to be used as electrodes can be determined. The complex electrode-electrolyte interface can also be expressed as an electrical equivalent circuit model known as the lumped-element model. The model component values were determined from the measurements of some of the electrodes under research in the electrochemical noise measurements. The knowledge about the component values provides means to calculate the impedance of the electrode which has to be taken into account in designing the measurement amplifier. The interface components also form a natural RC-filter which has to be taken into account when determining the measurement signal bandwidth. The measurements of the model components were performed with a square wave method, a novel and relatively simple measurement technique. The measurements done in the thesis applied the technique successfully to the component measurements although originally the technique was used for other purposes. The measurement results obeyed the frequency vs. impedance curves widely accepted among scientists. Some implantable biopotential measurement devices have been designed and realised and the results are reported in the thesis. An inductively powered implantable electrocardiogram (ECG) measurement device is presented and both in vitro and in vivo measurement results are reported. A resonance-based biopotential measurement device is also introduced. The measurement device has an extremely simple construction and is basically a resonating LC-tank whose impedance is modified by a varactor. The reflected impedance of the LC-tank can be measured at the detector device from which the biopotential can be derived. Measurement results of the human ECG measured from the skin surface with the device are reported in the thesis

A low-power and compact-sized wearable bio-impedance monitor with wireless connectivity

In this paper, we present a new bio-impedance monitor for wearable and continuous monitoring applications. The system consumes less than 14.4mW when measuring impedance, and 0.9mW when idling. Its compact size (4.8cm × 3cm × 2cm) makes it suitable for portable and wearable use. The proposed system has an accuracy of 0.5Ω and resolution of 0.2Ω on both resistance (R) and reactance (X) measurements, for impedance ranging between (j0.7)Ω to (54+j5)Ω with 2.9<5.7. We also report the results of the system validation using passive loads as human tissue model, and show our wireless and miniaturized bio-impedance monitoring system has comparable performances with a reference system

Impact of hospitalisation on health-related quality of life in patients with chronic heart failure

BACKGROUND: Empirical identification of the direct impact of hospitalisation in the change in utility could provide an interpretation for some of the unexplained variance in quality of life responses in clinical practice and clinical trials and provide assistance to researchers in assessing the impact of a hospitalisation in the context of economic evaluations. This study had the goal of determining the impact of nonfatal hospitalisations on the quality of life of a cohort of patients previously diagnosed with heart failure by using their quality of life measurements before and after hospitalisation. METHODS: The impact of hospitalisation on health-related quality of life was estimated by calculating the difference in utility measured using the EQ-5D-3L in patients that were hospitalised and had records of utility before and after hospitalisation. The variation in differences between the utilities pre and post hospitalisation was explained through two multiple linear regression models using (1) the individual patient characteristics and (2) the hospitalisation characteristics as explanatory variables. RESULTS: The mean difference between health-related quality of life measurement pre and post hospitalisation was found to be 0.020 [95% CI: - 0.020, 0.059] when measured with the EQ-5D index, while there was a mean decrease of - 0.012 [95% CI: - 0.043, 0.020] in the utility measured with the visual analogue scale. Differences in utility variation according to the primary cause for hospitalisation were found. Regression models showed a statistically significant impact of body mass index and serum creatinine in the index utility differences and of serum creatinine for utilities measured with the visual analogue scale. CONCLUSIONS: Knowing the impact of hospitalisation on health-related quality of life is particularly relevant for informing cost-effectiveness studies designed to assess health technologies aimed at reducing hospital admissions. Through using patient-level data it was possible to estimate the variation in utilities before and after the average hospitalisation and for hospitalisations due to the most common causes for hospital admission. These estimates for (dis) utility could be used in the calculations of effectiveness on economic evaluations, especially when discrete event simulations are the employed modelling technique