Bioelectrical Impedance Methods for Noninvasive Health Monitoring: A Review.
17 Jun 2014-Vol. 2014, pp 381251-381251
TL;DR: The working principles, applications, merits, and demerits of these methods has been discussed in detail along with their other technical issues followed by present status and future trends.
Abstract: Under the alternating electrical excitation, biological tissues produce a complex electrical impedance which depends on tissue composition, structures, health status, and applied signal frequency, and hence the bioelectrical impedance methods can be utilized for noninvasive tissue characterization. As the impedance responses of these tissue parameters vary with frequencies of the applied signal, the impedance analysis conducted over a wide frequency band provides more information about the tissue interiors which help us to better understand the biological tissues anatomy, physiology, and pathology. Over past few decades, a number of impedance based noninvasive tissue characterization techniques such as bioelectrical impedance analysis (BIA), electrical impedance spectroscopy (EIS), electrical impedance plethysmography (IPG), impedance cardiography (ICG), and electrical impedance tomography (EIT) have been proposed and a lot of research works have been conducted on these methods for noninvasive tissue characterization and disease diagnosis. In this paper BIA, EIS, IPG, ICG, and EIT techniques and their applications in different fields have been reviewed and technical perspective of these impedance methods has been presented. The working principles, applications, merits, and demerits of these methods has been discussed in detail along with their other technical issues followed by present status and future trends.
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08 Aug 2019
TL;DR: Calibration studies show that LEBISDI not only interpreted the simulated and circuit-element data accurately, but also successfully interpreted tissues impedance data and estimated the capacitive and resistive components produced by the compositions biological cells.
Abstract: Under an alternating electrical signal, biological tissues produce a complex electrical bioimpedance that is a function of tissue composition and applied signal frequencies. By studying the bioimpedance spectra of biological tissues over a wide range of frequencies, we can noninvasively probe the physiological properties of these tissues to detect possible pathological conditions. Electrical impedance spectroscopy can provide the spectra that are needed to calculate impedance parameters within a wide range of frequencies. Before impedance parameters can be calculated and tissue information extracted, impedance spectra should be processed and analyzed by a dedicated software program. National Instruments (NI) Inc. offers LabVIEW, a fast, portable, robust, user-friendly platform for designing data-analyzing software. We developed a LabVIEW-based electrical bioimpedance spectroscopic data interpreter (LEBISDI) to analyze the electrical impedance data for tissue characterization in medical, biomedical and biological applications. Here, we test, calibrate and evaluate the performance of LEBISDI on the impedance data obtained from simulation studies, electronic circuit element combinations as well as various biological tissues. We analyze the Nyquist plots obtained from the electrical impedance spectroscopy (EIS) measurements and compare the equivalent circuit parameters calculated by LEBISDI with the corresponding original circuit parameters to assess the accuracy of the program developed. Calibration studies show that LEBISDI accurately interpreted simulated and circuit-element data. Furthermore, results obtained from biological tissues show that LEBISDI successfully interpreted bioimpedance data and estimates of capacitance and resistance data. Finally, LEBISDI efficiently calculated and analyzed variation in bioimpedance parameters of different tissue compositions, health and temperatures. LEBISDI can also be used for human tissue impedance analysis for electrical impedance-based biopsy or cancer diagnosis.
23 citations
Cites background or methods from "Bioelectrical Impedance Methods for..."
...LEBISDI can also be potentially applied for multifrequency bioelectrical impedance analysis (BIA) based tissue composition assessment, electrical impedance-based tissue characterization and [95-96] or disease diagnosis [97-98] and EIS based tissue health characterization in biological, biomedical, medical and clinical applications [99-106]....
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...Many researchers [7-23] have investigated electrical bioimpedance as an effective, noninvasive method to probe the pathological status of biological tissues....
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...For example, bioelectrical impedance analysis (BIA) [7-10], electrical impedance spectroscopy (EIS) [11-21], impedance plethysmography (IPG) [22-23] and impedance cardiography (ICG) [24-26] reveal the impedance response of biological tissues at one, two or more specified frequencies (f)....
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01 Mar 2018
TL;DR: The paper demonstrates the simulation of alternating current conduction through biological tissues conducted by COMSOL Multiphysics, which shows the frequency response of the tissue impedance for different tissue compositions.
Abstract: Biological tissues are developed with biological cells which exhibit complex electrical impedance called electrical bioimpedance. Under an alternating electrical excitation the bioimpedance varies with the tissue anatomy, composition and the signal frequency. The current penetration and conduction paths vary with frequency of the applied signal. Bioimpedance spectroscopy is used to study the frequency response of the electrical impedance of biological materials noninvasively. In bioimpedance spectroscopy, a low amplitude electrical signal is injected to the tissue sample or body parts to characterization the sample in terms of its bioimpedance. The electrical current conduction phenomena, which is highly influenced by the tissue impedance and the signal frequency, is an important phenomena which should be studied to understand the bioimpedance techniques like bioelectrical impedance analysis (BIA), EIS, or else. In this paper the origin of bioelectrical impedance and current conduction phenomena has been reviewed to present a brief summary of bioelectrical impedance and the frequency dependent current conduction through biological tissues. Simulation studies are conducted with alternation current injection through a two dimensional model of biological tissues containing finite number of biological cells suspended in extracellular fluid. The paper demonstrates the simulation of alternating current conduction through biological tissues conducted by COMSOL Multiphysics. Simulation studies also show the frequency response of the tissue impedance for different tissue compositions.
23 citations
TL;DR: In this paper, the authors summarized the current state of hemodynamic monitoring through BIA in terms of different configurations and devices in the market, highlighting the suitable range of frequencies (1 kHz-1 MHz) as well as safety considerations for a BIA setup.
Abstract: Recent advances in hemodynamic monitoring have seen the advent of non-invasive methods which offer ease of application and improve patient comfort. Bioimpedance Analysis or BIA is one of the currently employed non-invasive techniques for hemodynamic monitoring. Impedance Cardiography (ICG), one of the implementations of BIA, is widely used as a non-invasive procedure for estimating hemodynamic parameters such as stroke volume (SV) and cardiac output (CO). Even though BIA is not a new diagnostic technique, it has failed to gain consensus as a reliable measure of hemodynamic parameters. Several devices have emerged for estimating CO using ICG which are based on evolving methodologies and techniques to calculate SV. However, the calculations are generally dependent on the electrode configurations (whole body, segmental or localised) as well as the accuracy of different techniques in tracking blood flow changes. Blood volume changes, concentration of red blood cells, pulsatile velocity profile and ambient temperature contribute to the overall conductivity of blood and hence its impedance response during flow. There is a growing interest in investigating limbs for localised BIA to estimate hemodynamic parameters such as pulse wave velocity. As such, this paper summarises the current state of hemodynamic monitoring through BIA in terms of different configurations and devices in the market. The conductivity of blood flow has been emphasized with contributions from both volume and velocity changes during flow. Recommendations for using BIA in hemodynamic monitoring have been mentioned highlighting the suitable range of frequencies (1 kHz-1 MHz) as well as safety considerations for a BIA setup. Finally, current challenges in using BIA such as geometry assumption and inaccuracies have been discussed while mentioning potential advantages of a multi-frequency analysis to cover all the major contributors to blood's impedance response during flow.
22 citations
TL;DR: In this paper, an alternative processing technique based on the use of pulsed laser irradiation is proposed to identify the processing parameters that result in selective removal of the electrically insulating resin with minimum surface fiber damage, and a quantitative analysis of the electrical contact resistance is presented and the results are compared with those obtained using sanding.
22 citations
Posted Content•
TL;DR: This dissertation presents an approach to build a personal model and dynamically estimate the health state of an individual by fusing multi-modal data and domain knowledge and concludes by presenting this framework of combining the healthState and personal graph model to perpetually plan and assist us in living life towards the authors' goals.
Abstract: Author(s): Nag, Nitish | Advisor(s): Jain, Ramesh C | Abstract: Life's most valuable asset is health. Continuously understanding the state of our health and modeling how it evolves is essential if we wish to improve it. Given the opportunity that people live with more data about their life today than any other time in history, the challenge rests in interweaving this data with the growing body of knowledge to compute and model the health state of an individual continually.This dissertation presents an approach to build a personal model and dynamically estimate the health state of an individual by fusing multi-modal data and domain knowledge. The system is stitched together from four essential abstraction elements: 1. the events in our life, 2. the layers of our biological systems (from molecular to an organism), 3. the functional utilities that arise from biological underpinnings, and 4. how we interact with these utilities in the reality of daily life. Connecting these four elements via graph network blocks forms the backbone by which we instantiate a digital twin of an individual. Edges and nodes in this graph structure are then regularly updated with learning techniques as data is continuously digested. Experiments demonstrate the use of dense and heterogeneous real-world data from a variety of personal and environmental sensors to monitor individual cardiovascular health state.State estimation and individual modeling is the fundamental basis for many revolutionary efforts in health. Continuous access to the individual's state allows a departure from disease-oriented approaches, to a total health continuum paradigm. Precision in predicting health requires a detailed understanding of an individual and their trajectory. By encasing this state estimation within a navigational approach, a user can use a systematic guidance framework to plan actions for each moment to transition their current state towards a desired one. This work concludes by presenting this framework of combining the health state and personal graph model to perpetually plan and assist us in living life towards our goals.
21 citations
References
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01 Nov 2011TL;DR: In this paper, the authors focus on topics at the forefront of electrochemical research, such as splitting water by electrolysis, splitting water with visible light, and the recent development of lithium batteries.
Abstract: This book focuses on topics at the forefront of electrochemical research. Splitting water by electrolysis; splitting water by visible light; the recent development of lithium batteries; theoretical approaches to intercalation; and fundamental concepts of electrode kinetics, particularly as applied to semiconductors are discussed. It is recommended for electrochemists, physical chemists, corrosion scientists, and those working in the fields of analytical chemistry, surface and colloid science, materials science, electrical engineering, and chemical engineering.
5,927 citations
04 Apr 2005
Abstract: Preface. Preface to the First Edition. Contributors. Contributors to the First Edition. Chapter 1. Fundamentals of Impedance Spectroscopy (J.Ross Macdonald and William B. Johnson). 1.1. Background, Basic Definitions, and History. 1.1.1 The Importance of Interfaces. 1.1.2 The Basic Impedance Spectroscopy Experiment. 1.1.3 Response to a Small-Signal Stimulus in the Frequency Domain. 1.1.4 Impedance-Related Functions. 1.1.5 Early History. 1.2. Advantages and Limitations. 1.2.1 Differences Between Solid State and Aqueous Electrochemistry. 1.3. Elementary Analysis of Impedance Spectra. 1.3.1 Physical Models for Equivalent Circuit Elements. 1.3.2 Simple RC Circuits. 1.3.3 Analysis of Single Impedance Arcs. 1.4. Selected Applications of IS. Chapter 2. Theory (Ian D. Raistrick, Donald R. Franceschetti, and J. Ross Macdonald). 2.1. The Electrical Analogs of Physical and Chemical Processes. 2.1.1 Introduction. 2.1.2 The Electrical Properties of Bulk Homogeneous Phases. 2.1.2.1 Introduction. 2.1.2.2 Dielectric Relaxation in Materials with a Single Time Constant. 2.1.2.3 Distributions of Relaxation Times. 2.1.2.4 Conductivity and Diffusion in Electrolytes. 2.1.2.5 Conductivity and Diffusion-a Statistical Description. 2.1.2.6 Migration in the Absence of Concentration Gradients. 2.1.2.7 Transport in Disordered Media. 2.1.3 Mass and Charge Transport in the Presence of Concentration Gradients. 2.1.3.1 Diffusion. 2.1.3.2 Mixed Electronic-Ionic Conductors. 2.1.3.3 Concentration Polarization. 2.1.4 Interfaces and Boundary Conditions. 2.1.4.1 Reversible and Irreversible Interfaces. 2.1.4.2 Polarizable Electrodes. 2.1.4.3 Adsorption at the Electrode-Electrolyte Interface. 2.1.4.4 Charge Transfer at the Electrode-Electrolyte Interface. 2.1.5 Grain Boundary Effects. 2.1.6 Current Distribution, Porous and Rough Electrodes- the Effect of Geometry. 2.1.6.1 Current Distribution Problems. 2.1.6.2 Rough and Porous Electrodes. 2.2. Physical and Electrochemical Models. 2.2.1 The Modeling of Electrochemical Systems. 2.2.2 Equivalent Circuits. 2.2.2.1 Unification of Immitance Responses. 2.2.2.2 Distributed Circuit Elements. 2.2.2.3 Ambiguous Circuits. 2.2.3 Modeling Results. 2.2.3.1 Introduction. 2.2.3.2 Supported Situations. 2.2.3.3 Unsupported Situations: Theoretical Models. 2.2.3.4 Unsupported Situations: Equivalent Network Models. 2.2.3.5 Unsupported Situations: Empirical and Semiempirical Models. Chapter 3. Measuring Techniques and Data Analysis. 3.1. Impedance Measurement Techniques (Michael C. H. McKubre and Digby D. Macdonald). 3.1.1 Introduction. 3.1.2 Frequency Domain Methods. 3.1.2.1 Audio Frequency Bridges. 3.1.2.2 Transformer Ratio Arm Bridges. 3.1.2.3 Berberian-Cole Bridge. 3.1.2.4 Considerations of Potentiostatic Control. 3.1.2.5 Oscilloscopic Methods for Direct Measurement. 3.1.2.6 Phase-Sensitive Detection for Direct Measurement. 3.1.2.7 Automated Frequency Response Analysis. 3.1.2.8 Automated Impedance Analyzers. 3.1.2.9 The Use of Kramers-Kronig Transforms. 3.1.2.10 Spectrum Analyzers. 3.1.3 Time Domain Methods. 3.1.3.1 Introduction. 3.1.3.2 Analog-to-Digital (A/D) Conversion. 3.1.3.3 Computer Interfacing. 3.1.3.4 Digital Signal Processing. 3.1.4 Conclusions. 3.2. Commercially Available Impedance Measurement Systems (Brian Sayers). 3.2.1 Electrochemical Impedance Measurement Systems. 3.2.1.1 System Configuration. 3.2.1.2 Why Use a Potentiostat? 3.2.1.3 Measurements Using 2, 3 or 4-Terminal Techniques. 3.2.1.4 Measurement Resolution and Accuracy. 3.2.1.5 Single Sine and FFT Measurement Techniques. 3.2.1.6 Multielectrode Techniques. 3.2.1.7 Effects of Connections and Input Impedance. 3.2.1.8 Verification of Measurement Performance. 3.2.1.9 Floating Measurement Techniques. 3.2.1.10 Multichannel Techniques. 3.2.2 Materials Impedance Measurement Systems. 3.2.2.1 System Configuration. 3.2.2.2 Measurement of Low Impedance Materials. 3.2.2.3 Measurement of High Impedance Materials. 3.2.2.4 Reference Techniques. 3.2.2.5 Normalization Techniques. 3.2.2.6 High Voltage Measurement Techniques. 3.2.2.7 Temperature Control. 3.2.2.8 Sample Holder Considerations. 3.3. Data Analysis (J. Ross Macdonald). 3.3.1 Data Presentation and Adjustment. 3.3.1.1 Previous Approaches. 3.3.1.2 Three-Dimensional Perspective Plotting. 3.3.1.3 Treatment of Anomalies. 3.3.2 Data Analysis Methods. 3.3.2.1 Simple Methods. 3.3.2.2 Complex Nonlinear Least Squares. 3.3.2.3 Weighting. 3.3.2.4 Which Impedance-Related Function to Fit? 3.3.2.5 The Question of "What to Fit" Revisited. 3.3.2.6 Deconvolution Approaches. 3.3.2.7 Examples of CNLS Fitting. 3.3.2.8 Summary and Simple Characterization Example. Chapter 4. Applications of Impedance Spectroscopy. 4.1. Characterization of Materials (N. Bonanos, B. C. H. Steele, and E. P. Butler). 4.1.1 Microstructural Models for Impedance Spectra of Materials. 4.1.1.1 Introduction. 4.1.1.2 Layer Models. 4.1.1.3 Effective Medium Models. 4.1.1.4 Modeling of Composite Electrodes. 4.1.2 Experimental Techniques. 4.1.2.1 Introduction. 4.1.2.2 Measurement Systems. 4.1.2.3 Sample Preparation-Electrodes. 4.1.2.4 Problems Associated With the Measurement of Electrode Properties. 4.1.3 Interpretation of the Impedance Spectra of Ionic Conductors and Interfaces. 4.1.3.1 Introduction. 4.1.3.2 Characterization of Grain Boundaries by IS. 4.1.3.3 Characterization of Two-Phase Dispersions by IS. 4.1.3.4 Impedance Spectra of Unusual Two-phase Systems. 4.1.3.5 Impedance Spectra of Composite Electrodes. 4.1.3.6 Closing Remarks. 4.2. Characterization of the Electrical Response of High Resistivity Ionic and Dielectric Solid Materials by Immittance Spectroscopy (J. Ross Macdonald). 4.2.1 Introduction. 4.2.2 Types of Dispersive Response Models: Strengths and Weaknesses. 4.2.2.1 Overview. 4.2.2.2 Variable-slope Models. 4.2.2.3 Composite Models. 4.2.3 Illustration of Typical Data Fitting Results for an Ionic Conductor. 4.3. Solid State Devices (William B. Johnson and Wayne L. Worrell). 4.3.1 Electrolyte-Insulator-Semiconductor (EIS) Sensors. 4.3.2 Solid Electrolyte Chemical Sensors. 4.3.3 Photoelectrochemical Solar Cells. 4.3.4 Impedance Response of Electrochromic Materials and Devices (Gunnar A. Niklasson, Anna Karin Johsson, and Maria Stromme). 4.3.4.1 Introduction. 4.3.4.2 Materials. 4.3.4.3 Experimental Techniques. 4.3.4.4 Experimental Results on Single Materials. 4.3.4.5 Experimental Results on Electrochromic Devices. 4.3.4.6 Conclusions and Outlook. 4.3.5 Time-Resolved Photocurrent Generation (Albert Goossens). 4.3.5.1 Introduction-Semiconductors. 4.3.5.2 Steady-State Photocurrents. 4.3.5.3 Time-of-Flight. 4.3.5.4 Intensity-Modulated Photocurrent Spectroscopy. 4.3.5.5 Final Remarks. 4.4. Corrosion of Materials (Digby D. Macdonald and Michael C. H. McKubre). 4.4.1 Introduction. 4.4.2 Fundamentals. 4.4.3 Measurement of Corrosion Rate. 4.4.4 Harmonic Analysis. 4.4.5 Kramer-Kronig Transforms. 4.4.6 Corrosion Mechanisms. 4.4.6.1 Active Dissolution. 4.4.6.2 Active-Passive Transition. 4.4.6.3 The Passive State. 4.4.7 Point Defect Model of the Passive State (Digby D. Macdonald). 4.4.7.1 Introduction. 4.4.7.2 Point Defect Model. 4.4.7.3 Electrochemical Impedance Spectroscopy. 4.4.7.4 Bilayer Passive Films. 4.4.8 Equivalent Circuit Analysis (Digby D. Macdonald and Michael C. H. McKubre). 4.4.8.1 Coatings. 4.4.9 Other Impedance Techniques. 4.4.9.1 Electrochemical Hydrodynamic Impedance (EHI). 4.4.9.2 Fracture Transfer Function (FTF). 4.4.9.3 Electrochemical Mechanical Impedance. 4.5. Electrochemical Power Sources. 4.5.1 Special Aspects of Impedance Modeling of Power Sources (Evgenij Barsoukov). 4.5.1.1 Intrinsic Relation Between Impedance Properties and Power Sources Performance. 4.5.1.2 Linear Time-Domain Modeling Based on Impedance Models, Laplace Transform. 4.5.1.3 Expressing Model Parameters in Electrical Terms, Limiting Resistances and Capacitances of Distributed Elements. 4.5.1.4 Discretization of Distributed Elements, Augmenting Equivalent Circuits. 4.5.1.5 Nonlinear Time-Domain Modeling of Power Sources Based on Impedance Models. 4.5.1.6 Special Kinds of Impedance Measurement Possible with Power Sources-Passive Load Excitation and Load Interrupt. 4.5.2 Batteries (Evgenij Barsoukov). 4.5.2.1 Generic Approach to Battery Impedance Modeling. 4.5.2.2 Lead Acid Batteries. 4.5.2.3 Nickel Cadmium Batteries. 4.5.2.4 Nickel Metal-hydride Batteries. 4.5.2.5 Li-ion Batteries. 4.5.3 Impedance Behavior of Electrochemical Supercapacitors and Porous Electrodes (Brian E. Conway). 4.5.3.1 Introduction. 4.5.3.2 The Time Factor in Capacitance Charge or Discharge. 4.5.3.3 Nyquist (or Argand) Complex-Plane Plots for Representation of Impedance Behavior. 4.5.3.4 Bode Plots of Impedance Parameters for Capacitors. 4.5.3.5 Hierarchy of Equivalent Circuits and Representation of Electrochemical Capacitor Behavior. 4.5.3.6 Impedance and Voltammetry Behavior of Brush Electrode Models of Porous Electrodes. 4.5.3.7 Impedance Behavior of Supercapacitors Based on Pseudocapacitance. 4.5.3.8 Deviations of Double-layer Capacitance from Ideal Behavior: Representation by a Constant-phase Element (CPE). 4.5.4 Fuel Cells (Norbert Wagner). 4.5.4.1 Introduction. 4.5.4.2 Alkaline Fuel Cells (AFC). 4.5.4.3 Polymer Electrolyte Fuel Cells (PEFC). 4.5.4.4 Solid Oxide Fuel Cells (SOFC). Appendix. Abbreviations and Definitions of Models. References. Index.
5,212 citations
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Abstract: A CO2-laser-based photoacoustic spectrometer was used to determine the temporal concentration profile of atmospheric ethene in Mexico City. Ethene measurements were conducted at the facilities of our institute, which is located in the north of the city and next to an avenue with heavy traffic density. Ambient air from outside our laboratory was continuously pumped into the spectrometer. This campaign was performed for 24 h a day, from November 24–30, 2001. The maximum ethene levels ranged between 26 and 81 ppbV. As expected, the lowest concentrations were monitored on weekends. These data were analyzed in combination with ozone and nitrogen oxides profiles, which were permanently monitored by an air-pollution-monitoring government network. Information on the seasonal variability of ethene was obtained by comparing the results of this campaign with data obtained in the winter of 2001. In general, the ethene concentration in November was about 30% higher than in February. On weekdays, the mean dose of human...
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