Electrical bioimpedance was used to detect local volume and aggregation changes in blood. This was done with two separate experimentation processes to improve upon current research methods. Abdominal internal hemorrhaging is bleeding and pooling of blood within the abdominal cavity which can put the welfare of the patient at risk and may cause organ failure. Electrical bioimpedance is the response of biological tissue to applied electrical current. In cooperation with Bioparhom, electrical bioimpedance was used as a detection device for abdominal internal hemorrhaging. It is hypothesized that electrical bioimpedance could be a non-invasive and cost effective avenue for the detection of internal bleeding. In this study we investigate the use of electrical bioimpedance with a custom 8x8 needle electrode array, for detecting and locating the blood pooling due to a drop in resistivity in a rat using a Z-Metrix (function generator by Bioparhom). 5 and 95 kHz signals were inputted into a dead rat experiencing internal bleeding of porcine blood at a rate of 3.33 ml/min to 10 ml. For 8 rats, the 5 kHz frequency was found to be more sensitive to internal blood pooling. Red blood cell aggregation is a physiological process where red blood cells form reversible aggregates. RBC aggregation is an important indicator for physicians for the health of the circulatory system. Utilizing electrical bioimpedance, it is hypothesized that a reactance change as a result of blood aggregation will be detected. As well, a method is developed using impedance spectroscopy to determine s frequency which exhibits the highest reactance change during blood aggregation. This sensitive frequency, found to be 304 kHz, is compared to a frequency used by previous studies (100 kHz) to validate its. Using the Z-Metrix (function generator by Bioparhom) with a custom 4 electrode configuration, 2 ml of porcine blood mixed with 2 mg/ml of EDTA is tested for 2 minutes at a single frequency. The 304 kHz is found to be the most sensitive of the frequencies tested to reactance changes during aggregation. Results found for blood samples give an average AIc of 27.32 ± 11.44, which is within the physiological range for porcine blood of 3-30. It is seen that the 304 kHz has a higher precision than the 100 kHz frequency, but the AIc is within the same magnitude. As a result, 304 kHz is found to be a more favorable frequency than the previously published 100 kHz for the trials performed based on precision of the results and the sensitivity of the reactance change to blood aggregation.

Electrical bioimpedance was used to detect local volume and aggregation changes in blood. This was done with two separate experimentation processes to improve upon current research methods. Abdominal internal hemorrhaging is bleeding and pooling of blood within the abdominal cavity which can put the welfare of the patient at risk and may cause organ failure. Electrical bioimpedance is the response of biological tissue to applied electrical current. In cooperation with Bioparhom, electrical bioimpedance was used as a detection device for abdominal internal hemorrhaging. It is hypothesized that electrical bioimpedance could be a non-invasive and cost effective avenue for the detection of internal bleeding. In this study we investigate the use of electrical bioimpedance with a custom 8x8 needle electrode array, for detecting and locating the blood pooling due to a drop in resistivity in a rat using a Z-Metrix (function generator by Bioparhom). 5 and 95 kHz signals were inputted into a dead rat experiencing internal bleeding of porcine blood at a rate of 3.33 ml/min to 10 ml. For 8 rats, the 5 kHz frequency was found to be more sensitive to internal blood pooling. Red blood cell aggregation is a physiological process where red blood cells form reversible aggregates. RBC aggregation is an important indicator for physicians for the health of the circulatory system. Utilizing electrical bioimpedance, it is hypothesized that a reactance change as a result of blood aggregation will be detected. As well, a method is developed using impedance spectroscopy to determine s frequency which exhibits the highest reactance change during blood aggregation. This sensitive frequency, found to be 304 kHz, is compared to a frequency used by previous studies (100 kHz) to validate its. Using the Z-Metrix (function generator by Bioparhom) with a custom 4 electrode configuration, 2 ml of porcine blood mixed with 2 mg/ml of EDTA is tested for 2 minutes at a single frequency. The 304 kHz is found to be the most sensitive of the frequencies tested to reactance changes during aggregation. Results found for blood samples give an average AIc of 27.32 ± 11.44, which is within the physiological range for porcine blood of 3-30. It is seen that the 304 kHz has a higher precision than the 100 kHz frequency, but the AIc is within the same magnitude. As a result, 304 kHz is found to be a more favorable frequency than the previously published 100 kHz for the trials performed based on precision of the results and the sensitivity of the reactance change to blood aggregation.

Neurologically related injuries cause a similar number of deaths ascancer, and brain damage is the second commonest cause of death in theworld and probably the leading cause of permanent disability. Thedevastating effects of most cases of brain damage could be avoided if itwere detected and medical treatment initiated in time. The passiveelectrical properties of biological tissue have been investigated for almost acentury and electrical bioimpedance studies in neurology have beenperformed for more than 50 years. Even considering the extensive effortsdedicated to investigating potential applications of electrical bioimpedancefor brain monitoring, especially in the last 20 years, and the specificallyacute need for such non-invasive and efficient diagnosis support tools,Electrical Bioimpedance technology has not made the expectedbreakthrough into clinical application yet. In order to reach this stage inthe age of evidence-based medicine, the first essential step is todemonstrate the biophysical basis of the method under study. The presentresearch work confirms that the cell swelling accompanying thehypoxic/ischemic injury mechanism modifies the electrical properties ofbrain tissue, and shows that by measuring the complex electricalbioimpedance it is possible to detect the changes resulting from braindamage. For the development of a successful monitoring method, after thevital biophysical validation it is critical to have available the properelectrical bioimpedance technology and to implement an efficient protocolof use. Electronic instrumentation is needed for broadband spectroscopymeasurements of complex electrical bioimpedance; the selection of theelectrode setup is crucial to obtain clinically relevant measurements, andthe proper biosignal analysis and processing is the core of the diagnosissupport system. This work has focused on all these aspects since they arefundamental for providing the solid medico-technological backgroundnecessary to enable the clinical usage of Electrical Bioimpedance forcerebral monitoring.

Electrical bioimpedance spectroscopy (EBIS) has been used to assess the status or composition of various types of tissue, and examples of EBIS include body composition analysis (BCA) and tissue characterisation for skin cancer detection. EBIS is a non-invasive method that has the potential to provide a large amount of information for diagnosis or monitoring purposes, such as the monitoring of pulmonary oedema, i.e., fluid accumulation in the lungs. However, in many cases, systems based on EBIS have not become generally accepted in clinical practice. Possible reasons behind the low acceptance of EBIS could involve inaccurate models; artefacts, such as those from movements; measurement errors; and estimation errors. Previous thoracic EBIS measurements aimed at pulmonary oedema have shown some uncertainties in their results, making it difficult to produce trustworthy monitoring methods. The current research hypothesis was that these uncertainties mostly originate from estimation errors. In particular, time-varying behaviours of the thorax, e.g., respiratory and cardiac activity, can cause estimation errors, which make it tricky to detect the slowly varying behaviour of this system, i.e., pulmonary oedema. The aim of this thesis is to investigate potential sources of estimation error in transthoracic impedance spectroscopy (TIS) for pulmonary oedema detection and to propose methods to prevent or compensate for these errors.   This work is mainly focused on two aspects of impedance spectrum estimation: first, the problems associated with the delay between estimations of spectrum samples in the frequency-sweep technique and second, the influence of undersampling (a result of impedance estimation times) when estimating an EBIS spectrum. The delay between frequency sweeps can produce huge errors when analysing EBIS spectra, but its effect decreases with averaging or low-pass filtering, which is a common and simple method for monitoring the time-invariant behaviour of a system. The results show the importance of the undersampling effect as the main estimation error that can cause uncertainty in TIS measurements.  The best time for dealing with this error is during the design process, when the system can be designed to avoid this error or with the possibility to compensate for the error during analysis. A case study of monitoring pulmonary oedema is used to assess the effect of these two estimation errors. However, the results can be generalised to any case for identifying the slowly varying behaviour of physiological systems that also display higher frequency variations.  Finally, some suggestions for designing an EBIS measurement system and analysis methods to avoid or compensate for these estimation errors are discussed. / <p>QC 20140604</p>

Introdução: O conjunto de alterações de composição corporal e metabólicas encontrada em pacientes soropositivos para HIV é denominado de síndrome da lipodistrofia O ponto central da síndrome são as alterações da composição corporal que envolve a lipoatrofia em membros e face e/ou lipohipertrofia abdominal e dorso cervical. Até o momento, nesse grupo a determinação de gordura por segmento corporal pode ser obtida por métodos como a absorciometria dos raios X de dupla energia (DXA), mas não por medidas antropométricas e de bioimpedância elétrica (BIA), que seriam mais viáveis na prática clínica. Objetivos: Elaborar equações por regressão linear para estimativa de gordura em cada segmento (braço, perna e tronco) considerando variáveis antropométricas e de BIA segmentar e propor pontos de corte para classificar a lipodistrofia em pacientes soropositivos para HIV em terapia antirretroviral de alta potência (TARV). Métodos: Foram aferidas circunferências (braço, cintura, quadril, coxa, panturrilha), pregas cutâneas (bíceps, tríceps, subescapular, suprailíaca) e realizados exames de BIA segmentar e DXA em 100 pacientes soropositivos para HIV do sexo masculino. A partir destas variáveis foram elaboradas equações para estimativa de gordura por segmentos (braço, perna e tronco). Para propor pontos de corte foram utilizadas as curvas ROC utilizando o exame clínico para identificação da sensibilidade e especificidade. Resultados: Foram elaboradas 2 modelos para braço e tronco utilizando apenas medidas antropométricas e 2 modelos para a perna utilizando variáveis de BIA e antropométricas. Os coeficientes de determinações para os modelos de braço, tronco, pernas foram: 0.66 e 0.66; 0.76 e 0.75; 0.5 e 0.45, respectivamente. As razões propostas foram: circunferência da cintura pela circunferência da coxa (CC/CCo), circunferência da cintura pela da panturrilha (CC/CPant) e razão tronco braço (RTB). Os melhores pontos de corte observados para CC/CCo, RTB e para o índice já proposto na literatura fat mass ratio (FMR) foram de 1,74; 2,08 e 1,26, respectivamente. Conclusões: As equações e razões antropométricas podem ser utilizados para auxiliar no diagnóstico de lipodistrofia com a finalidade de contribuir para um diagnóstico mais acurado e precoce possibilitando intervenções e até prevenindo maiores alterações da composição corporal. / Background: The changes in body composition and metabolic parameters, found in HIV seropositive is called lipodystrophy syndrome. The central point of the syndrome are changes in body composition that involves the face and limb lipoatrophy and / or abdominal back neck lipohypertrophy. Until now, in this group of individual, the determination of fat per body segment can be obtained by methods such as X-ray absorptiometry dual energy absorptiometry (DXA), but not by anthropometric measurements and bioelectrical impedance analysis (BIA), which would be more feasible in practice clinic. Objectives: Develop equations, using linear regression, to estimate fat in each segment (arm, leg and trunk) considering anthropometric variables and segmental BIA and propose cutoff points for classifying lipodystrophy in HIV seropositive patients on highly active antiretroviral therapy (HAART). Methods: We measured circumferences (arm, waist, hip, thigh, calf), skinfolds (biceps, triceps, subscapular, suprailiac) and conducted examinations of segmental BIA and DXA in 100 HIV seropositive men. From these variables were developed equations to estimate fat segments (arm, leg and trunk). To propose cutoffs were used ROC curves using clinical examination to identify the sensitivity and specificity. Results: We developed two models for arm and trunk using only anthropometric measurements and two models for leg using BIA and anthropometric variables. The coefficients of determination for models of arm, trunk and leg were 0.66 and 0.66, 0.76 and 0.75, 0.5 and 0.45, respectively. The proposed reasons were: waist circumference by the circumference of the thigh (WC / CTh), waist circumference by the calf (WC / Cca) and trunk arm ratio (TAR). The best cutoff points observed for WC/CTh , TAR and the index already proposed in the literature fat mass ratio (FMR) were 1.74, 2.08 and 1.26, respectively. Conclusions: The anthropometric reasons and the equations can be used to aid in the diagnosis of lipodystrophy in order to contribute to a more accurate diagnosis and early intervention and to prevent possible major changes in body composition.

In recent years, due to the combination of technological advances in the fields ofmeasurement instrumentation, communications, home-health care and textile-technology thedevelopment of medical devices has shifted towards applications of personal healthcare.There are well known the available solutions for heart rate monitoring successfully providedby Polar and Numetrex. Furthermore new monitoring applications are also investigated. Amongthese non-invasive monitoring applications, it is possible to find several ones enable bymeasurements of Electrical Bioimpedance.Analog Devices has developed the AD5933 Impedance Network Analyzer which facilitatesto a large extent the design and implementation of Electrical Bioimpedance Spectrometers in amuch reduced space. Such small size allows the development of a fully wearable bioimpedancemeasurement.With the development of a Electrical Bioimpedance-enable wearable medical device in focusfor personal healthcare monitoring, in this project, the issue of power management has beentargeted and a battery-driven Electrical Bioimpedance Spectrometer based in the AD5933 hasbeen implemented. The resulting system has the possibility to operate with a Li-Po battery with apower autonomy over 17 hours.

Nowadays, the Electrical Bioimpedance (EBI) measurements have become a commonpractice as they are useful for different clinical applications. EBI technology and EBImeasurement systems are relatively simple when compared to other type of medicalinstrumentation. But even in such simple measurement systems measurement artifact mayoccur. One of the most common artifacts present measurements is the Hook Effect, which isidentifiable by the hook-alike deviation on the EBI data that it produces on the impedanceplot.The Hook Effect influences typical EBI data analysis processes like Cole fitting processand the estimation of the Cole parameters, which are critical for several EBI applications.Therefore the Hook Effect must be corrected, compensated or removed before the any fittingprocess.With the goal of finding a reliable correction method the origin and the impact on theEBI measurement of the Hook Effect is studied in this thesis. The currently used Tdcompensation method is also studied and a new approach for compensation and correction ispresented.The results indicate that the proposed method truly corrects the Hook Effect and that themethodology to select the correcting parameters is solid based on the origin of the Hook Effectand it is extracted from the EBI measurement it-self avoiding any external dependency.

The concept of Electrical Bio Impedance prevails in this thesis. The EBI measurement which is used for obtaining the body composition is, by virtue of time becoming of great use as its one of the easiest method of finding out the body composition. In simple words, EBI is the opposition offered by the body to the current. It is just like another analysis tool. The result is only as good as the test is done. In this thesis, we have done the analysis on the neonatal EBI measurements of two kinds.In this work, 293 measurements are obtained from 12 babies and 230 measurements are obtained from 7 babies have been analyzed with the purpose of obtaining reference values for the spectrum of complex EBI. The analysis uses both statistical and model approach of obtaining reference values and in order to fit the given data, Cole model analysis is used.Filters were applied to get the highest degree of correctness. In the due course of the filtering, it was found that the measurements from some babies have been deleted. The Standard Error of Estimation (S.E.E.) is a parameter used for obtaining the further reliable and most probable output. The further analysis is done using MATLAB and the results are been compared to the previous analysis report.

Electrical Bioimpedance measurement has been used in clinical practice for several years for non-invasive monitoring. In recent years new applications of electrical bioimpedance measurements based in the spectral analysis has been validated.This fact have encouraged the use of spectral analysis on Electrical Bioimpedance measurements and it is a wide spread idea that spectral analysis of electrical bioimpedance data is going to open the door for new indicators for health assessment.The intended goal of this project is to develop a software tool, based in Matlab, that allows researchers to perform, both spectral and time signal analysis on the measurements performed Electrical Bioimpedance Spectrometers. This tool must incorporate the necessary display capabilities to allow quick visual inspection and visualization of the analysis results.Once this tool has been implemented, spectral analysis and validation of classification features will be possible in an easy way accelerating the process of test and analysis of experimental data analysis. This task is always critical in any research or clinical study.To facilitate the spectral analysis of electrical bioimpedance data will contribute to the developing of novel methods of non-invasive diagnosis and monitoring. / Uppsatsnivå: D

Electrical Bioimpedance (EBI) is the opposition offered by the biological material to theflow of electric current. Nowadays EBI technology is widely used for total body compositionand body fluid distribution.In this project a software suite is developed by using the GUI tool of Matlab, thissoftware is meant to help to remove artefacts from the EBI measurement and to visualize theEBIS measurements and the processing performed on them.Hook effect is one of the major artefacts found in EBI measurements, which createsproblems in any analysis. To eliminate the Hook effect some methods are followed. The data’sare processed using these methods and they are visualized. For the better understanding, bothraw data and the corrected data are plotted in impedance and admittance plots. The correcteddata is stored for further use and analysis.