Hook effect correction & resistance-based cole fitting prior cole model-based analysis: experimental validation

Preliminary study on parameterization of raw electrical bioimpedance data with 3 frequencies

This study tests the geometrical parameterization method for Electrical Bio-Impedance Spectroscopy (EBIS) readings previously proposed by one of the authors. This method uses the data of just three frequencies (therefore called 3P method). The test was carried out by the analysis of parameterization from 26 spectra (selected from 13 data sets) by the non-linear square (NLS) method, the 3P method and a combination of the two (3P-NLS). Additionally, the behaviour of the 3P method for 4 levels of noise and 3 different ways of segmenting the spectra were also explored with a MATLAB simulation of 400 spectra. Finally, a system for the classification of EBIS readings is presented, based on deviations of the raw data from the semi-circle obtained by the parameterization methods. Overall, the results suggest a very good performance of the 3P method when compared with the other two. The 3P method performs very well with levels of noise of 1 and 2%, but performs poorly with levels of noise of 5% and 10%. The results support the idea that the 3P method could be used with confidence for the parameterization of EBIS spectra, after the selection of three adequate frequencies according to specific applications.

A geometrical method for modeling bioelectrical impedance measurements and remove the hook effect deviations

OBJECTIVE

to describe a simple and straightforward method to calculate the circle parameters that can be used to fit Electrical Bioimpedance Spectroscopy (EBIS) raw data to the complex plane and remove the hook effect, a deviation of that model especially seen at higher frequencies and considered as an artifact due to instrumental limitations.

APPROACH

under the assumption that raw EBIS data in the middle frequencies best represent the beta dispersion, the authors of this article propose a geometrical procedure to calculate parameters for this dispersion and remove the hook effect. For this purpose, data obtained with two different devices were used with apparently very good results.

MAIN RESULTS

the results of this study suggest that circle parameters for the beta dispersion can be obtained, but, also, that the residuals of the hook effect correction seem to adjust to a circle and, therefore, they could also be parameterized using the same approach.

SIGNIFICANCE

the method proposed in this article is very easy to perform and could help end EBIS users not familiar with mathematical models and fitting processes, to better understand and interpret their data.

Bioimpedance Spectroscopy of the Breast

Background: Bioimpedance spectroscopy (BIS) measurements of breast lymphedema poses practical and technical challenges, in particular the determination of the resistance at zero frequency (R₀), the index of change in breast lymph content. Conventionally, R₀ is calculated from data analysis by using a procedure eponymously known as Cole modeling, a method that is error-prone in the breast. The aim of this study was to evaluate polynomial curve fitting as an alternative analytic procedure. Methods and Results: A sub-set of breast BIS measurements from 41 women with self-ascribed breast lymphedema obtained as part of the Breast Edema Exercise Trial (BEET) were analyzed by both the Cole and polynomial methods. BIS files for all subjects were able to be analyzed by using the polynomial method but only 73% and 88% of data files were analyzed for the affected and unaffected breasts, respectively, by using the Cole method. For those files that were capable of being analyzed by both methods, R₀ values were highly correlated (r = 0.99) but with a small (1.6%) although statistically significant difference (paired t test, p < 0.001) between methods. Conclusions: Analysis of BIS data using polynomial curve fitting is an acceptable and robust alternative to Cole modeling, particularly where impedance measurements are susceptible to technical sources of error of measurement. The small magnitude of difference observed between methods is unlikely to lead to misclassification of patients with lymphedema based on BIS assessment.