DATA-ANALYSIS IN MULTIPLE-FREQUENCY BIOELECTRICAL-IMPEDANCE ANALYSIS

The performance of three analytical methods for multiple-frequency bio electrical impedance analysis (MFBIA) data was assessed. The methods w ere the established method of Cole and Cole, the newly proposed method of Siconolfi and co-workers and a modification of this procedure. Met hod performance was assessed from the adequacy of the curve fitting te chniques, as judged by the correlation coefficient and standard error of the estimate, and the accuracy of the different methods in determin ing the theoretical values of impedance parameters describing a set of model electrical circuits. The experimental data were well fitted by all curve-fitting procedures (r = 0.9 with SEE 0.3 to 3.5% or better f or most circuit-procedure combinations). Cole-Cole modelling provided the most accurate estimates of circuit impedance values, generally wit hin 1-2% of the theoretical values, followed by the Siconolfi procedur e using a sixth-order polynomial regression (1-6% variation). None of the methods, however, accurately estimated circuit parameters when the measured impedances were low (<20 Omega) reflecting the electronic li mits of the impedance meter used. These data suggest that Cole-Cole mo delling remains the preferred method for the analysis of MFBIA data.