2011
DOI: 10.1016/j.medengphy.2010.11.001
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Design of a complex bioimpedance spectrometer using DFT and undersampling for neural networks diagnostics

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Cited by 9 publications
(3 citation statements)
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“…With a low-cost system there will be fundamental limitations to both these metrics because cheaper components will not be able to match the performance of expensive laboratory impedance analysers. Therefore, the majority of the cost of low-cost impedance analysers are usually focused on the components that will directly influence the accuracy and precision of the measurement [7].…”
Section: Low-cost Design Trade-offsmentioning
confidence: 99%
“…With a low-cost system there will be fundamental limitations to both these metrics because cheaper components will not be able to match the performance of expensive laboratory impedance analysers. Therefore, the majority of the cost of low-cost impedance analysers are usually focused on the components that will directly influence the accuracy and precision of the measurement [7].…”
Section: Low-cost Design Trade-offsmentioning
confidence: 99%
“…Any changes in tissue physiology should produce changes in the tissue electrical properties [23]. Based on this phenomenon, BIA analysis has been widely used to identify or monitor the presence of various illnesses or conditions such as body fluid shift, blood flow, cardiac output, and muscular dystrophy [24][25][26][27][28][29][30][31][32][33][34][35][36][37]. Different tissues exhibit different electrical properties, in addition, tissue electrical properties change with respect to tissue status evolution.…”
Section: Tissue Identification and Monitoringmentioning
confidence: 99%
“…Other works [28,33,34] realized BIS measurements of singlefrequency and FS undersampling in hardware systems. Do Amaral et al [35] designed a FS BIS measuring instrument based on undersampling of high-frequency signals and used it in a preliminary study of head and neck cancer. Schmitz and Green [29,36] studied multisine undersampling theory and proposed several algorithms for optimizing the frequency distribution of multisine excitation.…”
Section: Introductionmentioning
confidence: 99%