title: Fuzzy linguistic model for bioelectrical impedance vector analysis.
abstract: OBJECTIVE
  The boundaries between the categories of body composition provided by vectorial analysis of bioimpedance are not well defined. In this paper, fuzzy sets theory was used for modeling such uncertainty.
  
  
  METHODS
  An Italian database with 179 cases 18-70 years was divided randomly into developing (n = 20) and testing samples (n = 159). From the 159 registries of the testing sample, 99 contributed with unequivocal diagnosis. Resistance/height and reactance/height were the input variables in the model. Output variables were the seven categories of body composition of vectorial analysis. For each case the linguistic model estimated the membership degree of each impedance category. To compare such results to the previously established diagnoses Kappa statistics was used. This demanded singling out one among the output set of seven categories of membership degrees. This procedure (defuzzification rule) established that the category with the highest membership degree should be the most likely category for the case.
  
  
  RESULTS
  The fuzzy model showed a good fit to the development sample. Excellent agreement was achieved between the defuzzified impedance diagnoses and the clinical diagnoses in the testing sample (Kappa = 0.85, p < 0.001).
  
  
  CONCLUSIONS
  fuzzy linguistic model was found in good agreement with clinical diagnoses. If the whole model output is considered, information on to which extent each BIVA category is present does better advise clinical practice with an enlarged nosological framework and diverse therapeutic strategies.
authors.affiliation: Department of Epidemiology, School of Public Health, University of Sao Paulo, Av. Dr. Arnaldo, no 715, P.O.Box: 01246-904, Sao Paulo, Brazil. brunabronhara@usp.br
authors.forename: Bruna
authors.initials: B
authors.lastname: Bronhara
authors.forename: Antonio
authors.initials: A
authors.lastname: Piccoli
authors.forename: Júlio César R
authors.initials: JC
authors.lastname: Pereira
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001823:Body Composition; D017097:Electric Impedance; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009752:Nutritional Status; D055815:Young Adult