title: Data processing for noninvasive continuous glucose monitoring with a multisensor device.
abstract: BACKGROUND
  Impedance spectroscopy has been shown to be a candidate for noninvasive continuous glucose monitoring in humans. However, in addition to glucose, other factors also have effects on impedance characteristics of the skin and underlying tissue.
  
  
  METHODS
  Impedance spectra were summarized through a principal component analysis and relevant variables were identified with Akaike's information criterion. In order to model blood glucose, a linear least-squares model was used. A Monte Carlo simulation was applied to examine the effects of personalizing models.
  
  
  RESULTS
  The principal component analysis was able to identify two major effects in the impedance spectra: a blood glucose-related process and an equilibration process related to moisturization of the skin and underlying tissue. With a global linear least-squares model, a coefficient of determination (R²) of 0.60 was achieved, whereas the personalized model reached an R² of 0.71. The Monte Carlo simulation proved a significant advantage of personalized models over global models.
  
  
  CONCLUSIONS
  A principal component analysis is useful for extracting glucose-related effects in the impedance spectra of human skin. A linear global model based on Solianis Multisensor data yields a good predictive power for blood glucose estimation. However, a personalized linear model still has greater predictive power.
authors: Research & Development Department, Solianis Monitoring AG, Zürich, Switzerland. andreas.caduff@solianis.com
authors: Martin
authors: M
authors: Mueller
authors: Mark S
authors: MS
authors: Talary
authors: Lisa
authors: L
authors: Falco
authors: Oscar
authors: O
authors: De Feo
authors: Werner A
authors: WA
authors: Stahel
authors: Andreas
authors: A
authors: Caduff
mesh_terms: D000328:Adult; D001786:Blood Glucose / Q000032:analysis; D015190:Blood Glucose Self-Monitoring / Q000379:methods*; D058266:Dielectric Spectroscopy / Q000379:methods; D017097:Electric Impedance; D004867:Equipment Design; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D016014:Linear Models; D008297:Male; D008422:Materials Testing; D008875:Middle Aged; D009010:Monte Carlo Method; D010477:Perfusion; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D012867:Skin / Q000378:metabolism; D013997:Time Factors
chemical_list: D001786:Blood Glucose