Intelligent system for detecting errors and determining failure modes in noninvasive measurement of blood and tissue analytes

Abstract

An intelligent system for detecting errors and determining failure modes operates on an absorbance spectrum of in vivo skin tissue. Application of the system results in improved prediction accuracy through rejection of invalid and poor samples. System components include a noninvasive blood glucose meter, such as a near IR spectrometer, an error detection system (EDS); a system for diagnosing and mitigating errors; and a reporting method. In the EDS, a pattern classification engine and hierarchy of levels analyzes, detects and diagnoses instrument, interface and sample errors manifested in the spectrum to determine suitability of an absorbance spectrum for blood glucose measurement. The final component of the system evaluates the error condition, diagnoses the specific mode of failure (if necessary) and reports actions to be taken. Sub-components and levels of the EDS can operate independently of the other system elements to the benefit of a noninvasive glucose measurement system.

Dependencies are inferred from the claim text.