Noninvasive and simultaneous quantitative analysis of multiple human blood components based on the grey analysis...

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Mathematical Modeling

Background:

• Noninvasive detection of human blood components is a significant goal in clinical diagnostics.
• Current methods often require invasive procedures, limiting real-time monitoring and patient comfort.

Purpose of the Study:

• To develop a complete, high-precision, synchronous, and noninvasive detection system for multiple human blood components.
• To introduce and validate the novel "spectral elimination method" for enhanced accuracy in quantitative spectral analysis.

Main Methods:

• Utilized mathematical analysis, grey analysis system, and multivariate linear equation principles.
• Pioneered the "spectral elimination method" to reduce interference from non-target components in spectral analysis.
• Established fourteen models to analyze seven blood components (hemoglobin, red blood cell count, neutrophils, lymphocytes, monocytes, eosinophils, basophils).

Main Results:

• Models developed using the spectral elimination method achieved predicted correlation coefficients greater than 0.9500 for all seven blood components.
• Demonstrated high accuracy in predicting the content of multiple blood components simultaneously.
• The non-invasive detection system proved effective for quantitative analysis.

Conclusions:

• The spectral elimination method provides a highly accurate, simultaneous, and noninvasive approach for analyzing multiple human blood components.
• This advancement holds significant potential for clinical medical treatment and disease diagnosis.
• Represents a major progress in non-invasive quantitative spectral analysis of blood components.