Biochemistry Analyzer and Typical Architecture
Biochemical analyzers use many electrochemical and optical techniques to analyze blood, urine, cerebral spinal fluid, and other biological samples. The most widely used techniques are optically based measurements, and examples include colorimetric, absorption, spectrometric, and fluoroscopic detection methods. These processes can measure chemicals such as antigens, molecules, and proteins in body fluids. These techniques are widely used at all levels of hospitals, clinics, epidemic prevention stations, and family planning service providers because of their fast measurement ability, high sensitivity, and accuracy when detecting even small doses of chemicals.
Biochemical analyzers are complex systems that are composed of an optical engine consisting of light sources, detectors and other optical elements, sample movement/fluidics, automation control and processing, power management, and environmental monitoring and control (temperature, pressure, humidity). For greater efficiency, biochemical analyzers have become highly automated. This technology automates sample loading, tube cleaning, mechanical control, and data processing. The operator just needs to insert the sample for analysis, choose the program, and start the instrument.
Laboratory biochemical analyzers could be classified by processing capacity into large (600+ samples per hours), middle (300-600 samples per hours), and small (below 300 samples per hour) sizes. They can also me characterized by laboratory based or point of care testers (POCT), which are deployed near patients for faster test turnaround time.
Biochemistry Analyzer Design Considerations and Major Challenges
• System integration is complex because a biochemical analyzer is composed of different technologies
like a spectrophotometer, electrochemistry modules (ISE, ph), fluidic and sample handling features,
automatic control, and data processing systems.
• Temperature control is very important for reagent and chemical reaction.
• Automation control is necessary to improve executive efficiency.
• Data processing and classification.
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