Meters & Monitors
Blood Glucose Meters Current Continuous Monitors Comparison of Available Monitors
Various Future Monitors Improving Today's Meters Other Monitors Older Monitors
Future Monitoring
AiMedics A.Menarini Diagnostics Cybiocare OHD InLight Solutions Kumetrix LighTouch Medical NAS - iSense NIR Diagnostics Optiscan Orsense Pindi Products Sensors For Medicine and Science Sensys Medical Sentek Solianis Sontra SpectRx Synthetic Blood International Therasense Visual Pathways
InLight Solutions - Near Infrared Technology 
InLight Solutions researches and develops sensor-based measurement systems for life science applications. They have ties with researchers at the University of New Mexico, and has been working on a Near-IR device for several years. InLight's optics and software design is specific to distinguish the target molecule glucose, from similar molecules like water.
Their devices consist of three parts: a light source, an optical detector, and a spectrometer. The light shines into the skin and a small amount of that light reflects back. The reflected light is analyzed by the spectrometer with subsequent measurement by the detector. Measuring the differences between the light that went into the skin with the light that the detector collects. Each molecule's response to the light can be distinguished by different vibration characteristics, thus the system can be programmed to analyze a particular molecule. This system is optimized to give an accurate quantitative measurement of glucose concentrations in the body.
VeraLight, Inc. was established in 2004 as a spinout of Inlight Solutions to focus on a comprehensive approach to noninvasive diabetes screening. They are developing the Scout DS instrument for screening of type 2 and pre-diabetes. Scout DS employs fluorescence spectroscopy to noninvasively measure advanced glycation endproducts (AGEs) in the skin of a subject’s forearm. Skin AGEs are a well-known biomarker of diabetes, an excellent indicator of cumulative hyperglycemic exposure, and have been shown to predict the development of type 2 diabetes.
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