Fluorescence measurement instrumentation with pattern recognition capability

荧光是一些材料和有机体吸收光线并以不同的、更温暖的颜色重新发射的特性。荧光的研究在农业、食品加工、环境研究、生化分析、物质鉴定和细菌检测等领域都有很大的应用价值。荧光测量可以非常准确，比使用其他光谱技术获得的灵敏度要好得多。尽管如此，还需要更多的创新研究来进一步改进，从而克服荧光方法的一些弱点。这些因素包括所需仪器的体积和成本，需要精确的校准程序，需要补偿环境变化，以及通常是手动或半自动的测量过程。此外，获取的数据的处理是一项复杂的任务，需要复杂的技术来从获得的光谱中提取有用的信息。这导致了特别获取技术的发展，这些技术是特定于给定问题的，不能推广。这在一定程度上是因为传感器开发人员使用的技术语言对于来自其他专业领域的最终用户来说往往是晦涩难懂的。我们实验室正在进行的研究旨在调查上述基本问题，并最终提出集成的单芯片系统解决方案，允许研究各种物质的物理和化学性质和/或识别这些物质在不同环境中的浓度。在本提案中，我们解决了大小和效率方面的问题，并增加了功能，例如在缺乏全面模型的情况下执行获取的荧光信号的自动、在线分析的能力。我们相信，我们的研究将导致通用单芯片系统设备的开发，这种设备可以很容易地适应各种应用，包括生物医学应用，同时提高非技术专家的易用性。

Fluorescence is the property of some materials and organisms to absorb light and reemit it at different, warmer colors. The study of fluorescence has useful applications in several areas, of which agriculture, food processing, environmental studies, biochemical analysis, substance identification, and bacteria detection. Fluorescence measurements can be very accurate, with much better sensitivities than those obtained with using other spectroscopic techniques. Still, more innovative research is needed to improve further, and thus overcome some weaknesses of fluorescence methods. These include the bulk and cost of the required instruments, the need for precise calibration procedures, the need to compensate for environmental changes and the usually manual or semi-automatic measurement process. Also, the processing of the acquired data is a complex task and requires sophisticated techniques to extract useful information from the obtained spectra. This has led to the development of ad hoc acquisition techniques that are specific to given problems and cannot be generalized. This is in part because the sensor developers speak a technical language that is often obscure to end users who come from other areas of expertise.    Ongoing research in our laboratory aims at investigating basic questions such as the above, and ultimately propose integrated, system-on-a-chip, solutions that allow the study of the physical and chemical properties of various substances and/or the identification of these substances with their concentration in various contexts. In the present proposal, we address concerns of size and efficiency, and adding functionality such as the ability to perform automatic, online analysis of the acquired fluorescence signals in the absence of comprehensive models. We believe that our research will lead to the development of generic system-on-a-chip devices that can be easily adapted to various applications, including biomedical ones, while enhancing their ease of use by non technical experts.