Shinde Sujit R, Bhavsar Karan, Kimbahune Sanjay, Khandelwal Sundeep, Ghose Avik, Pal Arpan
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:6155-6158. doi: 10.1109/EMBC44109.2020.9176419.
Worldwide revenue of pharmaceutical market is more than 1200 billion USD [1] and that of counterfeit medicines is around 200 billion USD [2][3]. Counterfeit medicines can be detected by technical experts using visual inspection or through sophisticated lab and relevant methods. However, such methods require time, sample preparation and technical expertise with lab setup. These methods are not feasible and scalable to be used in the field by the general public. The objective of our research work was to detect counterfeit medicines using simpler and faster method using hyperspectral sensing. In this experiment, a visible - near infrared (350nm - 1050nm) hyperspectral device was used to capture spectral signature of the medicines. We used 24 medicine tablets of different companies. To imitate counterfeit medicines, tablet powders were adulterated by adding different levels of calcium carbonate. Spectral signatures were captured from original stage to all stages of adulterations and analyzed using machine learning (multilayer perceptron classifier). Result shows that we are able to achieve more than 90% classification accuracy. Portable hyperspectral sensing combined with medicines spectral database can be a good field level test method for detection of counterfeit medicines, as it is very fast, easy to use and does not require technical expertise.
全球药品市场收入超过12000亿美元[1]，而假药市场收入约为2000亿美元[2][3]。技术专家可以通过目视检查或借助精密实验室及相关方法来检测假药。然而，这些方法需要时间、样品制备以及实验室设置方面的技术专长。这些方法对于普通大众在现场使用而言既不可行也无法扩展应用。我们研究工作的目标是使用更简单、快速的高光谱传感方法来检测假药。在本实验中，使用了一台可见 - 近红外（350纳米 - 1050纳米）高光谱设备来获取药品的光谱特征。我们使用了来自不同公司的24片药。为了模拟假药，通过添加不同含量的碳酸钙来掺假药片粉末。从掺假的原始阶段到所有阶段都采集光谱特征，并使用机器学习（多层感知器分类器）进行分析。结果表明我们能够实现超过90%的分类准确率。便携式高光谱传感与药品光谱数据库相结合，可以成为一种很好的现场检测假药的测试方法，因为它非常快速、易于使用且不需要技术专长。
