1. A smartphone-based optical platform for colorimetric analysis of microfluidic device
- Author
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Uddin M. Jalal, Joon S. Shim, Sang C. Kim, Sung B. Im, and Sungho Ko
- Subjects
Computer science ,Microfluidics ,Nanotechnology ,02 engineering and technology ,Hematocrit ,01 natural sciences ,Materials Chemistry ,medicine ,Hematocrit levels ,Electrical and Electronic Engineering ,Instrumentation ,Detection limit ,Microchannel ,medicine.diagnostic_test ,010401 analytical chemistry ,Metals and Alloys ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,0104 chemical sciences ,Surfaces, Coatings and Films ,Electronic, Optical and Magnetic Materials ,Hematocrit determination ,0210 nano-technology ,Colorimetric analysis ,Sensitivity (electronics) ,Biomedical engineering - Abstract
In this work, a smartphone based optical platform for colorimetric analysis of blood hematocrit using a disposable microfluidic device is designed, implemented and fully characterized. Using an integrated camera in the smartphone, pictures of human blood in the microchannel were taken and analyzed by a mobile application. To avoid the image burning and ambient light effect, a unique light-diffusing model inside a white acrylic-imaging box was included in this platform. With the image-processing program on the smartphone, the developed device was successfully applied to determine various hematocrit levels of human blood from 10% to 65%. Furthermore, the characterization of the depth of the microfluidic channel demonstrated that a shallower depth of the microchannel enhanced the sensitivity of the hematocrit determination. The limit of detection (LOD) obtained from the developed platform was 0.1% of hematocrit with a sensitivity of 0.53 GSV (a.u.)/hematocrit%. Thus, utilizing the advantage of the microfluidic effect, a rapid and sensitive hematocrit determination was achieved successfully. With this, the hematocrit of human blood could be conveniently and accurately determined using the disposable microfluidic device, and then processed by the smartphone camera and mobile image analysis application.
- Published
- 2017
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