Compact design of a planar compliant XY precision positioning stage

For automated malaria diagnosis using a microscope

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Abstract

Malaria remains a major burden on global health, with roughly 200 million reported cases worldwide and more than 400,000 deaths per year. According to the World Health Organization, ninety-three percent of all deaths due to the disease occurred in developing countries in sub-Saharan Africa. This large percentage is directly correlated to the lack of diagnostic tools in those developing countries. Early and accurate diagnosis of malaria is a critical aspect of efforts to control the disease. Microscopic examination of a blood smear remains the clinical gold standard for malaria diagnosis. However, this examination is subjective and requires a highly experienced and skilled microscopist. Next to that, it is a labor-intensive procedure that is very time-consuming. Automated hematology analyzers that are currently available are of high cost and therefore only suitable for laboratories and not for a local doctor’s practice. The objective of this research was to provide the design of a compact and affordable compliant XY positioning stage that can be integrated into a microscope to be used for automated malaria diagnosis in developing countries without the involvement of a laboratory. The challenge imposed with this objective is that compliant stages can only reach small strokes due to the inherent imperfection of flexures. Achieving long-stroke results in high stresses and cross-axis coupling between the two motion axes which is undesired. This challenge is solved by implementing a constraint-based method that results in a design with parallel kinematics and modular structure that exhibits high geometric decoupling. A demonstrator of the precision stage is 3D-printed out of PLA and used for performance evaluation measurements. The demonstrator managed to achieve the set requirements for blood smear analysis. Therefore, it can be concluded that the stage was designed successfully and it can be implemented for automated malaria diagnosis to help Africa control the disease.