A smartphone with AI and a special lens helps medical workers diagnose malaria cheaply.
More than half the world’s population are at risk from malaria. Diagnostic procedures are time consuming, expensive and require special expertise and training. In many of the places where the risk of malaria is highest, these procedures are out of reach. Now, a group of researchers from TU Delft University have devised an innovation that could automate the analysis of blood samples. Called the Excelscope, this innovation could reduce the workload of staff and the cost of diagnosis.
The Excelscope uses a smartphone and ball-lens to magnify and identify malaria parasites in blood samples. Researchers then stain samples and place them on a movable platform, similar to a microscope. The platform enables medical workers to capture multiple fields of view within a blood sample in order to properly determine the number of malaria parasites present. The colour and shape of the parasites then becomes recognised by an algorithm that runs on the phone. The algorithm identifies any bacteria or parasites in the samples. Any relevant images are automatically saved to an SD card for further examination.
The Excelscope was International Runner Up in the 2018 James Dyson Awards. It joins other recent Dyson Award winners covered by Springwise, including a water bottle that uses friction to melt snow and a single axis wind turbine. Following their success, the makers will test the scope in the field in Africa. They will also be focused on streamlining the scope and optimising the algorithm for parasite detection and to work with Android platforms.