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International Runner Up

Excelscope 2.0

A semi-automated, smart Malaria diagnostic device using a ball-lens enhanced smartphone, which reduces workload in developing countries while increasing accuracy and decreasing cost of diagnoses.

What it does

The Excelscope reduces workload of medical staff in developing countries by automating the analysis of blood samples. It captures multiple field of views within a blood sample and uses an algorithm to determine the number of malaria parasites present.

Your inspiration

More than half of the world's population is at the risk of malaria. Current mistrust in diagnostic procedures (rapid diagnostic tests) leads to the preventive use of malaria medication; while manual microscopy (the gold standard) is very time consuming, expensive, requires special expertise and training. The World Health Organisation (WHO) recommends a nurse to patient ratio of 2,5:1000, while in Uganda it is 6:100000, thus being 4000% above the recommendation. The TU Delft Global Initiative, collaborating with African universities, has been conducting research on this topic for two years and provided us with the opportunity to contribute.

How it works

The Excelscope uses a smartphone and ball-lens to magnify and identify malaria parasites of 1μm in blood samples. The back cover of the phone was modified to raise the camera module and accommodate the ball-lens. Underneath lies the blood sample on top of a 3-axes moving system, fine-tuned to achieve micro stepping of 100μm. This enables us to take 800 field of views in 8mm², which fulfils the WHO’s recommendation for declaring a person malaria free. All electronic components (back-up battery, microcontrollers, phone, LEDs, SD-slot, buttons, etc.) come together in a custom printed circuit board, which controls them sequentially (e.g. triggering the phone's camera). By staining the blood sample (Giemsa - WHO recommended procedure) prior to examination, the parasites within blood cells turn purple which then can be identified by a colour and shape recognising algorithm that runs on the phone. All relevant pictures are automatically saved to a SD card.

Design process

Initially, we were given three prototypes: a visual prototype, a moving system prototype to evaluate the capability of various stepper motors and an optical prototype to evaluate numerous ball-lenses composed of different sizes and materials. We thoroughly analysed the prototypes and evaluated their feasibility, desirability and viability, before synthesising a program of requirements (PoR). Moreover, we opted to use a smartphone for its functionality and price value. The PoR was refined in an interactive and iterative process, which included consulting medical and optical experts, and finally was used to validate our solution. From the start we divided our team into sub-systems: housing & frame, moving system, electronics and optical system. Each sub-system underwent dozens of iterations, while validating integration with other sub-systems. Additionally, each sub-system went through ideation, conceptualisation, testing and validation before freezing and fine-tuning the final outcomes. Challenges within sub-systems evolved around aperture, light saturation/contrast, friction, micro stepping and power distribution (during power cuts). To test our ideas, we used rapid-prototyping techniques such as clay, cardboard, foam modelling, FDM, polyjet, SLA printing and laser cutting.

How it is different

The most unique aspect of our 3D printed design is the automation of the moving system in combination with the phone's camera and the algorithm. We are enabling the transition from manual microscopy to automated microscopy while increasing accuracy and reducing time and cost in the process. Other algorithms in existence require professional microscopes (approx. 3000€), whilst cheap microscopes (Foldscope - 1€) require enduring manual labour. We have combined the two and developed a solution that is more accessible, accurate, reliable and most importantly reduces the workload for medical professionals. In developing countries, these professionals are scarce and operate under immense pressure due to their workload, which leads to mistakes and inconsistencies. Moreover, our design is not dependant on the electricity grid and cellular services. Instead, our design includes a rechargeable back-up battery and a SD card slot for physical data collection and transfer.

Future plans

In the coming months, the Excelscope will be tested in the field in Africa, after which we will gain user feedback on potential improvements. On a more technical note, every part of the excelscope needs to be streamlined once more and/or evaluated on necessity to reduce manufacturing and assembly cost and time. More importantly, the algorithm for parasite detection and auto-focus will need to be optimised for Android platforms. Potential alternatives include utilising servers for machine-learning and image processing. However, whether this is feasible is questionable due to the lack of Wi-Fi and cellular connections in underdeveloped areas.


We have not won any awards but would like to acknowledge long-term contributors of this project, namely: Dr. Ir. J.C. Diehl (Design expert), Ir. T.E. Agbana (Optical expert), Dr. S. Patlan (Optical expert), Ing. F. van Pul (Medical Expert), Vinay Bhajantri (Design expert) and Karthik Mahadevan (Design expert)

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