Schistoscope

Smartphone versus Raspberry Pi based low-cost diagnostic device for urinary Schistosomiasis

Conference Paper (2020)
Author(s)

Jan Carel Diehl (TU Delft - Design for Sustainability)

Prosper Oyibo (TU Delft - Team Raf Van de Plas)

Temitope E. Agbana (TU Delft - Team Michel Verhaegen)

Satyajith Jujjavarapu (TU Delft - Design for Sustainability)

G.Y. Van (TU Delft - Design for Sustainability)

Gleb Vdovin (TU Delft - Team Mulders)

Wellington Oyibo (University of Lagos)

Research Group
Design for Sustainability
DOI related publication
https://doi.org/10.1109/GHTC46280.2020.9342871
More Info
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Publication Year
2020
Language
English
Research Group
Design for Sustainability
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
ISBN (electronic)
9781728173887
Reuse Rights

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Abstract

Schistosomiasis is a neglected tropical disease of Public Health importance affecting over 252 million people worldwide with Nigeria having a very high number of cases. It is caused by blood flukes of the genus Schistosoma and transmitted by freshwater snails. To achieve the current global elimination objectives, low-cost and easy-to-use diagnostic tools are critically needed. Recent innovations in optical and computer technologies have made handheld digital and smartphone-based microscopes a viable diagnostic approach. Development, validation and deployment of these diagnostic devices for field use, however, require the optimisation of its optical train for the registration of high-resolution images and the realisation of a robust system design that can be locally produced in low-income countries. Field research conducted in Nigeria with active involvement of key stakeholders in research and development (RD) led to the design of an initial prototype device for the diagnosis of urinary schistosomiasis, called Schistoscope 1.0. In this paper, we present further development of the Schistoscope 1.0 along two parallel design trajectories: A Raspberry Pi and a Smartphone-based Schistoscope. Specifically, we focused on the optimization of the optics, embodiment design and the electronics systems of the devices so as to produce a robust design with potential for local production.

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