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

Jan Carel Diehl, Prosper Oyibo, Temitope Agbana, Satyajith Jujjavarapu, G. Young Van, Gleb Vdovin, Wellington Oyibo

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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.

Original languageEnglish
Title of host publication2020 IEEE Global Humanitarian Technology Conference, GHTC 2020
PublisherIEEE
ISBN (Electronic)9781728173887
DOIs
Publication statusPublished - 29 Oct 2020
Event10th Annual IEEE Global Humanitarian Technology Conference, GHTC 2020 - Virtual, Seattle, United States
Duration: 29 Oct 20201 Nov 2020

Publication series

Name2020 IEEE Global Humanitarian Technology Conference, GHTC 2020

Conference

Conference10th Annual IEEE Global Humanitarian Technology Conference, GHTC 2020
Country/TerritoryUnited States
CityVirtual, Seattle
Period29/10/201/11/20

Keywords

  • algorithms
  • artificial intelligence
  • diagnostics
  • global health
  • local production
  • Neglected tropical disease
  • Nigeria
  • schistosomiasis
  • technical optics

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