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A Neuromodulation Decision Support System: A User-Centered Development Study

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XXVII Brazilian Congress on Biomedical Engineering (CBEB 2020)

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Abstract

The choice of the brain area to be stimulated by non-invasive brain stimulations (NIBS) often poses a challenge to physiotherapists. To address this issue, a mockup design of a Decision Support System (DSS) application called SMDQ App was created following the Design Thinking (DT) methodology. As a part of this method, SMDQ App 1.0 was tested, and based on this testing a second version was elaborated (SMDQ App 2.0). Again, tests were made to the second prototype version, and feedback was collected. The application of two rounds of tests is common when using DT and enables a better understanding of users’ needs, thus improving the acceptance of the tool. SMDQ App 1.0 had Ok usability according to the System Usability Scale. With the improvements, SMDQ App 2.0 was classified with Good usability.

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Notes

  1. 1.

    SMDQ App 1.0: https://bit.ly/2Tzwt2Z.

    2SMDQ App 2.0: https://bit.ly/3gfdm7U.

References

  1. Breining BL, Sebastian R (2020) Neuromodulation in post-stroke aphasia treatment. Curr Phys Med Rehabil Rep 8:44–56. https://doi.org/10.1007/s40141-020-00257-5

    Article  Google Scholar 

  2. Wang X (2019) Advances in the application of non-invasive brain stimulation in the treatment of depression. Adv Psychol 09:293–300. https://doi.org/10.12677/ap.2019.92038

    Article  Google Scholar 

  3. Brighina F, Curatolo M, Cosentino G, Tommaso M, Battaglia G, Sarzi-Puttini PC, Guggino G, Fierro B (2019) Brain modulation by electric currents in fibromyalgia: a structured review on non-invasive approach with transcranial electrical stimulation. Front Hum Neurosci 13:40. https://doi.org/10.3389/fnhum.2019.00040

    Article  Google Scholar 

  4. Power JD et al (2013) Evidence for hubs in human functional brain networks. Neuron 79(4):798–813. https://doi.org/10.1016/j.neuron.2013.07.035

    Article  Google Scholar 

  5. Van Den Heuvel MP, Sporns O (2013) Network hubs in the human brain. Trends Cogn Sci 17(12):683–696. https://doi.org/10.1016/j.tics.2013.09.012

    Article  Google Scholar 

  6. Anderson JA, Willson P (2008) Clinical decision support systems in nursing: synthesis of the science for evidence-based practice. Cin-Comput Inform Nu 26(3):151–158

    Article  Google Scholar 

  7. Berrouiguet S, Barrigón ML, Brandt SA, Ovejero-García S et al (2016) Development of a web-based clinical decision support system for drug prescription: non-interventional naturalistic description of the antipsychotic prescription patterns in 4345 outpatients and future applications. PloS One 11(10). https://doi.org/10.1371/journal.pone.0163796

  8. Umer A, Mattila J, Liedes H, Koikkalainen J et al (2019) A decision support system for diagnostics and treatment planning in traumatic brain injury. IEEE J Biomed Health 23(3):1261–1268

    Article  Google Scholar 

  9. Mirsky R, Hibah S, Hadad M, Gorenstein A, Kalech M (2020) “PhysIt”—a diagnosis and troubleshooting tool for physiotherapists in training. Diagnostics (Basel) 10(2):72

    Article  Google Scholar 

  10. Gorbunov I, Zaitsev A, Roman Meshcheryakov, Hodashinsky I (2017) A decision support system for prescription of non-medication-based rehabilitation. Bull South Ural State Univ 10(3):41–51. https://doi.org/10.1007/s10527-017-9663-1

    Article  Google Scholar 

  11. Oliveira DM (2019) Desenvolvimento e validação de um instrumento para avaliação de disfunção sensório-motora para o tratamento com estimulação cerebral não-invasiva na prática do fisioterapeuta. Doctoral Thesis in Neuropsychiatry and Behavioral Sciences, Universidade Federal de Pernambuco, Recife, PE

    Google Scholar 

  12. Diogo R, Kolbe A, Santos N (2019) A transformação digital e a gestão do conhecimento: contribuições para a melhoria dos processos produtivos e organizacionais. p 2p e inovação 5(2):154–175

    Google Scholar 

  13. De Couvreur L, Goossens R (2011) Design for (every)one: co-creation as a bridge between universal design and rehabilitation engineering. CoDesign 7(2):107–121. https://doi.org/10.1080/15710882.2011.609890

    Article  Google Scholar 

  14. Pereira JC, Russo RFSM (2018) Design thinking integrated in agile software development: a systematic literature review. Procedia Comput Sci 138:775–782

    Article  Google Scholar 

  15. Carroll N, Richardson I (2016) Aligning healthcare innovation and software requirements through design thinking. In: IEEE/ACM international workshop on software engineering in healthcare systems (SEHS), Austin, Texas, pp 1–7

    Google Scholar 

  16. Aguiar B et al (2011) Uso da Escala Likert na Análise de Jogos. In: Proceedings of SBGames, Salvador, Bahia

    Google Scholar 

  17. Martins AI et al (2015) European Portuguese validation of the system usability scale (SUS). Procedia Comput Sci 67:293–300

    Article  Google Scholar 

  18. SUMI at sumi.exp.ie

    Google Scholar 

  19. Kaya A, Ozturk R, Gumussoy AC (2019) Usability measurement of mobile applications with system usability scale (SUS). In: Industrial engineering in the big data era, global joint conference on industrial engineering and its application areas, Nevsehir, Turkey, pp 389–400

    Google Scholar 

  20. Bangor A, Kortum PT, Miller JT (2008) An empirical evaluation of the system usability scale. Int J Hum-Comput Int 24(6):574–594. https://doi.org/10.1080/10447310802205776

    Article  Google Scholar 

  21. Scarparo AF et al (2012) Reflexões sobre o uso da técnica Delphi em pesquisas na enfermagem. Revista da Rede de Enfermagem do Nordeste 13(1)

    Google Scholar 

  22. Cavalcanti VC et al (2018) Usability assessments for augmented reality motor rehabilitation solutions: a systematic review. Int J Comput Games Technol 23:1–18. https://doi.org/10.1155/2018/5387896

    Article  Google Scholar 

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Correspondence to A. E. F. Da Gama .

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Maranhão, G.B.A., De Santana, T.M., De Oliveira, D.M., Da Gama, A.E.F. (2022). A Neuromodulation Decision Support System: A User-Centered Development Study. In: Bastos-Filho, T.F., de Oliveira Caldeira, E.M., Frizera-Neto, A. (eds) XXVII Brazilian Congress on Biomedical Engineering. CBEB 2020. IFMBE Proceedings, vol 83. Springer, Cham. https://doi.org/10.1007/978-3-030-70601-2_70

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  • DOI: https://doi.org/10.1007/978-3-030-70601-2_70

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