IF-Cloud: FHIR API for integrating digital healthcare projects

Authors

  • Juliano Machado Vieira IFSul
  • Jeremias Piontkoski de Abreu IFSul
  • Juliano Costa Machado IFSul
  • Fábio Pires Itturriet UTFPR
  • André Luís Del Mestre Martins IFSul

DOI:

https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1340

Keywords:

Cloud Computing, Health Information Interoperability, Digital Health

Abstract

Objective: Develop IF-Cloud, an API for prototyping and integrating IoT devices and web applications for healthcare. Method: The case study is a healthcare ecosystem for biosignal monitoring that only performs Create/Read/Update/Delete (CRUD) operations. IF-Cloud receives new operations by uploading python scripts into a graphical user interface. IF-Cloud uses data of FHIR resources coming from some CRUD API and returns another FHIR resource with the data processed by the scripts. Results: a biosignal was registered in the CRUD API for the experiments. Data compression and heart rate calculation are operations included in the ecosystem using IF-Cloud. An application for visualizing biosignals benefits from the addition by displaying heart rate and biosignal simultaneously. Conclusion: IF-Cloud allows the inclusion of new functionalities in healthcare ecosystems by uploading script files.

Author Biographies

Juliano Machado Vieira, IFSul

IFSul campus Charqueadas (RS), Brasil

Jeremias Piontkoski de Abreu, IFSul

IFSul campus Charqueadas (RS), Brasil.

Juliano Costa Machado, IFSul

IFSul campus Charqueadas (RS), Brasil.

Fábio Pires Itturriet, UTFPR

Departamento Acadêmico de Eletrotécnica, UTFPR, Curitiba (PR), Brasil

André Luís Del Mestre Martins, IFSul

IFSul campus Charqueadas (RS), Brasil.

References

Szabó Z, Bilicki V. Access control of EHR records in a heterogeneous cloud infrastructure. Acta Cybernetica. 2021 Dec 7;25(2):485-516. DOI: https://doi.org/10.14232/actacyb.290283

Al-Fuqaha A, Guizani M, Mohammadi M, Aledhari M, Ayyash M. Internet of things: A survey on enabling technologies, protocols, and applications. IEEE communications surveys & tutorials. 2015 Jun 15;17(4):2347-76. DOI: https://doi.org/10.1109/COMST.2015.2444095

Farahani B, Firouzi F, Chang V, Badaroglu M, Constant N, Mankodiya K. Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare. Future generation computer systems. 2018 Jan 1;78:659-76. DOI: https://doi.org/10.1016/j.future.2017.04.036

Benson T, Grieve G. Principles of health interoperability. Cham: Springer International. 2021:21-40. DOI: https://doi.org/10.1007/978-3-030-56883-2_2

FHIR Release 5 [Internet]. HL7.org. 2024. [Acessado em 15/04/2024]. Disponível em: https://www.hl7.org/fhir/

dos Santos LS, del Mestre Martins G, Itturriet FP, Machado JC, del Mestre Martins AL. Interoperabilidade e Segurança na Implementação de Aplicações Web de Saúde com SMART on FHIR. Journal of Health Informatics. 2023 Jul 20;15(Especial). DOI: https://doi.org/10.59681/2175-4411.v15.iEspecial.2023.1096

Abdelaziz AB, Rahimi MA, Alrabeiah MR, Ibrahim AB, Almaiman AS, Ragheb AM, Alshebeili SA. Photoplethysmography Data Reduction Using Truncated Singular Value Decomposition and Internet of Things Computing. Electronics. 2023 Jan 2;12(1):220. DOI: https://doi.org/10.3390/electronics12010220

Serhani MA, T. El Kassabi H, Ismail H, Nujum Navaz A. ECG monitoring systems: Review, architecture, processes, and key challenges. Sensors. 2020 Mar 24;20(6):1796. DOI: https://doi.org/10.3390/s20061796

Tejedor J, García CA, Márquez DG, Raya R, Otero A. Multiple physiological signals fusion techniques for improving heartbeat detection: A review. Sensors. 2019 Oct 29;19(21):4708. DOI: https://doi.org/10.3390/s19214708

Ayaz M, Pasha MF, Alzahrani MY, Budiarto R, Stiawan D. Correction: The Fast Health Interoperability Resources (FHIR) standard: systematic literature review of implementations, applications, challenges and opportunities. JMIR Med Inform. 2021 Aug 17;9(8):e32869. DOI: https://doi.org/10.2196/32869

AWS Free Tier [Internet]. Amazon Web Services. 2024. [Acessado em 15/04/2024]. Disponível em: https://aws.amazon.com/free/

Knuth DE. Dynamic huffman coding. Journal of algorithms. 1985 Jun 1;6(2):163-80. DOI: https://doi.org/10.1016/0196-6774(85)90036-7

Morás PL, del Mestre Martins AL, Itturriet FP. CardIoT - Eletrocardiógrafo Interoperável Baseado em Internet das Coisas. Anais do Computer on the Beach. 2023 May 3;14:416-23. DOI: https://doi.org/10.14210/cotb.v14.p416-423

Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng CK, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. circulation. 2000 Jun 13;101(23):e215-20. DOI: https://doi.org/10.1161/01.CIR.101.23.e215

HAPI FHIR - The Open Source FHIR API for Java. [Internet]. Smile CDR. 2024. [Acessado em 15/04/2024]. Disponível em: https://hapifhir.io/

Bota P, Silva R, Carreiras C, Fred A, da Silva HP. BioSPPy: A Python toolbox for physiological signal processing. SoftwareX. 2024 May 1;26:101712. DOI: https://doi.org/10.1016/j.softx.2024.101712

Moody GB. Lightwave: Waveform and annotation viewing and editing in a web browser. In Computing in Cardiology 2013 2013 Sep 22 (pp. 17-20). IEEE.

Published

2024-11-19

How to Cite

Vieira, J. M., de Abreu, J. P., Machado, J. C., Itturriet, F. P., & Martins, A. L. D. M. (2024). IF-Cloud: FHIR API for integrating digital healthcare projects. Journal of Health Informatics, 16(Especial). https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1340

Similar Articles

<< < 15 16 17 18 19 20 21 22 23 24 > >> 

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)