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Unifying Wearable Data: A Novel Architecture Integrating Fitbit Wristbands and Smartphones for Enhanced Data Availability and Linguistic Summaries

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Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023) (UCAmI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 841))

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Abstract

The management of wearable device data faces significant challenges due to the limited availability of suitable Application Programming Interfaces (APIs). In response to this issue, we present a pioneering architecture that seamlessly integrates data from commercially available Fitbit wristbands’ sensors and smartphones, resulting in improved data accessibility and advanced linguistic summaries. Our novel approach utilises cutting-edge sensors to efficiently capture and transmit user movement and heart rate data wirelessly to smartphones. A key element of our architecture involves facilitating communication with a central platform via a robust REST API. This enables us to incorporate fuzzy linguistic protoforms, empowering sophisticated data analysis techniques to be employed. Furthermore, we have developed specific applications tailored for both mobile devices and smartwatches, enabling seamless data collection and visualizations. To demonstrate the efficacy and versatility of our proposed architecture, we conducted a comprehensive case study encompassing multiple scenarios. The results of this study affirm the substantial benefits of our approach, showcasing its potential to revolutionise wearable data management and analysis. By providing a scalable and adaptive solution to the current limitations in wearable data management, our work lays the groundwork for further advancements in this field, promising to foster new research and applications in diverse domains.

This work has been partially supported by grant PID2021-127275OB-I00, funded by MCIN/AEI/10.13039/501100011033, and by the ‘ERDF - A way of making Europe’.

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Notes

  1. 1.

    https://fastapi.tiangolo.com/.

  2. 2.

    https://swagger.io/.

  3. 3.

    https://docs.pydantic.dev/latest/.

References

  1. Albín-Rodríguez, A.P., De-La-Fuente-Robles, Y.M., López-Ruiz, J.L., Verdejo-Espinosa, Á., Espinilla Estévez, M.: UJAmI Location: a fuzzy indoor location system for the elderly. Int. J. Environ. Res. Public Health 18(16), 8326 (2021)

    Article  Google Scholar 

  2. Albín-Rodríguez, A.P., Ricoy-Cano, A.J., de-la Fuente-Robles, Y.M., Espinilla-Estévez, M.: Fuzzy protoform for hyperactive behaviour detection based on commercial devices. Int. J. Environ. Res. Public Health 17(18), 6752 (2020)

    Google Scholar 

  3. Bradshaw, S., Brazil, E., Chodorow, K.: MongoDB: the definitive guide: powerful and scalable data storage. O’Reilly Media (2019)

    Google Scholar 

  4. Díaz, D., Medina, J., Montoro, A., López, J.L., Espinilla, M.: Linguistic summaries for dwellings energy poverty monitoring. In: International Conference on Ubiquitous Computing and Ambient Intelligence, pp. 693–704. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-21333-5_69

  5. Espinilla, M., Medina, J., García-Fernández, Á.L., Campaña, S., Londoño, J.: Fuzzy intelligent system for patients with preeclampsia in wearable devices. Mob. Inf. Syst. 2017, 1–10 (2017). https://doi.org/10.1155/2017/7838464

    Article  Google Scholar 

  6. Lou, Z., Wang, L., Jiang, K., Wei, Z., Shen, G.: Reviews of wearable healthcare systems: materials, devices and system integration. Mater. Sci. Eng. R. Rep. 140, 100523 (2020)

    Article  Google Scholar 

  7. Lu, L., et al.: Wearable health devices in health care: narrative systematic review. JMIR Mhealth Uhealth 8(11), e18907 (2020)

    Article  Google Scholar 

  8. Marín, N., Sánchez, D.: On generating linguistic descriptions of time series. Fuzzy Sets Syst. 285, 6–30 (2016). https://doi.org/10.1016/j.fss.2015.04.014, https://www.sciencedirect.com/science/article/pii/S0165011415002110, special Issue on Linguistic Description of Time Series

  9. Martinez-Cruz, C., Rueda, A.J., Popescu, M., Keller, J.M.: New linguistic description approach for time series and its application to bed restlessness monitoring for eldercare. IEEE Trans. Fuzzy Syst. 30(4), 1048–1059 (2022). https://doi.org/10.1109/tfuzz.2021.3052107

    Article  Google Scholar 

  10. Masse, M.: REST API design rulebook: designing consistent RESTful web service interfaces. O’Reilly Media, Inc. (2011)

    Google Scholar 

  11. Miotto, R., Wang, F., Wang, S., Jiang, X., Dudley, J.T.: Deep learning for healthcare: review, opportunities and challenges. Brief. Bioinform. 19(6), 1236–1246 (2018)

    Article  Google Scholar 

  12. Nahmias, S.: Fuzzy variables. Fuzzy Sets Syst. 1(2), 97–110 (1978). https://doi.org/10.1016/0165-0114(78)90011-8

    Article  MathSciNet  MATH  Google Scholar 

  13. Oresko, J.J., et al.: A wearable smartphone-based platform for real-time cardiovascular disease detection via electrocardiogram processing. IEEE Trans. Inf Technol. Biomed. 14(3), 734–740 (2010)

    Article  Google Scholar 

  14. Parkka, J., Ermes, M., Korpipaa, P., Mantyjarvi, J., Peltola, J., Korhonen, I.: Activity classification using realistic data from wearable sensors. IEEE Trans. Inf Technol. Biomed. 10(1), 119–128 (2006)

    Article  Google Scholar 

  15. Patel, S., et al.: Monitoring motor fluctuations in patients with Parkinson’s disease using wearable sensors. IEEE Trans. Inf Technol. Biomed. 13(6), 864–873 (2009)

    Article  Google Scholar 

  16. Peláez-Aguilera, M.D., Espinilla, M., Olmo, M.R.F., Medina, J.: Fuzzy linguistic protoforms to summarize heart rate streams of patients with ischemic heart disease. Complexity 2019, 1–11 (2019). https://doi.org/10.1155/2019/2694126

    Article  Google Scholar 

  17. Ravì, D., et al.: Deep learning for health informatics. IEEE J. Biomed. Health Inform. 21(1), 4–21 (2016)

    Article  Google Scholar 

  18. Son, D., et al.: Multifunctional wearable devices for diagnosis and therapy of movement disorders. Nat. Nanotechnol. 9(5), 397–404 (2014)

    Article  Google Scholar 

  19. Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning-III. Inf. Sci. 9(1), 43–80 (1975). https://doi.org/10.1016/0020-0255(75)90017-1

    Article  MathSciNet  MATH  Google Scholar 

  20. Zadeh, L.: Fuzzy logic. Computer 21(4), 83–93 (1988). https://doi.org/10.1109/2.53

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science, University of Jaén, Jaén, Spain

    David Díaz-Jiménez & Macarena Espinilla-Estévez

  2. Department of Computer Engineering, Automation and Robotics, University of Granada, Granada, Spain

    Javier Medina-Quero

Authors
  1. David Díaz-Jiménez
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  2. Javier Medina-Quero
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  3. Macarena Espinilla-Estévez
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Corresponding author

Correspondence to David Díaz-Jiménez .

Editor information

Editors and Affiliations

  1. Ciudad Real, Spain

    José Bravo

  2. Mérida, Yucatán, Mexico

    Gabriel Urzáiz

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Díaz-Jiménez, D., Medina-Quero, J., Espinilla-Estévez, M. (2023). Unifying Wearable Data: A Novel Architecture Integrating Fitbit Wristbands and Smartphones for Enhanced Data Availability and Linguistic Summaries. In: Bravo, J., Urzáiz, G. (eds) Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023). UCAmI 2023. Lecture Notes in Networks and Systems, vol 841. Springer, Cham. https://doi.org/10.1007/978-3-031-48590-9_13

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