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Fuzzy Linguistic Protoforms to Summarize Heart Rate Streams of Patients with Ischemic Heart Disease

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  • María Dolores Peláez-Aguilera
  • Macarena Espinilla
  • María Rosa Fernández Olmo
  • Javier Medina

Abstract

Cardiac rehabilitation is a key program which significantly decreases mortality rates in high-risk patients with ischemic heart disease. Due to the huge lack of accessibility to such programs at Health Centers, outdoor-based programs for cardiac rehabilitation have been proposed as an excellent tool to improve accessibility for patients at Health Centers. These outdoor-based programs make use of wrist-worn devices for real-time monitoring of rehabilitation sessions based on clinical guidelines. In this way, a greater number of patients can fortunately gain access to the rehabilitation program. However, this advantage also means that the cardiac rehabilitation team has to monitor a greater number of sessions due to the increase of the number of benefited patients, so the team members spend a lot of time analyzing each patient’s sessions. In this paper, we present a methodology to evaluate heart rate streams of patients with ischemic heart disease using a linguistic approach. This innovative methodology manages relevant linguistic descriptions (protoforms) for the cardiac rehabilitation team to identify sessions with interest indicators by means of linguistic summaries. Therefore, the analysis process is automated in a comprehensible way, offering short linguistic descriptions to the cardiac rehabilitation team, who promptly provide feedback to their patients. In order to show the great efficiency and effectiveness of the proposed methodology, we have used and applied this methodology to real data provided by patients of an outdoor cardiac rehabilitation program run by the Health Council of the Andalusian Health Service (Spain).

Suggested Citation

  • María Dolores Peláez-Aguilera & Macarena Espinilla & María Rosa Fernández Olmo & Javier Medina, 2019. "Fuzzy Linguistic Protoforms to Summarize Heart Rate Streams of Patients with Ischemic Heart Disease," Complexity, Hindawi, vol. 2019, pages 1-11, January.
  • Handle: RePEc:hin:complx:2694126
    DOI: 10.1155/2019/2694126
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    References listed on IDEAS

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    Cited by:

    1. Antonio-Pedro Albín-Rodríguez & Adrián-Jesús Ricoy-Cano & Yolanda-María de-la-Fuente-Robles & Macarena Espinilla-Estévez, 2020. "Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices," IJERPH, MDPI, vol. 17(18), pages 1-24, September.
    2. Antonio-Pedro Albín-Rodríguez & Yolanda-María De-La-Fuente-Robles & José-Luis López-Ruiz & Ángeles Verdejo-Espinosa & Macarena Espinilla Estévez, 2021. "UJAmI Location: A Fuzzy Indoor Location System for the Elderly," IJERPH, MDPI, vol. 18(16), pages 1-22, August.
    3. Miguel à ngel López-Medina & Macarena Espinilla & Chris Nugent & Javier Medina Quero, 2020. "Evaluation of convolutional neural networks for the classification of falls from heterogeneous thermal vision sensors," International Journal of Distributed Sensor Networks, , vol. 16(5), pages 15501477209, May.

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