A Personalized Approach for Predicting the Effect of Aerobic Exercise on Blood Pressure Using a Fuzzy Inference System

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

7 Citations (Scopus)

Abstract

Regular aerobic exercise is a recommended treatment for elevated blood pressure (BP). However, making permanent lifestyle changes is not easy. Having personally relevant information about the treatment, about its effects and importance, is a precondition for motivation. Thus, the first step towards a successful lifestyle change is appropriate education. This paper describes a Sugeno-type Fuzzy Inference System (FIS) that predicts the effect of regular aerobic exercise on blood pressure based on the exercise dose variables, exercise frequency and intensity, as well as demographics (age, gender, ethnicity), and the baseline BP of a person. Since BP response to exercise varies largely between individuals, the system takes an initial step towards personalized prediction. Hence, the system can be used to educate a person about the benefits of exercise on BP in a personally relevant way, providing more accurate information than traditional education materials. Furthermore, preliminary validation results of the performance of the FIS are promising. The predictions comply with the findings of medical research for populations, though the individual-level validation remains still to be done.
Original languageEnglish
Title of host publicationProceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. Boston, MA, USA, 30 Aug. - 3 Sept. 2011
PublisherInstitute of Electrical and Electronic Engineers IEEE
Pages8299-8302
ISBN (Print)9781424441211
DOIs
Publication statusPublished - 2011
MoE publication typeA4 Article in a conference publication
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society: EMBC 2011 - Boston, United States
Duration: 30 Aug 20113 Sep 2011

Conference

Conference33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CountryUnited States
CityBoston
Period30/08/113/09/11

Fingerprint

Blood pressure
Fuzzy inference
Exercise
Blood Pressure
Life Style
Education
Biomedical Research
Motivation
Demography
Population

Keywords

  • decision support methods and systems
  • personalised health

Cite this

Honka, A., van Gils, M., & Pärkkä, J. (2011). A Personalized Approach for Predicting the Effect of Aerobic Exercise on Blood Pressure Using a Fuzzy Inference System. In Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. Boston, MA, USA, 30 Aug. - 3 Sept. 2011 (pp. 8299-8302). Institute of Electrical and Electronic Engineers IEEE. https://doi.org/10.1109/IEMBS.2011.6092046
Honka, Anita ; van Gils, Mark ; Pärkkä, Juha. / A Personalized Approach for Predicting the Effect of Aerobic Exercise on Blood Pressure Using a Fuzzy Inference System. Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. Boston, MA, USA, 30 Aug. - 3 Sept. 2011. Institute of Electrical and Electronic Engineers IEEE, 2011. pp. 8299-8302
@inproceedings{1765e55f74bb4c74b64105b18ce2c3e0,
title = "A Personalized Approach for Predicting the Effect of Aerobic Exercise on Blood Pressure Using a Fuzzy Inference System",
abstract = "Regular aerobic exercise is a recommended treatment for elevated blood pressure (BP). However, making permanent lifestyle changes is not easy. Having personally relevant information about the treatment, about its effects and importance, is a precondition for motivation. Thus, the first step towards a successful lifestyle change is appropriate education. This paper describes a Sugeno-type Fuzzy Inference System (FIS) that predicts the effect of regular aerobic exercise on blood pressure based on the exercise dose variables, exercise frequency and intensity, as well as demographics (age, gender, ethnicity), and the baseline BP of a person. Since BP response to exercise varies largely between individuals, the system takes an initial step towards personalized prediction. Hence, the system can be used to educate a person about the benefits of exercise on BP in a personally relevant way, providing more accurate information than traditional education materials. Furthermore, preliminary validation results of the performance of the FIS are promising. The predictions comply with the findings of medical research for populations, though the individual-level validation remains still to be done.",
keywords = "decision support methods and systems, personalised health",
author = "Anita Honka and {van Gils}, Mark and Juha P{\"a}rkk{\"a}",
note = "Project code: 18982",
year = "2011",
doi = "10.1109/IEMBS.2011.6092046",
language = "English",
isbn = "9781424441211",
pages = "8299--8302",
booktitle = "Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. Boston, MA, USA, 30 Aug. - 3 Sept. 2011",
publisher = "Institute of Electrical and Electronic Engineers IEEE",
address = "United States",

}

Honka, A, van Gils, M & Pärkkä, J 2011, A Personalized Approach for Predicting the Effect of Aerobic Exercise on Blood Pressure Using a Fuzzy Inference System. in Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. Boston, MA, USA, 30 Aug. - 3 Sept. 2011. Institute of Electrical and Electronic Engineers IEEE, pp. 8299-8302, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, United States, 30/08/11. https://doi.org/10.1109/IEMBS.2011.6092046

A Personalized Approach for Predicting the Effect of Aerobic Exercise on Blood Pressure Using a Fuzzy Inference System. / Honka, Anita; van Gils, Mark; Pärkkä, Juha.

Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. Boston, MA, USA, 30 Aug. - 3 Sept. 2011. Institute of Electrical and Electronic Engineers IEEE, 2011. p. 8299-8302.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

TY - GEN

T1 - A Personalized Approach for Predicting the Effect of Aerobic Exercise on Blood Pressure Using a Fuzzy Inference System

AU - Honka, Anita

AU - van Gils, Mark

AU - Pärkkä, Juha

N1 - Project code: 18982

PY - 2011

Y1 - 2011

N2 - Regular aerobic exercise is a recommended treatment for elevated blood pressure (BP). However, making permanent lifestyle changes is not easy. Having personally relevant information about the treatment, about its effects and importance, is a precondition for motivation. Thus, the first step towards a successful lifestyle change is appropriate education. This paper describes a Sugeno-type Fuzzy Inference System (FIS) that predicts the effect of regular aerobic exercise on blood pressure based on the exercise dose variables, exercise frequency and intensity, as well as demographics (age, gender, ethnicity), and the baseline BP of a person. Since BP response to exercise varies largely between individuals, the system takes an initial step towards personalized prediction. Hence, the system can be used to educate a person about the benefits of exercise on BP in a personally relevant way, providing more accurate information than traditional education materials. Furthermore, preliminary validation results of the performance of the FIS are promising. The predictions comply with the findings of medical research for populations, though the individual-level validation remains still to be done.

AB - Regular aerobic exercise is a recommended treatment for elevated blood pressure (BP). However, making permanent lifestyle changes is not easy. Having personally relevant information about the treatment, about its effects and importance, is a precondition for motivation. Thus, the first step towards a successful lifestyle change is appropriate education. This paper describes a Sugeno-type Fuzzy Inference System (FIS) that predicts the effect of regular aerobic exercise on blood pressure based on the exercise dose variables, exercise frequency and intensity, as well as demographics (age, gender, ethnicity), and the baseline BP of a person. Since BP response to exercise varies largely between individuals, the system takes an initial step towards personalized prediction. Hence, the system can be used to educate a person about the benefits of exercise on BP in a personally relevant way, providing more accurate information than traditional education materials. Furthermore, preliminary validation results of the performance of the FIS are promising. The predictions comply with the findings of medical research for populations, though the individual-level validation remains still to be done.

KW - decision support methods and systems

KW - personalised health

UR - http://www.scopus.com/inward/record.url?scp=84861688279&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.2011.6092046

DO - 10.1109/IEMBS.2011.6092046

M3 - Conference article in proceedings

SN - 9781424441211

SP - 8299

EP - 8302

BT - Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. Boston, MA, USA, 30 Aug. - 3 Sept. 2011

PB - Institute of Electrical and Electronic Engineers IEEE

ER -

Honka A, van Gils M, Pärkkä J. A Personalized Approach for Predicting the Effect of Aerobic Exercise on Blood Pressure Using a Fuzzy Inference System. In Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. Boston, MA, USA, 30 Aug. - 3 Sept. 2011. Institute of Electrical and Electronic Engineers IEEE. 2011. p. 8299-8302 https://doi.org/10.1109/IEMBS.2011.6092046