Abstract
Low back pain affects a large proportion of the adult population at some point in their lives and has a major economic and social impact. To soften this impact, one possible solution is to make use of recommender systems, which have already been introduced in several health fields. In this paper, we present TPLUFIB-WEB, a novel fuzzy linguistic Web system that uses a recommender system to provide personalized exercises to patients with low back pain problems and to offer recommendations for their prevention. This system may be useful to reduce the economic impact of low back pain, help professionals to assist patients, and inform users on low back pain prevention measures. A strong part of TPLUFIB-WEB is that it satisfies the Web quality standards proposed by the Health On the Net Foundation (HON), Official College of Physicians of Barcelona, and Health Quality Agency of the Andalusian Regional Government, endorsing the health information provided and warranting the trust of users.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ehrlich, G.E.: Low back pain. Bulletin of the World Health Organization 81(9), 671–676 (2003)
Burton, A.K., McClune, T.D., Clarke, R.D., Main, C.J.: Long-term follow-up of patients with low back pain attending for manipulative care: outcomes and predictors. Manual Therapy 9(1), 30–35 (2004)
Cohen, I., Rainville, J.: Aggressive exercise as treatment for chronic low back pain. Sports Medicine 32(1), 75–82 (2002)
Vizirianakis, I.S.: Nanomedicine and personalized medicine toward the application of pharmacotyping in clinical practice to improve drug-delivery outcomes. Nanomedicine: Nanotechnology, Biology and Medicine 7, 11–17 (2011)
Al-Shorbaji, N.: Health and medical informatics. Technical paper, World Health Organization, RA/HIS, Regional Office for the Eastern Mediterranean (2001)
Santana, S., Lausen, B., Bujnowska-Fedak, M., Chronaki, C., Prokosch, H.U., Wynn, R.: Informed citizen and empowered citizen in health: results from an european survey. BMC Family Practice 12, 20 (2011)
Burke, R.: Hybrid web recommender systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 377–408. Springer, Heidelberg (2007)
Porcel, C., Herrera-Viedma, E.: Dealing with incomplete information in a fuzzy linguistic recommender system to disseminate information in university digital libraries. Knowledge-Based Systems 23, 32–39 (2010)
Tejeda-Lorente, A., Porcel, C., Peis, E., Sanz, R., Herrera-Viedma, E.: A quality based recommender system to disseminate information in a university digital library. Information Sciences 261(52-69) (2014)
Hussein, A., Omar, W., Li, X., Ati, M.: Efficient chronic disease diagnosis prediction and recommendation system. In: IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), Malaysia, pp. 17–19 (2012)
Alonso, S., Pérez, I., Cabrerizo, F., Herrera-Viedma, E.: A linguistic consensus model for web 2.0 communities. Applied Soft Computing 13(1), 149–157 (2013)
Herrera, F., Alonso, S., Chiclana, F., Herrera-Viedma, E.: Computing with words in decision making: Foundations, trends and prospects. Fuzzy Optimization and Decision Making 8(4), 337–364 (2009)
Palacín-Marín, F., Esteban-Moreno, B., Olea, N., Herrera-Viedma, E., Arroyo-Morales, M.: Agreement between telerehabilitation and face-to-face clinical outcome measurements for low back pain in primary care. Spine 38(11), 947–952 (2013)
Porcel, C., Moreno, J., Herrera-Viedma, E.: A multi-disciplinar recommender system to advice research resources in university digital libraries. Expert Systems with Applications 36(10), 12520–12528 (2009)
Porcel, C., Tejeda-Lorente, A., Martínez, M.A., Herrera-Viedma, E.: A hybrid recommender system for the selective dissemination of research resources in a technology transfer office. Information Sciences 184(1), 1–19 (2012)
Zadeh, L.: The concept of a linguistic variable and its applications to approximate reasoning. Part I, Information Sciences 8, 199–249 (1975), Part II, Information Sciences 8, 301–357 (1975), Part III, Information Sciences 9, 43–80 (1975)
Herrera-Viedma, E., López-Herrera, A., Luque, M., Porcel, C.: A fuzzy linguistic IRS model based on a 2-tuple fuzzy linguistic approach. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems 15(2), 225–250 (2007)
Herrera, F., Martínez, L.: A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems 8(6), 746–752 (2000)
Herrera, F., Martínez, L.: A model based on linguistic 2-tuples for dealing with multigranularity hierarchical linguistic contexts in multiexpert decision-making. IEEE Transactions on Systems, Man and Cybernetics. Part B: Cybernetics 31(2), 227–234 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Esteban, B., Tejeda-Lorente, Á., Porcel, C., Moral-Muñoz, J.A., Herrera-Viedma, E. (2014). Aiding in the Treatment of Low Back Pain by a Fuzzy Linguistic Web System. In: Cornelis, C., Kryszkiewicz, M., Ślȩzak, D., Ruiz, E.M., Bello, R., Shang, L. (eds) Rough Sets and Current Trends in Computing. RSCTC 2014. Lecture Notes in Computer Science(), vol 8536. Springer, Cham. https://doi.org/10.1007/978-3-319-08644-6_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-08644-6_26
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08643-9
Online ISBN: 978-3-319-08644-6
eBook Packages: Computer ScienceComputer Science (R0)