Aiding in the Treatment of Low Back Pain by a Fuzzy Linguistic Web System
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.
KeywordsLow back pain health care recommender systems fuzzy linguistic modeling quality evaluation
Unable to display preview. Download preview PDF.
- 1.Ehrlich, G.E.: Low back pain. Bulletin of the World Health Organization 81(9), 671–676 (2003)Google Scholar
- 5.Al-Shorbaji, N.: Health and medical informatics. Technical paper, World Health Organization, RA/HIS, Regional Office for the Eastern Mediterranean (2001)Google Scholar
- 9.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)Google Scholar
- 10.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)Google Scholar
- 16.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)Google Scholar