Fuzzy Cognitive Map to Classify Plantar Foot Alterations

Authors

  • Julian Andres Ramirez Bautista Fundación Universitaria de San Gil - UNISANGIL https://orcid.org/0000-0002-6472-5751
  • Silvia L. Chaparro-Cárdenas Research Department of Fundación Universitaria de San Gil – UNISANGIL, Santander, Colombia https://orcid.org/0000-0002-2589-259X
  • Antonio Hernández-Zavala Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada – Instituto Politécnico Nacional, Av. Cerro Blanco #141, Col. Colinas del Cimatario, Querétaro, México https://orcid.org/0000-0002-0964-9522
  • Ruth Magdalena Gallegos-Torres Department of Nursing, Universidad Autónoma de Querétaro, Centro Universitario, 76010, Querétaro, México https://orcid.org/0000-0001-8034-4089
  • Martha Zequera Departamento de Electrónica, BASPI-FootLaB, Pontificia Universidad Javeriana, Cra. 7 No. 40-62, Bogotá, Colombia https://orcid.org/0000-0001-8226-3370
  • Yosabad Tovar-Barrera Yosafisio Clinic of Querétaro, México https://orcid.org/0000-0002-1743-5671
  • Juan M. Pradilla-Gómez School of Medicine, Pontificia Universidad Javeriana, Cra 7 No. 40–62, Bogotá, Colombia https://orcid.org/0000-0002-4423-1623
  • Jorge Adalberto Huerta-Ruelas Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada – Instituto Politécnico Nacional, Av. Cerro Blanco #141, Col. Colinas del Cimatario, Querétaro, México https://orcid.org/0000-0001-5632-3368

Keywords:

Clinical decision support systems, bacterial foraging optimization algorithm, fuzzy cognitive maps, optimization algorithms, plantar data analysis

Abstract

The function of the back, hip, knee, ankle and other orthopedic alterations of the human body can be analyzed through plantar pressure distribution. The development of Clinical Decision Support Systems (CDSS) can handle the uncertainties present in biological data using different Artificial Intelligence techniques to obtain accurate and easy-to-use systems. This paper presents the application of a Fuzzy Cognitive Map (FCM) formulation, for knowledge extraction in the classification of human plantar foot alterations, with a relatively small and transparent model. The FCM is trained using the Bacterial Search Optimization Algorithm (BFOA). One hundred and twenty-five volunteer subjects (aged 20-68 years) participated in the study. Classification of the foot into normal (n=31), flat (n=32), cavus type III (n=31) and cavus type IV (n=31) to train the system was performed by specialized physicians. The test was performed by walking on a FreeMed platform. The proposed method shows an accuracy rate of about 89% in the classification task and allows extracting information related to the important factors that the system considers to make a decision.

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Author Biographies

Julian Andres Ramirez Bautista, Fundación Universitaria de San Gil - UNISANGIL

J. A. Ramirez-Bautista, Electronic Engineer from the Fundación Universitaria de San Gil (UNISANGIL), San Gil, Colombia, in 2013. The master degree in advanced technology, and the Ph.D. degree in advanced technology, with a specialty in mechatronics, from the Research Center for Applied Science and Advanced Technology (CICATA), Instituto Politécnico Nacional, Queretaro, Mexico, in 2016 and 2020. His research interests include fuzzy systems, hybrid systems, interface development, neural networks, and clinical decision support systems. He is currently a full-time professor at the Faculty of Natural Sciences and Engineering of UNISANGIL.

Silvia L. Chaparro-Cárdenas, Research Department of Fundación Universitaria de San Gil – UNISANGIL, Santander, Colombia

Electronic Engineer from the Fundación Universitaria de San Gil (UNISANGIL), San Gil, Colombia, in 2013. The master degree in advanced technology, and the Ph.D. degree in advanced technology, with a specialty in mechatronics, from the Research Center for Applied Science and Advanced Technology (CICATA), Instituto Politécnico Nacional, Queretaro, Mexico, in 2016 and 2021. She is currently a professor and researcher in UNISANGIL, Colombia. Her research interests include fuzzy systems, hybrid systems, robotic rehabilitation devices, neural networks, intelligent control and electrophysiology.

Antonio Hernández-Zavala, Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada – Instituto Politécnico Nacional, Av. Cerro Blanco #141, Col. Colinas del Cimatario, Querétaro, México

A. Hernández-Zavala, received the Computer Systems engineer title from the Tecnológico de Estudios Superiores de Ecatepec, México, in 2001. Received the Master degree in computer engineering with a speciality in digital systems in 2004 and the Ph. D degree in computer architecture in 2009, both from the Centro de Investigación en Computación from Instituto Politécnico Nacional, México. Currently, he is a member of the National Researchers System (SNI) and is a full-time professor at Mechatronics department in Centro de Investigación en Ciencia Aplicada y Tecnologia Avanzada CICATA from IPN, in Querétaro city. His research interests include Fuzzy Logic, Fuzzy Hardware, Fuzzy Control, Neural Networks, Computer Architecture, and Digital Logics.

Ruth Magdalena Gallegos-Torres, Department of Nursing, Universidad Autónoma de Querétaro, Centro Universitario, 76010, Querétaro, México

R. M. Gallegos-Torres, bachelor's Degree in Nursing from the Universidad Veracruzana, Master's Degree in Nursing Sciences and Doctor in Health Sciences from the Universidad Autónoma de Querétaro. Specialty in Drug Phenomenon Research in Toronto, Canada. Multiple courses and diplomas in research. More than 70 publications in scientific journals and national and international papers. She has been conducting research for more than 23 years. Since 2008, she has been teaching research subjects at undergraduate and graduate level. She has directed multiple undergraduate and master's theses. Full-time professor since 2006 of the Faculty of Nursing at the Autonomous University of Queretaro. Certified as a teacher by the Mexican Council for Nursing Certification.

Martha Zequera, Departamento de Electrónica, BASPI-FootLaB, Pontificia Universidad Javeriana, Cra. 7 No. 40-62, Bogotá, Colombia

M. Zequera obtained her MSc in Biomedical Engineering at the University of Dundee, UK, in 1992 and her PhD from the Bioengineering Unit of the University of Strathclyde, UK, in 2003. Since 2010 she is an Honorary Research Fellow of the University of Strathclyde in the Bioengineering Unit, United Kingdom. Prof. Zequera is Full Professor in the Electronics Department of the Faculty of Engineering, at the Pontificia Universidad Javeriana, Bogotá, Columbia since 2010. She has been working as a researcher for 24 years in the Bioengineering Research Group "BASPI", oriented to biosignal and image processing analysis. Her current research interests include the integration of emerging technologies and the analysis of information with the use of deep learning techniques for the prediction of neurological diseases in elderly patients with diabetes.

Yosabad Tovar-Barrera, Yosafisio Clinic of Querétaro, México

Y. Tovar-Barrera, Bachelor in Physical Therapy graduated from the Polytechnic University of Santa Rosa Jauregui (UPSRJ), in Queretaro Mexico, in 2016. He performed his social service at the Hospital General Naval de Alta Especialidad (HOSGENAES) 2015-2016. Worked in the Integral Development System for the family (DIF) of Tequisquiapan, (2017-2020). In 2018 he completed a certification in Manual Therapy of Cervicalgias and Neuralgias and Cervicobrachial. In 2019 he completed a certificate in Neurodianamia. In 2020 he completed a certification in recommendations for a safe return to work before the COVID-19. In 2021 he completed a certification in low back pain. He currently works at Yosafisio Clinic.

Juan M. Pradilla-Gómez, School of Medicine, Pontificia Universidad Javeriana, Cra 7 No. 40–62, Bogotá, Colombia

J. M. Pradilla-Gómez Professional doctor from the Pontificia Universidad Javeriana born in Bucaramanga – Colombia and studied in Bogotá - Colombia, with a high sense of commitment currently working as a surgical assistant in Orthopedics and as doctor of the hospital area of the orthopedic service in two different renowned institutions (Clinica La Sabana and Fundacion Cardioinfantil) in the city of Bogotá. He constantly maintains the willingness to acquire academic and professional concepts participating in multiples symposia and congresses, in addition to the desire to continue developing research in the area by contributing to publication related to the area of orthopedic. Also, he has a high sense of responsibility and humanity by being volunteer in programs of charity in his country as (TECHO)

Jorge Adalberto Huerta-Ruelas, Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada – Instituto Politécnico Nacional, Av. Cerro Blanco #141, Col. Colinas del Cimatario, Querétaro, México

J. A. Huerta-Ruelas, received the Master of Science degree in solid state physics and the Ph.D. degree in electrical engineering from the Autonomous University of San Luis Potosi, San Luis Potosi, Mexico, in 1995 and 2000, respectively. He held a Postdoctoral Fellowship in the Department of Science and Food Technology, Oregon State University, Corvallis, OR, USA, in 2004. He is a Professor with the Advanced Technology Graduate Program, teaching: optical characterization techniques, interaction of radiation with matter, and the writing and publishing of technical and scientific documents. He is currently a member of the National System of Researchers. His current research focuses on the development of optical measuring systems for use in research and industrial process control, that includes instrumentation, optomechanical design, and programming.

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Published

2022-04-27

How to Cite

Ramirez Bautista, J. A., Chaparro-Cárdenas, S. L., Hernández-Zavala, A., Gallegos-Torres, R. M., Zequera, M., Tovar-Barrera, Y., Pradilla-Gómez, J. M., & Huerta-Ruelas, J. A. (2022). Fuzzy Cognitive Map to Classify Plantar Foot Alterations. IEEE Latin America Transactions, 20(7), 1092–2000. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/6319

Issue

Vol. 20 No. 7 (2022): Ordinary Issue

Section

Articles