TY - JOUR
T1 - Fuzzy Cognitive Map to Classify Plantar Foot Alterations
AU - Ramirez Bautista, Julian Andres
AU - Chaparro-Cardenas, Silvia L.
AU - Hernandez-Zavala, Antonio
AU - Gallegos-Torres, Ruth Magdalena
AU - Zequera, Martha
AU - Tovar-Barrera, Yosabad
AU - Pradilla-Gomez, Juan M.
AU - Huerta-Ruelas, Jorge Adalberto
N1 - Publisher Copyright:
© 2003-2012 IEEE.
PY - 2022/7
Y1 - 2022/7
N2 - 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.
AB - 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.
KW - Clinical decision support systems
KW - bacterial foraging optimization algorithm
KW - fuzzy cognitive maps
KW - optimization algorithms
KW - plantar data analysis
UR - http://www.scopus.com/inward/record.url?scp=85135143978&partnerID=8YFLogxK
U2 - 10.1109/TLA.2021.9827472
DO - 10.1109/TLA.2021.9827472
M3 - Artículo
AN - SCOPUS:85135143978
SN - 1548-0992
VL - 20
SP - 1092
EP - 2000
JO - IEEE Latin America Transactions
JF - IEEE Latin America Transactions
IS - 7
ER -