TY - GEN
T1 - A real-time algorithm for movement assessment using fuzzy logic of hip arthroplasty patients
AU - Guevara, César
AU - Jadán-Guerrero, Janio
AU - Rybarczyk, Yves
AU - Acosta-Vargas, Patricia
AU - Esparza, Wilmer
AU - González, Mario
AU - Villarreal, Santiago
AU - Sanchez-Gordon, Sandra
AU - Calle-Jimenez, Tania
AU - Nunes, Isabel L.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - The present work proposes a model of detection of movements of patients in rehabilitation of hip surgery in real time. The model applies the Fuzzy Logic technique to identify correct and incorrect movements in the execution of rehabilitation exercises using the motion capture device called XBOXONE Microsoft’s Kinect. An algorithm generates a multivalent logical model that allows the simultaneous modeling of deductive and decision-making processes. This model identifies the correct and incorrect movements of the patient during the execution of rehabilitation exercises. This model uses all the information collected from 24 points of the body with their respective axes of coordinates (X, Y, Z). Using data mining analysis, the algorithm selects the most remarkable attributes, eliminating non-relevant information. The main contributions of this work are: creation of a patient profile based on the movement of the human being in a generic way for the detection and prediction of execution of physical exercises in rehabilitation. On the other hand, an avatar was developed in 3D, which copies and evidences graphically the exercises performed by patients in real time.
AB - The present work proposes a model of detection of movements of patients in rehabilitation of hip surgery in real time. The model applies the Fuzzy Logic technique to identify correct and incorrect movements in the execution of rehabilitation exercises using the motion capture device called XBOXONE Microsoft’s Kinect. An algorithm generates a multivalent logical model that allows the simultaneous modeling of deductive and decision-making processes. This model identifies the correct and incorrect movements of the patient during the execution of rehabilitation exercises. This model uses all the information collected from 24 points of the body with their respective axes of coordinates (X, Y, Z). Using data mining analysis, the algorithm selects the most remarkable attributes, eliminating non-relevant information. The main contributions of this work are: creation of a patient profile based on the movement of the human being in a generic way for the detection and prediction of execution of physical exercises in rehabilitation. On the other hand, an avatar was developed in 3D, which copies and evidences graphically the exercises performed by patients in real time.
KW - Fuzzy logic
KW - Hip arthroplasty patients
KW - Kinect
KW - Movement assessment
KW - Tele-rehabilitation platform
UR - http://www.scopus.com/inward/record.url?scp=85049642535&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-94334-3_27
DO - 10.1007/978-3-319-94334-3_27
M3 - Conference contribution
AN - SCOPUS:85049642535
SN - 9783319943336
T3 - Advances in Intelligent Systems and Computing
SP - 265
EP - 273
BT - Advances in Human Factors and Systems Interaction - Proceedings of the AHFE 2018 International Conference on Human Factors and Systems Interaction, 2018
A2 - Nunes, Isabel L.
PB - Springer Verlag
T2 - AHFE International Conference on Human Factors and Systems Interaction, 2018
Y2 - 21 July 2018 through 25 July 2018
ER -