TY - GEN
T1 - Artificial neural network model for the characterization of human locomotion parameters
AU - Ashmi, A. M.
AU - Mathew, Anila
AU - Sivanandan, K. S.
AU - Jayaraj, S.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/6/16
Y1 - 2021/6/16
N2 - Artificial walking aids compensate the physical limitations experienced by handicapped persons in their routine activities and help them to reduce their dependence on others. The characteristics of healthy gait in terms of angular velocity, angular acceleration, linear velocity and linear acceleration needs to be examined for designing a walking aid. The human locomotion was analyzed using high resolution video camera for normal level walking. The angular displacement of knee and hip were recorded and an artificial neural network model was developed for estimating the human locomotion parameters. The average value based approach was employed in the developed model for linearization. The output response of the model can be used for activating joint angles in the walking aid and helped in estimating linear displacement. Also, the complexity involved in the dynamics of human gait can be reduced to a greater extent with the help of this modeling technique.
AB - Artificial walking aids compensate the physical limitations experienced by handicapped persons in their routine activities and help them to reduce their dependence on others. The characteristics of healthy gait in terms of angular velocity, angular acceleration, linear velocity and linear acceleration needs to be examined for designing a walking aid. The human locomotion was analyzed using high resolution video camera for normal level walking. The angular displacement of knee and hip were recorded and an artificial neural network model was developed for estimating the human locomotion parameters. The average value based approach was employed in the developed model for linearization. The output response of the model can be used for activating joint angles in the walking aid and helped in estimating linear displacement. Also, the complexity involved in the dynamics of human gait can be reduced to a greater extent with the help of this modeling technique.
UR - http://www.scopus.com/inward/record.url?scp=85113352911&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113352911&partnerID=8YFLogxK
U2 - 10.1109/ICCISc52257.2021.9484899
DO - 10.1109/ICCISc52257.2021.9484899
M3 - Conference contribution
AN - SCOPUS:85113352911
T3 - ICCISc 2021 - 2021 International Conference on Communication, Control and Information Sciences, Proceedings
BT - ICCISc 2021 - 2021 International Conference on Communication, Control and Information Sciences, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 International Conference on Communication, Control and Information Sciences, ICCISc 2021
Y2 - 16 June 2021 through 18 June 2021
ER -
