TY - JOUR
T1 - Investigation of the effects of human body stability on joint angles’ prediction
AU - Pasha Zanoosi, A. A.
AU - Naderi, D.
AU - Sadeghi-Mehr, M.
AU - Feri, M.
AU - Beheshtiha, A. Sh
AU - Fallahnejad, K.
PY - 2015/5/13
Y1 - 2015/5/13
N2 - Loosing stability control in elderly or paralyzed has motivated researchers to study how a stability control system works and how to determine its state at every time instant. Studying the stability of a human body is not only an important problem from a scientific viewpoint, but also finally leads to new designs of prostheses and orthoses and rehabilitation methods. Computer modeling enables researchers to study and describe the reactions and propose a suitable and optimized motion pattern to strengthen the neuromuscular system and helps a human body maintain its stability. A perturbation as a tilting is exposed to an underfoot plate of a musculoskeletal model of the body to study the stability. The studied model of a human body included four links and three degrees of freedom with eight muscles in the sagittal plane. Lagrangian dynamics was used for deriving equations of motion and muscles were modeled using Hill’s model. Using experimental data of joint trajectories for a human body under tilting perturbation, forward dynamics has been applied to predict joint trajectories and muscle activation. This study investigated the effects of stability on predicting body joints’ motion. A new stability function for a human body, based on the zero moment point, has been employed in a forward dynamics procedure using a direct collocation method. A multi-objective optimization based on genetic algorithm has been proposed to employ stability as a robotic objective function along with muscle stresses as a biological objective function. The obtained results for joints’ motion were compared to experimental data. The results show that, for this type of perturbations, muscle stresses are in conflict with body stability. This means that more body stability requires more stresses in muscles and reverse. Results also show the effects of the stability objective function in better prediction of joint trajectories.
AB - Loosing stability control in elderly or paralyzed has motivated researchers to study how a stability control system works and how to determine its state at every time instant. Studying the stability of a human body is not only an important problem from a scientific viewpoint, but also finally leads to new designs of prostheses and orthoses and rehabilitation methods. Computer modeling enables researchers to study and describe the reactions and propose a suitable and optimized motion pattern to strengthen the neuromuscular system and helps a human body maintain its stability. A perturbation as a tilting is exposed to an underfoot plate of a musculoskeletal model of the body to study the stability. The studied model of a human body included four links and three degrees of freedom with eight muscles in the sagittal plane. Lagrangian dynamics was used for deriving equations of motion and muscles were modeled using Hill’s model. Using experimental data of joint trajectories for a human body under tilting perturbation, forward dynamics has been applied to predict joint trajectories and muscle activation. This study investigated the effects of stability on predicting body joints’ motion. A new stability function for a human body, based on the zero moment point, has been employed in a forward dynamics procedure using a direct collocation method. A multi-objective optimization based on genetic algorithm has been proposed to employ stability as a robotic objective function along with muscle stresses as a biological objective function. The obtained results for joints’ motion were compared to experimental data. The results show that, for this type of perturbations, muscle stresses are in conflict with body stability. This means that more body stability requires more stresses in muscles and reverse. Results also show the effects of the stability objective function in better prediction of joint trajectories.
KW - Direct collocation method
KW - Forward dynamics
KW - Genetic algorithm
KW - Human body stability
KW - Multi-objective optimization
KW - Musculoskeletal model
UR - http://www.scopus.com/inward/record.url?scp=84941422169&partnerID=8YFLogxK
U2 - 10.1007/s11044-015-9459-6
DO - 10.1007/s11044-015-9459-6
M3 - Article
AN - SCOPUS:84941422169
SN - 1384-5640
VL - 35
SP - 111
EP - 129
JO - Multibody System Dynamics
JF - Multibody System Dynamics
ER -