Identification of active properties of knee joint using GA optimization
Ibrahim, BSKK, Huq, MS, Tokhi, MO, Gharooni, SC, Jailani, R and Hussain, Z (2009). Identification of active properties of knee joint using GA optimization. World Academy of Science, Engineering and Technology. 55, pp. 441-446.
|Authors||Ibrahim, BSKK, Huq, MS, Tokhi, MO, Gharooni, SC, Jailani, R and Hussain, Z|
Functional Electrical Stimulation requires an accurate model of electrically stimulated muscles to control the muscle contraction force. Characterization of electrically stimulated muscle is complex because of the non-linearity and time-varying nature of the system with interdependent variables. The muscle model consists of relatively well known time-invariant passive properties and uncertain time-variant active properties. In this research a new approach for estimating nonlinear active properties of the electrically stimulated quadriceps muscle group is investigated. The objective of this study is to develop a model that could be used to describe active joint properties including continuous-time nonlinear activation dynamics and nonlinear static contraction. As an example, the modelling of a freely swinging lower leg by electrical stimulation of the quadriceps is considered.
|Keywords||Knee joint; Functional electrical stimulation; Genetic algorithm; Fuzzy inference system|
|Journal||World Academy of Science, Engineering and Technology|
|Journal citation||55, pp. 441-446|
|Publication process dates|
|Accepted||01 Jan 2009|
|Deposited||29 Apr 2020|
|Accepted author manuscript|
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