The work presented in this paper is our first step toward the develop- ment of an exoskeleton for human gait support. The device we foresee should be suitable for assisting walking in paralyzed subjects and should be based on myo- electrical muscular signals (EMGs) as a communication channel between the hu- man and the machine. This paper concentrates on the design of a biomechanical model of the human lower extremity. The system predicts subjects intentions from the analysis of his/her electromyographical activity. Our model takes into account three main factors. Firstly, the main muscles spanning the knee articulation. Sec- ondly, the gravity affecting the leg during its movement. Finally, it considers the limits within which the leg swings. Furthermore, it is capable of estimating several knee parameters such as joint moment, angular acceleration, angular velocity, and angular position. In order to have a visual feedback of the predicted movements we have implemented a three-dimensional graphical simulation of a human leg which moves in response to the commands computed by the model.
|Title of host publication||Intelligent Autonomous Systems 10 (IAS-10)|
|Editors||Wolfram Burgard, Rüdiger Dillmann, Christian Plagemann, Nikolaus Vahrenkamp|
|Number of pages||8|
|Publication status||Published - 2008|
- EMG signals
- Human knee
Sartori, M., Chemello, G., Reggiani, M., & Pagello, E. (2008). Control of a virtual leg via EMG signals from four thigh muscles. In W. Burgard, R. Dillmann, C. Plagemann, & N. Vahrenkamp (Eds.), Intelligent Autonomous Systems 10 (IAS-10) (pp. 137-144). IOS Press. https://doi.org/10.3233/978-1-58603-887-8-137