My proposed research seeks to understand the complex relationship between the neural signals that activate the muscles of the legs, and the global forces that the legs produce to accomplish locomotion. A model of this relationship will be invaluable in the development of future functional electrical stimulation (FES) and neuroprosthesis devices intended to augment or replace the impaired portion of a neuromusculoskeletal system. In the human, such models exist but ethical considerations limit the development and testing of FES devices. In the rat, more freedom exists to test applications of the model, but there has been little work done toward developing the model itself. Therefore, I propose to develop a computational model of a rat hindlimb, which will precisely characterize the mathematical relationship between the neural input to the leg as reflected in electromyographic (EMG) recordings of the muscle activation, and its dynamic behavior as output. As the first part of this project, I will measure the morphological parameters that govern force output (i.e. joint torques and forces at the foot/ground interface), namely muscle paths, angles, and moment arms at the joints. These data will be useful not only in this project, but in any investigation of rat hindlimb dynamics, and are not currently found in the literature. The physiological muscle properties required for development of the model are also not well known in the rat. As the second part of model development, I will measure the physiological properties that govern local force generation by individual muscles. Again, these data alone will be a significant contribution to the utility of the rat model in biomechanics research. The third and final part of the project is to combine the morphological and physiological data with a Hill type muscle force generation model. The combined model will ease future FES and neuroprosthesis development in the rat model in several ways. Perhaps most significantly, in the most successful mechanical control schemes the controller uses an estimate of the system state - found using the model of the system - to determine the appropriate input. Thus with the model I will develop, established control theory will be much more easily applied to FES and neuroprosthesis development. This project draws on biomechanics, physiology, and control theory to develop a model of the rat hindlimb. The model is an important step toward creating prostheses that allow spinal cord injury patients to regain use of the affected muscles and limbs. ? ? ?
| Johnson, Will L; Jindrich, Devin L; Roy, Roland R et al. (2012) Quantitative metrics of spinal cord injury recovery in the rat using motion capture, electromyography and ground reaction force measurement. J Neurosci Methods 206:65-72 |
| Johnson, Will L; Jindrich, Devin L; Zhong, Hui et al. (2011) Application of a rat hindlimb model: a prediction of force spaces reachable through stimulation of nerve fascicles. IEEE Trans Biomed Eng 58:3328-38 |
| Johnson, Will L; Jindrich, Devin L; Roy, Roland R et al. (2008) A three-dimensional model of the rat hindlimb: musculoskeletal geometry and muscle moment arms. J Biomech 41:610-9 |
