S Iman Shirinbayan1, Jochem W Rieger2. 1. Department of Psychology, Carl von Ossietzky University of Oldenburg, Germany. 2. Department of Psychology, Carl von Ossietzky University of Oldenburg, Germany. Electronic address: jochem.rieger@uni-oldenburg.de.
Abstract
BACKGROUND: Functional magnetic resonance imaging is well suited to link neural population activation with movement parameters of complex natural arm movements. However, currently existing MR-compatible arm tracking devices are not constructed to measure arm joint movement parameters of unrestricted movements. Therefore, to date most research focuses on simple arm movements or includes very little knowledge about the actual movement kinematics. NEW METHOD: We developed a low cost gyroscope-based arm movement tracking system (GAMTS) that features MR-compatibility. The system consists of dual-axis analogue gyroscopes that measure rotations of upper and lower arm joints. After MR artifact reduction, the rotation angles of the individual arm joints are calculated and used to animate a realistic arm model that is implemented in the OpenSim platform. The OpenSim platform can then provide the kinematics of any point on the arm model. RESULTS: In order to demonstrate the capabilities of the system, we first assessed the quality of reconstructed wrist movements in a low-noise environment where typical MR-related problems are absent and finally, we validated the reconstruction in the MR environment. COMPARISON WITH EXISTING METHODS: The system provides the kinematics of the whole arm when natural unrestricted arm movements are performed inside the MR-scanner. CONCLUSION: The GAMTS is reliably capable of reconstructing the kinematics of trajectories and the reconstruction error is small in comparison with the movement induced variation of speed, displacement, and rotation. Moreover, the system can be used to probe brain areas for their correlation with movement kinematics.
BACKGROUND: Functional magnetic resonance imaging is well suited to link neural population activation with movement parameters of complex natural arm movements. However, currently existing MR-compatible arm tracking devices are not constructed to measure arm joint movement parameters of unrestricted movements. Therefore, to date most research focuses on simple arm movements or includes very little knowledge about the actual movement kinematics. NEW METHOD: We developed a low cost gyroscope-based arm movement tracking system (GAMTS) that features MR-compatibility. The system consists of dual-axis analogue gyroscopes that measure rotations of upper and lower arm joints. After MR artifact reduction, the rotation angles of the individual arm joints are calculated and used to animate a realistic arm model that is implemented in the OpenSim platform. The OpenSim platform can then provide the kinematics of any point on the arm model. RESULTS: In order to demonstrate the capabilities of the system, we first assessed the quality of reconstructed wrist movements in a low-noise environment where typical MR-related problems are absent and finally, we validated the reconstruction in the MR environment. COMPARISON WITH EXISTING METHODS: The system provides the kinematics of the whole arm when natural unrestricted arm movements are performed inside the MR-scanner. CONCLUSION: The GAMTS is reliably capable of reconstructing the kinematics of trajectories and the reconstruction error is small in comparison with the movement induced variation of speed, displacement, and rotation. Moreover, the system can be used to probe brain areas for their correlation with movement kinematics.