Experimental architecture for synchronized recordings of cerebral, muscular and biomechanical data during lower limb activities

In this paper, an architecture that allows the synchronized recording of cerebral, muscular and biomechanical data during lower limb activities has been designed. The synchronization issue has been addressed. The goal is to analyze the relationship between the different signals, first during simple lower limbs movements, then extending the analysis to gait. Five incomplete spinal cord injury patients and four healthy users participated in experiments to validate the architecture. The users were asked to perform simple movements that involve only one or two joints, particularly knee and ankle. Future studies with the recorded data will address several issues, such as creating neuromusculoskeletal models that relate kinematics data with EMG information, improving the decoding of the angles of the lower limb through EEG signals, or analyzing the coherence between the EEG signals and the EMG information.

[1]  Andrés Úbeda,et al.  Decoding knee angles from EEG signals for different walking speeds , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[2]  B. Conway,et al.  The motor cortex drives the muscles during walking in human subjects , 2012, The Journal of physiology.

[3]  H. Hermens,et al.  European recommendations for surface electromyography: Results of the SENIAM Project , 1999 .

[4]  Kyuwan Choi,et al.  Reconstructing for joint angles on the shoulder and elbow from non-invasive electroencephalographic signals through electromyography , 2013, Front. Neurosci..

[5]  Dario Farina,et al.  EMG-Driven Forward-Dynamic Estimation of Muscle Force and Joint Moment about Multiple Degrees of Freedom in the Human Lower Extremity , 2012, PloS one.

[6]  Ronald N. Goodman,et al.  Neural decoding of treadmill walking from noninvasive electroencephalographic signals. , 2011, Journal of neurophysiology.

[7]  T. Castermans,et al.  Corticomuscular coherence revealed during treadmill walking: further evidence of supraspinal control in human locomotion , 2013, The Journal of physiology.

[8]  Valer Jurcak,et al.  10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems , 2007, NeuroImage.

[9]  José Luis Pons Rovira,et al.  A robotic exoskeleton for overground gait rehabilitation , 2013, 2013 IEEE International Conference on Robotics and Automation.

[10]  Evangelos A. Christou,et al.  Synchronous EMG Activity in the Piper Frequency Band Reveals the Corticospinal Demand of Walking Tasks , 2013, Annals of Biomedical Engineering.

[11]  Peter Desain,et al.  Feasibility of measuring event Related Desynchronization with electroencephalography during walking , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.