Removal OF EMG and ECG artifacts from EEG based on real time recurrent learning algorithm

Portable, heavy duty jacks used in the railway, mining and construction industries are expensive units including a motor, a pump, a working fluid reservoir and a hydraulic cylinder, all mounted on a wheeled carriage. The jacks are moved to a use location and often left in one position for a lengthy period of time. Thus, it is often necessary to stock a large number of expensive units. A simple solution to the problem involves a single power module including a carriage, a motor, a pump and a fluid reservoir, and separate lift modules including a hydraulic cylinder. A lift module is releasably connected to the power module for moving the module to a use location, where the hydraulic cylinder is actuated to raise a load. The two modules are then disconnected, another lift module is attached to the power module, and the resulting unit is moved to another use location.

[1]  Bruce J. West,et al.  Wavelet analysis of epileptic spikes. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  J. Si,et al.  A conceptual brain machine interface system , 2005, Proceedings. 2005 First International Conference on Neural Interface and Control, 2005..

[3]  C. Li,et al.  Detection of ECG characteristic points using wavelet transforms. , 1995, IEEE transactions on bio-medical engineering.

[4]  J. Gotman Automatic recognition of epileptic seizures in the EEG. , 1982, Electroencephalography and clinical neurophysiology.

[5]  Cuiwei Li,et al.  Detection of ECG characteristic points using wavelet transforms , 1995, IEEE Transactions on Biomedical Engineering.

[6]  C. Robert,et al.  Electroencephalogram processing using neural networks , 2002, Clinical Neurophysiology.