Accuracy of neural network is better than SVM classifier in motor imagery based brain computer interface. Performance of DWT feature extraction from EEG motor imagery signals is different in various paradigms. Tuning of classifier parameters by R3PSO could increase the accuracy of classifier. Proposed R3PSO together with 10-Fold CV leads to promising results for classifier tuning in motor imagery classification.