Neuro-feedback (NFB) has been considered as the cognitive science to retrain brainwave patterns. The occurrence of various brain waves take place at different frequencies, some fast, some quite slow called as delta (0.5–3.5 Hz very slow high amplitude experienced in deep restorative sleep), theta (4–8 Hz represents daydream correlated with mental inefficiency a twilight zone between waking and sleep), alpha (8–12 Hz, slower and larger correlated with a state of relaxation), beta (13–30 Hz, fast brainwave correlated with intellectual activity) and gamma (above 30 Hz, represents very fast EEG activity), specified as classic EEG bands. The proposed work focuses upon utilizing parallel computing based neurofeedback (PCBNFB) as rehabilitation means that will directly retrain the electrical activity (waves) in human brain. The concept of brain ability for making sense of doing different stimuli at the same time (simultaneously) is referred as Parallel Computing so the proposed research study will be directed upon utilizing parallel computing based neuro-feedback (PCBNFB) as a major therapeutic role in difficult areas like ADD (Adult Attention Deficit)/ADHD (Attention Deficit Hyperactivity Disorder), anxiety, obsessive compulsive disorder, learning disabilities, head injuries, Obsessive-Compulsive Disorder (OCD), reduces pain, quality of life for cancer patients suffering from chemotherapy etc. In a developing country like ours citing an ADD/ADHD as a reason for underperformance, underachievement is not taken seriously as its still unheard and unaware off and ADD/ADHD, compulsive and obsessive disorder patients spend their whole life considered as lazy, unorganized and duffers. The PCBNF unit will provide for each modality a real-time processing pipeline that handles signal acquisition and all the necessary methods/algorithms required for NFB calculation through effective and easier QEEG & LENS approach. Both QEEG and LENS have their advantages and limitations so the proposed research study explores in parallel fashion both QEES & LENS for better analysis of various neural disorders. Furthermore, it should provide the flexibility of using multimodal or uni-modal NFB.