NeuroSurvey is conducted to get neurobiofeedback, is a type of biofeedback that uses real-time displays of brain activity most commonly electroencephalography (EEG), to teach self-regulation of brain function. Typically, sensors are placed on the scalp to measure activity, with measurements displayed using video dis-plays or sound. The next phenomenal outcome of the survey system would be brain computer interface, instead of general neuromuscular activities brain com-puter interface acquires direct input from the brain as signals process, analyze and transmit input to the desired output action. The brain computer Interface will be a revolutionary technology for people disabled by neuromuscular disorders. There are numerous hardware devices available to capture the brain waves and process them one such is the EEG (Electroencephalography) device, the EEG registers the ionic current flows within the neurons of the human brain along the scalp. The device has specific electrodes that records the neural oscillations of the brain and converts them into signals. And those signals are analyzed to generate the threshold report.Automation has been the top priority for twenty first century and it ranges from automating spell checking to a complex auto launch rockets. When it comes to neurosurvey classification, automatic classification of large, uncategorized, non summarized collection of data is very much required. Manual classification of neurosurvey may not only need the help of experts from their respective domain and they are also done at the expense of precious time. In this paper we have proposed a novel scheme to classify and summarize neurosurvey based on classification and clustering algorithms. Once summarization is done we can use them to generate a survey of their respective category.