The aim of this study is to find a correlation between human intelligence with EEG signals. Information processing in the brain is reflected in brain oscillations. The brains of more intelligent individuals work more efficiently when engaged in cognitive task performance as compared to those of less
Intelligence meter
The aim of this study is to find a correlation between human intelligence with EEG signals. Information processing in the brain is reflected in brain oscillations. The brains of more intelligent individuals work more efficiently when engaged in cognitive task performance as compared to those of less intelligent ones. However, it is still not clear how neurobiological factors contribute to more effective cognitive performance. The way used by us to investigate the intelligence level is the network neuroscience approach.
The first step would be data acquisition through an EEG sensor and some core pre-processing of data would lead to feature extraction for our regressor machine learning model. The core objective of our project is to investigate which frequency bands are more related to intelligence measures. The result of our ML model will tell us the intelligence of a person.
The objectives of this study are:
• Acquisition of EEG data set
• Selection of appropriate features for detection of human intelligence
• Algorithm testing using state of art machine learning algorithm
• Comparison of the proposed scheme with the other methods in the literature.
The methodology of the project is a four-step process given in the figure below. The five steps of the methodology are:
This project intends to build software that can take input from EEG and can generate the levels of intelligence. so we don't have to fill the long and hectic intelligence test for our IQ level we just have to sit relax with our eyes closed to record EEG signals through the MUSE headband and on the bases of that data our intelligence level or Iq will be predicted.
A software application (python based) that will display the intelligence level of the user and the dataset used for a training ML algorithm.
The training dataset is the most important part of our project the more accurate it will be the more accurate the predicted result will be.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Muse Headband. | Equipment | 1 | 70000 | 70000 |
| Total in (Rs) | 70000 |
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