Brain Machine Interface (BMI) is a process where a communication link is established between a user and a device in which brain signals of the user is collected, processed and analyzed to recognize certain intention of the user. BMI helps patients to interact with others who are unable to communicate with the outside world due to motor disorder. In this paper, we have proposed a communication system that involves BMI where real-time brain signals are collected with the electrodes of EEG device placed at different lobes of the brain. Then the signals are transferred via Bluetooth to an Android smartphone. We have designed an app called “Chinta” which acts as an interface between the user and smartphone. The mobile app is trained for a user through performing different brain activities. A Boolean classifier has been used in this app, and it allows the smartphone to interpret and understand users intention. When the concentration level of an individual lies between 65% to 70%, the mobile app considers the user’s intention as true and responds accordingly. The output is in the form of voice in Bengali Language, and SMS is sent to designated persons whose contacts are configured in the app. We found that at least 14-channel electrodes are generally used in most of the BMI researches, however, in this research we have gathered the brain signals using a 5–channel EEG headset known as Emotiv Insight. Thus this research has demonstrated that with the help of 5– channel EEG headset, such communication system can also be established, which is economic and user–friendly.