Human brain contains about 100 billion of massively (connected?) neurons (nerve cells).
It has the incredible capacity to capture an image/scene, perceive, judge, calculate,
reason, learn (what not) through the formation of neural networks with the exchange of
electrochemical impulses among the neurons (probably nature inspired optimum ways) to
achieve a task. Unfolding and understanding ways the neurons interact in temporal and
spatial domains even including the third dimension is the motto of the experiments being
conducted under controlled environment followed by uncontrolled or day to day normal environment.
Faculty, and researchers may contact us for the collaborative efforts to be made in these directions.
Brain Computer Interface (BCI) is an intelligent system that creates a direct communication path between the human neuronal system and external devices by directing human intentions into control signals. Therefore, BCI systems provide an interface for communication and control capability of an external device to individuals who suffer from neuromuscular disorders caused by amyotrophic lateral sclerosis, spinal cord injury or brain stroke. The key properties of a BCI are: A BCI must be able to record or capture the brain activity directly. It must be capable of providing feedback to the user in real-time. Finally, the system must be able to provide intentional control which enables the user to perform a particular task based on his/her intentions.
Signal processing is another challenging area when it comes to dealing with the brain signals.
The process requires the insight of the probable changes in the human brain in the form of
variation in blood circulation, neuronal impulse generation, way of interactions among different
regions so that appropriate method for measurement of activation state of the human brain can be
chosen. We have limited our efforts on the use of non-invasive ways of capturing brain signals
which may not be very accurate. And these types of (non-invasive) signals are the cumulative
responses of the nerve cells of the human brain human brain and as such may not be accurately
revealing about the dynamics of neuron cells.
More revealing works can be carried out in collaboration with other having requisite infrastructural facilities and experts like neuro surgeons for capturing more accurate neuronal signals.
1. Development of EEG based Intelligent model for anaesthetic level identification.
2. Development of contactless/remote stethoscope for Covid-19 patients.
1. “Identification of depressed persons with AI based classifier using EEG signals”.
P.I. - Dr. Rajdeep Ghosh,
co-P.I. - Prof. Nidul Sinha
Sponsored by: TEQIP III
Fundings: 15.43 Lakhs (1.5M)
1. Analysis of Brain Waves and Development of Intelligent Model for Silent Speech Recognition.
P.I. - Prof. Nidul Sinha,
co-P.I. - Dr. Saroj Kr. Biswas.
Research Scolars: Dr. Rajdeep Ghosh, Mr. Souvik Phadikar.
Sponsored by: Ministry of Communications & Information Technology, Govt. of India
Duration: September 2014 to September 2017.
Fundings: 25 Lakhs (2.5M)
Title: Some Studies On Silent Speech Recognition From Brain Waves.
Submitted by: Dr. Rajddep Ghosh.
Title: Prominent Trials Selection of EEG Data for Motor Imagery Tasks Classification.
Submitted by: Mr. Vikas Kumar.
Supervisor: Prof. Nidul Sinha.
Title: Emotion Recognition From EEG Signals.
Submitted by: Ms. Neetu Singh.
Supervisor: Prof. Nidul Sinha.
Title: Automated Human Emotion Detection From EEG Signals Using Convolutional Neural Network.
Submitted by: Mr. Vishwajeet Singh.
Supervisor: Prof. Nidul Sinha
Co-supervisor: Dr. Badal Soni.
Title: Development of intelligent model using Machine learning tools for brain signal analysis
Submitted by: Ashish Ranjan and Alankrita Sonowal