Developed a ML Algorithm on EEG signals to extend Russell’s 2-D model on emotions to a 3-D model. Dataset used for training and testing purposes is DEAP dataset. Research paper accepted at 2nd International Conference on Computer Science and Artificial Intelligence (CSAI 2018), Shenzhen, China.

An Android Application Developed which takes as input the real time EEG signals from the brain and provides different kinds of Neurofeedback -

• Subject can select a Text file to read and based on the attention value of the subject the opacity level of the selected content changes. That is, the content is clearly visible only if the subject is in a High Attention state. As the attention level drops, the content becomes unclear to read thus making the reader aware of the drop in their attention.
• This application can also be used to improve the attention value of the subject. Initially, a subject is made to read some content and the attention level is recorded. Then, the participants are made to play a Pattern Backward-Retrace Android Brain Game called NeuroNation and created by NeuroNation. This game is a psychologically approved tool to simulate Brain regions pertaining to Attention. Following the game, another prose is selected as content and the attention values are recorded. A neurofeedback showing the comparison between the two different attention values is shown in the form of a graph.

Developed a Web interface for people to chat. Users first have to create an account. Following which they have to create a chat room or join an existing chat room. Chat room is like a group where all the members of that room form a group and can chat only within that room. A URL can be generated by members of the chat room and can be sent to other people as an invitation to join the chat room. Multiple chat rooms can be generated simultaneously. Once the user is done chatting, they may logout off their account. On logging into their respective accounts again, the user can see the chat in the chat room they're a part of and continue chatting.

During the winter 2016 Research Internship at LANS Lab, Delhi Technological University; I attended a workshop on Brain Science and Technology at Indian Institute of Technology, Delhi. Here I learned about Brain Science and various technologies used to understand Brain Science. Following which I developed a Machine Learning Algorithm to predict if a person is in a High Attention state or a Low Attention State. Data was collected using the Neurosky Mindwave EEG Headset from various people in different environments - While Solving math problems, Listening to Music, During meditation etc. For Attention prediction I used a SVM classifier as various research papers also suggested the same.

During the summer 2016 Training at HCL, Delhi; I learned about Embedded Systems and developed 3 Projects as part of the training task - Fire Detector being one of the three. Circuit design was done using Proteus software initially which was then implemented on the Hardware. The coding for the detector was done using C language in the Atmel Studio software. On detection of very high temperature, the alarm would be set on, alarming everyone around of fire in vicinity.

During the summer 2016 Training at HCL, Delhi; I learned about Embedded Systems and developed 3 Projects as part of the training task - Heart Attack Detector being one of the three. Circuit design was done using Proteus software initially which was then implemented on the Hardware. The coding for the detector was done using C++ language in the Atmel Studio software. GSM technology was also used. The detector would notify the Emergency contact numbers saved in the device when a Heart Attack is detected in a person wearing the device.

During the summer 2016 Training at HCL, Delhi; I learned about Embedded Systems and developed 3 Projects as part of the training task - Pulse Detector being one of the three. Circuit design was done using Proteus software initially which was then implemented on the Hardware. The coding for the detector was done using C language in the Atmel Studio software. The detector would display the real time pulse rate of the subject on a LCD screen attached to the detector.

Developed a web page to update student records of those staying in Hostel. New student records can be added, student details can be edited and student records can also be removed. Certain parameter checks were also deployed to check if the details inputted aren't incorrect.

An Android application developed to control the Flashlight of the mobile device by turning it on and off.