1. The document summarizes an internship report from Ms. Shreya Kapoor who interned at the Design Innovation Centre laboratory under mentor Abhijeet K. Parmar. Her research focused on cognitive science and brain computer interfaces. 2. She surveyed research on the relationship between music, personality, and brain activity. She collected EEG data from subjects and analyzed it using statistical techniques to map electrical activity in the brain related to music. 3. Based on her experience, she proposes expanding her research to use machine learning to develop a personalized music playlist application that could help alter mood by influencing brain wave frequencies, drawing on the known effects of music on the brain.

1. Wednesday, 13 July 2016
Summer Internship in Laboratory Research
Report
1. Name of the student
Ms. Shreya Kapoor, B.Sc. Hons. (Physics) | Miranda House
2. Laboratory Assigned
Design Innovation Centre, CIC, University of Delhi
3. Research Group
Pattern Engineering & Knowledge Discovery
4. Mentor
Abhijeet K. Parmar
5. Broad areas of Research Covered in Lab
Product Design & Development, Affective Computing, AI and Machine Learning,
Computational Creativity, Computer Vision
6. Research Area Assigned
Cognitive Science and Brain Computer Interface
7. Literature Surveyed/Read (Details of Research Papers)
1Anitei, Mihai, Mihaela Chraif, Cristian Vasile, Laura-Elena Năstasă, and Emilia Ionescu.
2015. “INTERNATIONAL CONFERENCE PSIWORLD 2014 - 5th editionFavorite Musical
Styles, Emotional Intelligence and Adolescent’ Personality.” Procedia - Social and
Behavioral Sciences 187: 83–87. doi:http://dx.doi.org/10.1016/j.sbspro.2015.03.016.
1

2. Wednesday, 13 July 2016
2Banerjee, Archi, Shankha Sanyal, Anirban Patranabis, Kaushik Banerjee, Tarit
Guhathakurta, Ranjan Sengupta, Dipak Ghosh, and Partha Ghose. 2016. “Study on Brain
Dynamics by Non Linear Analysis of Music Induced EEG Signals.” Physica A: Statistical
Mechanics and Its Applications 444. Elsevier B.V.: 110–20. doi:10.1016/j.physa.
2015.10.030.
3Wilkins, R W, D A Hodges, P J Laurienti, M Steen, and J H Burdette. 2014. “Network
Science and the Effects of Music Preference on Functional Brain Connectivity: From
Beethoven to Eminem.” Scientific Reports 4 (August). The Author(s): 6130. http://dx.doi.org/
10.1038/srep06130.
(1) Explains how music taste is related to adolescents personality and behaviour.
(2) Is concerned with how EEG signals can help us better understand the effects of music
by mapping electrical activity in various parts of the brain .
(3) Concludes the fact that same neural network is activated for different people when they
listen to the same music because their likes and dislikes are different , so depending upon
the person different parts of the brain are activated for same piece of music.
8. Hands-on-Experience Undertaken
1.Identification of subjects for the research and gaining consent for participation.
2.Collection of data using API (application processing interface)
3.Interpreting and analysing data using statistical techniques (correlation coefficients etc.)
4.Working with python libraries for scientific computing.
5. Extracting information from EEG data.
6. Visualising EEG in the form of waveforms by using MATLAB software.
7.Applying Non-Linear regression techniques and modelling the EEG waveform.
8. Assess models as tools for predictive analysis.
9. Other responsibilities carried out
N/A
10. Learnings
1.Reading Scientific Journals and interpreting them.
2.Using Python libraries for data handling and file handling.
3.Using MATLAB software.
2

3. Wednesday, 13 July 2016
4.Developing reasoning skills to substantiate findings using mathematical tools.
5.Designing network models etc.
6. Writing scientific reports.
11. If you are given the opportunity to expand your research based on the experience
during internship, what would it be?
I would like to expand my research based upon the experience during the internship
towards machine learning and how machines can provide us answers to our daily
problems with optimal solutions. As I have assessed the correlations of music with
personality, perhaps an application can be designed in order to provide a personalised
playlist which helps a person alleviate moods. Similar type of technique is also used
musical therapy to treat schizophrenia and epilepsy. Music is said to alter brain wave
frequency and we could use this knowledge to our advantage by using music to increase
the dominance of a particular frequency band , my research would be identifying such
correlations of music and brain waves to use music to our advantage and accordingly
help us achieve the desired mental state and eventually increase our efficiency. The
questions I want to be answered if a sense of music is a different sense altogether and
gain knowledge about this sense because generally a person spends about 10-15%of
his/her time listening to music. Humans are making every activity beneficial and prolific
and it would be great to discover the productivity in listening to music.
(Shreya Kapoor)
Signature of Student
Observations/Remarks of the Mentor
1. Always at work and on time.
2. Never misses work without prior approval and appropriate notification.
3. Enthusiastic, energetic and displays positive behaviour.
4. Adapted to new systems and processes well and seeks out training to enhance knowledge,
skills and abilities.
5. Demonstrated excellent oral and written communication skills.
6. Always offered ideas to solve problems based on good information and sound judgment.
7. Is able to troubleshoot and solves all work related problems quickly and efficiently.
3