BigPsy: a big data framework to support psycho-informatics
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
| Autors principals: | , , , , |
|---|---|
| Altres autors: | |
| Format: | Thesis |
| Idioma: | English |
| Publicat: |
Brac University
2021
|
| Matèries: | |
| Accés en línia: | http://hdl.handle.net/10361/14978 |
| id |
10361-14978 |
|---|---|
| record_format |
dspace |
| spelling |
10361-149782022-01-26T10:13:14Z BigPsy: a big data framework to support psycho-informatics Muizz, Rashik Al Uddin, Md. Sakib Sakib, Mirza Md. Nazmus Islam, S.M.Fahmidul Ahmed, Nourin Akhond, Mostafijur Rahman Khatun, Afrina Department of Computer Science and Engineering, Brac University Psychology Mental Health Depression Big Data Big Data Storage Psycho-informatics Behavior Psychological Sleep Analysis Psychology This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 38-41). Human conduct and state of mind are fundamental pieces of both psychiatry and psychological research. A person’s mental state can be determined by analyzing his behavioral patterns which contain subtle signals. This paper outlines the technical vision, sketches the signals that can be detected and illustrates the tremendous benefits over traditional methods of psychometrics. In particular, it suggests tracking user behavior with smartphones, a particularly rich and intimate source of data. The proposed method will help researchers and psychologists to study human minds more efficiently. This study also aims to dissect human conduct in detail with the help of large information by estimating the seriousness of an individual’s downturn and web fixation. Because of this kind of excessive behavior, a person experiences depression, anxiety, insomnia and some other deteriorated mental health conditions. It is hard to see how genuine it is as the methods for evaluating mental health are not entirely solid. Despite, everything analysts rely upon psychometric tests, studies and perceptions, which face difficulties to address the issues of each distinctive individual. In the paper, the ordinary exercises can be recorded with the help of cell phones or computers. It will gather information on a finer scale and search for transient action designs. Additionally, the information will be collected in an electronic structure and be stored in Big Data Storage. This information-driven system will turn out to be less tedious and less expensive than conventional strategies for both specialists and patients. The most significant challenge of this research is dealing with streaming data. It will be stored in the big data storage and then, using machine learning with the useful data, a sample feature such as sleep analysis can be created. Besides, the stigma related to mental health is also a matter of concern to know more about their mental health condition. In addition, it will create another sub-zone of psychometrics which can make a new research area in the field of psychology by exclusively examining data. Finally, the proposed paper will show a portion of the moral issues natural to Large Information advancements. Therefore, the proposed approach might incite the methodological move since the arrival of psychiatry or psychological research. Rashik Al Muizz Md. Sakib Uddin Mirza Md. Nazmus Sakib S.M.Fahmidul Islam Nourin Ahmed B. Computer Science 2021-09-06T12:17:36Z 2021-09-06T12:17:36Z 2021 2021-06 Thesis ID 17101158 ID 16201035 ID 17101144 ID 17101161 ID 17101022 http://hdl.handle.net/10361/14978 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 41 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Psychology Mental Health Depression Big Data Big Data Storage Psycho-informatics Behavior Psychological Sleep Analysis Psychology |
| spellingShingle |
Psychology Mental Health Depression Big Data Big Data Storage Psycho-informatics Behavior Psychological Sleep Analysis Psychology Muizz, Rashik Al Uddin, Md. Sakib Sakib, Mirza Md. Nazmus Islam, S.M.Fahmidul Ahmed, Nourin BigPsy: a big data framework to support psycho-informatics |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
| author2 |
Akhond, Mostafijur Rahman |
| author_facet |
Akhond, Mostafijur Rahman Muizz, Rashik Al Uddin, Md. Sakib Sakib, Mirza Md. Nazmus Islam, S.M.Fahmidul Ahmed, Nourin |
| format |
Thesis |
| author |
Muizz, Rashik Al Uddin, Md. Sakib Sakib, Mirza Md. Nazmus Islam, S.M.Fahmidul Ahmed, Nourin |
| author_sort |
Muizz, Rashik Al |
| title |
BigPsy: a big data framework to support psycho-informatics |
| title_short |
BigPsy: a big data framework to support psycho-informatics |
| title_full |
BigPsy: a big data framework to support psycho-informatics |
| title_fullStr |
BigPsy: a big data framework to support psycho-informatics |
| title_full_unstemmed |
BigPsy: a big data framework to support psycho-informatics |
| title_sort |
bigpsy: a big data framework to support psycho-informatics |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14978 |
| work_keys_str_mv |
AT muizzrashikal bigpsyabigdataframeworktosupportpsychoinformatics AT uddinmdsakib bigpsyabigdataframeworktosupportpsychoinformatics AT sakibmirzamdnazmus bigpsyabigdataframeworktosupportpsychoinformatics AT islamsmfahmidul bigpsyabigdataframeworktosupportpsychoinformatics AT ahmednourin bigpsyabigdataframeworktosupportpsychoinformatics |
| _version_ |
1814307998198136832 |