BigPsy: a big data framework to support psycho-informatics

Abstract

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.