Title:Progress in Detection of Insomnia Sleep Disorder: A Comprehensive Review
Volume: 22
Issue: 6
Author(s): Md Belal Bin Heyat, Faijan Akhtar, M.A. Ansari, Asif Khan, Fahed Alkahtani, Haroon Khan*Dakun Lai*
Affiliation:
- Department of Pharmacy, Abdul Wali Khan University, Mardan, KPK 23200,Pakistan
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054,China
Keywords:
Insomnia, detection, diagnostic, machine learning, prognostic, pubmed, network visualization, sleep, sleep disorder,
web of science.
Abstract: Lack of adequate sleep is a major source of many harmful diseases related to heart,
brain, psychological changes, high blood pressure, diabetes, weight gain, etc. 40 to 50% of the
world’s population is suffering from poor or inadequate sleep. Insomnia is a sleep disorder in
which an individual complaint of difficulties in starting/continuing sleep at least four weeks regularly.
It is estimated that 70% of heart diseases are generated during insomnia sleep disorder. The
main objective of this study is to determine all work conducted on insomnia detection and to make
a database. We used two procedures including network visualization techniques on two databases
including PubMed and Web of Science to complete this study. We found 169 and 36 previous
publications of insomnia detection in the PubMed and the Web of Science databases, respectively.
We analyzed 10 datasets, 2 databases, 21 genes, and 23 publications with 30105 subjects of insomnia
detection. This work has revealed the future way and gap so far directed on insomnia detection
and has also tried to provide objectives for the future work to be proficient in a scientific and significant
manner.