: 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. The 40 to 50 % of the world’s population is suffering from poor or inadequate sleep. Insomnia is a sleep disorder in which individual complaint of difficulties in starting/continuing sleep at least four weeks regularly. It is estimated that 70% of the heart diseases are generated during insomnia sleep disorder. The main objective of this study to determine the 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.

Globally, the aging and the lifestyle lead to rabidly increment of the number of type two diabetes (T2D) patients. Critically, T2D considers as one of the most challenging healthcare issue. Importantly, physical activity (PA) plays a vital role of improving glycemic control T2D. However, daily monitoring of T2D using wearable devices/ sensors have a crucial role to monitor glucose levels in the blood. Nowadays, daily physical activity (PA) and exercises have been used to manage T2D. The main contribution of the proposed study is to review the literature about managing and monitoring T2D with daily PA through wearable devices and sensors. Finally, challenges and future trends are also highlighted.