This review shows the various sleep related disorders including insomnia, parasomnia, hypersomnia significantly impacting the health, and overall quality life of an individual, early detection and effective management of such disorders are crucial, yet there are many traditional diagnostic measures such as polysomnography often have drawbacks like limited accessibility and are not cost effective for the people. There are many advancements in technologies like the development of innovative sleep detection methods such as wearable devices, machine learning models, easy to use interface mobile apps. The focus of this paper is to check on latest developments in sleep disorder detection, focusing on the various wearable and non-contact models, also evaluating the accuracy, reliability of these various detection models. Additionally, the key challenges and limitations are also discussed in this paper and the need for customized diagnostic methods, checking on the potential for these technologies to be applied for future uses and their inclusion in routine healthcare.