AI-enabled Wi-Fi Network to Estimate Human Sleep Quality based on Intensity of Movements

Due to increase in number of wireless devices for the development of smarter spaces such as offices, homes etc., Wi-Fi devices are available as off-the-shelf sensing devices. Researchers are looking for various sensing applications which can make reuse of already installed devices to make the human life easy. Wireless human sensing (WHS) has evolved as a field of study of interaction between the human body and on-going wireless communication to extract various human activities, such as sleep, without attaching any sensor to the body. Sleep is an important part of human life and a quality sleep is essential for healthy being. Due to various sleep disorders and physiological conditions quality sleep is obstructed. It is essential to monitor the sleep to estimate quality of the sleep so the remedial measures can be taken thereof. The movements viz. of limbs turns and rollovers made by the subject on the bed during the sleep can be observed with the proposed method of sleep monitoring and a corresponding movement score is created. This is for the first time when the sleep quality is being estimated on the basis of this score by using WHS. We present here optimistic prelim results of the sleep quality estimation based on rollovers through an Artificial Intelligence enabled Wi-Fi network.