SmartHypnos: An Android application for low-cost sleep self-monitoring and personalized recommendation generation

Abstract

Background and Objective:

Sleep is an essential biological function that is critical for a healthy and fulfilling life. Available sleep quality assessment tools contain long questionnaires covering a long period of time, not taking into account daily physical activity patterns and individual lifestyles.

Methods:

In this paper we present SmartHypnos, an Android application that supports low-end devices. It enables users to report their sleep quality, monitor their physical activity and exercise intensity and gain personalized recommendations aimed at increasing sleep quality. The application functionalities are implemented through sleep quality evaluation questions, passive step counter, efficient data storage and Personal data are stored locally protecting user privacy. All these are integrated into a single interface that requires a single device, is of low learning difficulty and easy to use. SmartHypnos was evaluated during a pilot study that involved 48 adults (ages 18-50) that used the application for seven days and subsequently submitted their data, possible through the interface directly, and evaluated the application through an appropriate questionnaire.

Results:

SmartHypnos was rated positively by users, especially it terms of learnability, ease of use and stability, with a mean score over 8. Task completion time and ease, simplicity, user comfort and recommendation utility were scored with a mean over 7. The correlation between the features extracted were in accordance to prior works.

Conclusions:

SmartHypnos has the potential to become a sleep monitoring and intervention tool readily available to the general public, including vulnerable populations of low socio-economic status.