Design And Implementation Of Sleep Quality Detection Model System Based On Smart Phone

With the rapid development of science and technology,new science and technology have promoted the improvement of people's thinking and material living conditions,and people have gradually paid attention to their own health problems.Sleep plays a vital role in the human body,about one-third of human life is spent in sleep,the quality of sleep directly affects people's health.Problems with sleeping health can lead to many undesirable consequences such as headaches,anxiety,decreased immunity,and so on.Therefore,people want to have a more intuitive understanding of their own sleep quality,which has led to a lot of sleep monitoring devices,from sleep mattresses to smart bracelets,which provide users with an overnight sleep report but need to purchase additional equipment or wear them overnight without guaranteeing a good user experience,and such products mainly rely on the single factor of body movement data for sleep detection,and many details of the sleep process cannot be explored,such as breathing and snoring.With the popularization of mobile Internet and the development of hardware technology,intelligent terminal devices represented by mobile phones have gradually become the standard for everyone.With the support of powerful CPUs,complex computations can also be done on the phone.And nowadays smart phones are equipped with many sensors,which provide the basis for obtaining sleep-related data.The current sleep monitoring equipment has shortcomings in its use due to its drawbacks.In order to solve the shortcomings of traditional sleep monitoring equipment,this paper proposes a smart phone-based sleep quality detection model system.The basic idea is to use the built-in sensors of the smart phone to collect relevant data in the sleep process,and then perform sleep analysis.The data includes body motion data,respiratory data,ambient light data,and so on.For different types of sleep-related physiological events,specific data analysis and feature monitoring mechanisms have been specifically designed in this paper.Then,based on the differences in significant physiological characteristics at different stages of sleep,fuzzy logic theory algorithms are used to structure specific sleep event-specific memberships.The degree function determines sleep staging to predict the most likely sleep state in the current time period.After obtaining the user's sleep-related feature data for the entire night,the user's personal information and ambient light information are included in the calculation range,and an algorithm for determining the user's sleep quality is given.In order to evaluate the effectiveness of the model system,we implemented our model on the iPhone and compared it with the Jawbone UP bracelet product.Through comparative experiments on 20 volunteers from different ages and genders,we foundthat the accuracy rate of time monitoring for light sleep and deep sleep in the model system proposed in this paper reached 81.2% and 78.8%,respectively,fully demonstrating that this model system is suitable for sleep state monitoring.In addition,the model system can also provide snore monitor,to help users find potential safety hazard in time,at the same time provide intelligent wake up function,so that users can be awakened at the most suitable time period to ensure good mental state after waking up.Since the model system does not need to be in direct contact with the user during use,a contactless sleep monitoring method is implemented,and the user is provided with the entire night's sleep data under the premise of accuracy.It provides another way for users to pay more attention to sleep health.