This product is a depression screening system designed for potential depression patients in the population, mainly through sleep signals to detect and screen depression. The following will describe the product in terms of design, use and advantages of the work. 1. Design method This product adopts the method of convolutional neural network, deep learning construction model and system construction to achieve the ultimate goal of the depression feature screening model based on the multi-channel sleep staging model, which is divided into the following blocks (details can be found in the work description material): (1) Multi-channel EEG sleep staging based on convolutional neural network (2) Construction of depression feature screening model based on deep learning (3) Construction of depression feature screening system based on project algorithm 2. Method of use Open the sleep monitoring system, before sleep monitoring, you need to wear the EEG ring before you can read the EEG data during sleep. First, the Bluetooth receiver of the EEG ring is connected to the computer, the switch of the EEG ring is turned on, and the EEG ring is worn on the head. After wearing, open the sleep monitoring interface. Click the Start Sleep button, the system starts to collect EEG signals, the implementation of staging, the website is built by the Django framework, in the process of real-time sleep staging using dual-thread mechanism. Thread one real-time transfer the brain electrical signal obtained by the brain electrical ring to local storage, thread two uses the trained CNN-BiLSTM model for staging, and finally through the PC-DRN network to achieve the screening classification of depression. During sleep, the user can personalize the selection of sleep-aid music, including low-frequency sleep-aid music, including natural sounds, sleep-aid sounds and bedtime stories, and induce the human body to enter a sleep state by simulating the brain wave signals in the relaxed state of the brain. After the start of sleep, the system will update the sleep state every 150s according to the real-time change of sleep, so as to better record the sleep data. When the user wakes up, he can click the end sleep button, the system stops monitoring the user's EEG signal, and clicks the sleep report button. At this time, the sleep situation of the user last night can be viewed. In the sleep report interface, you can view the user's sleep changes during the night's monitoring, and the system will judge the possibility of depression based on the sleep situation. Click the View More button to view the user's historical sleep details, including sleep duration, sleep duration, light sleep duration, deep sleep duration, rapid eye movement duration, deep sleep ratio, and sleep score, so as to better highlight the difference between sleep physiological signals between depression patients and normal people, improve classification accuracy, and enable users to have a good understanding of their mental state. 3. Advantages of works At present, the diagnosis of depression is mainly based on clinical interviews and psychiatric questionnaires, which lack objective criteria. The examination efficiency of this kind of mental and psychological related diseases is low, the workload is large, and the accuracy rate of diagnosis is very low due to subjective factors. And there is a shortage of professional psychiatrists in China, and the level of diagnosis and treatment of doctors in various hospitals is uneven, which leads to a high probability of missed diagnosis and misdiagnosis of patients with depression. This product can automatically and quickly learn multiple levels of abstraction, representation, and information from the data set, does not require a large amount of prior knowledge to guide the training process, and can imitate humans to provide effective information or make decisions. It can help users more accurately and quickly predict the risk of diseases, so that these diseases can be detected earlier. Therefore, through this accurate and efficient diagnosis, patients with depression can take treatment measures as soon as possible, and reduce the pain caused by depression to patients and the burden on society.