Development of an Intelligent Sleep Monitoring System Based on the Integration of Artificial Intelligence and Digital Medical Technologies

In the context of modern digital society, the development of healthcare systems requires the introduction of innovative technological solutions. One of the most promising directions in medical science is the integration of artificial intelligence, the Internet of Medical Things (IoMT), and blockchain technologies. Particular attention is paid to sleep quality monitoring, as sleep plays a fundamental role in maintaining physiological stability and psychological well-being.

This scientific research is being conducted with the participation of the scientific community of Al-Farabi Kazakh National University, where developments in digital medicine and intelligent data analysis systems are actively carried out. The scientific potential of the university and the experience of research teams create favorable conditions for advancing innovative medical technologies. The project is aimed at improving diagnostic accuracy and enhancing the overall health status of the population.

Sleep disorders are among the most common problems in modern society. Chronic sleep deprivation may increase the risk of cardiovascular diseases and negatively affect cognitive functions. Therefore, continuous sleep monitoring and intelligent structural analysis of sleep patterns have significant scientific and practical importance.

The main objective of the project is the development of an intelligent system capable of collecting physiological signals in real time. Using Internet of Medical Things technologies, the system monitors key physiological indicators, including heart rate, blood oxygen saturation level (SpO2), heart rate variability (HRV), electroencephalographic activity (EEG), respiratory rate, and body temperature.

Artificial intelligence algorithms are applied to automatically analyze and predict sleep quality. Graph Attention Network (GAT) technology is used to identify significant relationships between physiological signals. The Denoising Diffusion Probabilistic Model (DDPM) method is implemented to reduce random noise in the data and improve analytical processing quality.

To predict sleep disorders, Temporal Graph Networks (TGN) and Neural Ordinary Differential Equation (Neural ODE) models are being developed. These algorithms allow modeling the temporal dynamics of physiological parameters. Analysis of sleep phase evolution increases the possibility of early detection of sleep apnea syndrome and insomnia.

Data security is one of the key components of the study. The use of blockchain technology ensures the immutability and confidentiality of medical information. The decentralized data storage architecture is aimed at protecting patient personal data. Smart contracts regulate access to medical information.

The diagnostic intelligent platform is based on capsule neural network and hypernetwork architectures. These models allow the analysis of complex spatial structures of physiological signals. Individual biometric characteristics of each patient are considered, enabling the development of personalized medical recommendations.

As a result of the project implementation, an interactive platform will be created to provide users with personalized recommendations for improving sleep quality. The push notification system will inform users about changes in their health condition in real time. Through the mobile application, users will be able to monitor sleep patterns and receive medical reports.

The research is oriented not only toward theoretical scientific problems but also toward practical application. The proposed technology can be used in medical institutions, telemedicine systems, and technology companies operating in the healthcare sector. The remote monitoring system is particularly effective for regions with limited access to medical services.

The scientific research is conducted in accordance with international standards. Scientific ethics principles are strictly followed during data processing, and the obtained results are protected by copyright. Patent registration and protection of intellectual property objects are also planned.

The project contributes to the development of digital medicine in Kazakhstan. The integration of artificial intelligence, IoT, and blockchain technologies into medical systems creates new opportunities for the formation of advanced scientific research directions.

The development of an intelligent sleep monitoring system represents a transition to a new stage in medical diagnostics and disease prevention. The combination of digital technologies and medicine contributes to improving research efficiency, enhancing healthcare infrastructure, and promoting social well-being.