Sleep disorders management is paramount for maintaining overall well-being. In response to the limitations of traditional approaches, we present an innovative solution that leverages the synergy of Internet of Medical Things (IoMT) and Gated Recurrent Unit (GRU)-based data analytics, leading to smart sleep monitoring that effectively addresses sleep disorders. The conventional methods of sleep monitoring often fall short due to their inability to provide continuous monitoring and personalized insights tailored to individual needs.Our proposed work offers a comprehensive solution to these challenges by introducing an IoMT-enabled system. This system integrates wearable devices and sensors to continuously gather and transmit sleep-related data in real-time. The uniqueness of our approach lies in the integration of GRU, a sophisticated deep learning algorithm, which excels at capturing and analyzing sequential data patterns. GRU enables us to comprehensively analyze the collected sleep data, accurately classifying sleep stages, detecting anomalies, and predicting potential disruptions. To validate the effectiveness of our IoMT and GRU-based approach, We carried out comprehensive trials with individuals who had been diagnosed with a range of sleep disorders, encompassing conditions such as insomnia, obstructive sleep apnea, and idiopathic narcolepsy. The results demonstrate an impressive average sleep efficiency improvement of 18%. This enhancement is achieved through the generation of personalized interventions that stem from the deep insights derived from the GRU analysis. Our approach thus not only improves sleep efficiency but also offers tailored solutions that address specific sleep-related challenges faced by individuals. The real-time nature of IoMT, combined with the advanced pattern recognition capabilities of GRU, equips individuals with actionable insights, personalized recommendations, and effective solutions, thus significantly enhancing the quality of sleep and overall well-being.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Smart Sleep Monitoring: IoMT and GRU for Effective Sleep Disorders Management


    Contributors:


    Publication date :

    2023-11-22


    Size :

    377555 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Short sleep duration, sleep disorders, and traffic accidents

    Yoko Komada / Shoichi Asaoka / Takashi Abe et al. | DOAJ | 2013

    Free access

    SLEEP MONITORING

    Beckingham, Thomas | TIBKAT | 2020


    Sleep monitoring system

    BENSON RONALD STUART / DENOMME RYAN CAMERON | European Patent Office | 2019

    Free access

    Sleep monitoring system

    BENSON RONALD STUART / DENOMME RYAN CAMERON | European Patent Office | 2020

    Free access