Sleep Monitoring and Sleep-Aid Intervention Methods: A Review

作者：Chunhua He, Xiaoman Wang, Yangxing Wen, Shuibin Liu, Zewen Fang, Heng Wu, Maojin Liang, Songqing Deng · 发表于：IEEE Internet of Things Journal · 年份：2025 · DOI：10.1109/jiot.2025.3582901 · 被引用次数：5 · 研究领域：Sleep and related disorders、Sleep and Wakefulness Research

Sleep disorders and the associated physical and mental illnesses are becoming increasingly prominent, affecting people’s quality of life and work-learning efficiency. Accurate sleep monitoring and efficient sleep-aid interventions are still world challenges. In recent years, there have been significant advances in monitoring the in-and-out-of-bed state, heart rate, HRV, respiratory rate, snoring event, body movement, and sleep stage, including the development and use of multimodal sensors for data acquisition and the adoption of AI techniques such as feature extraction and pattern recognition for sleep parameter identification. Common sleep-aid methods can be categorized into two main groups: pharmacologic and non-pharmacologic. However, in the long run, it seems that the effect of a single sleepaid method is limited, and the integration of multiple sleep-aid intervention methods is the trend. Microneedle sleep-aid techniques that integrate herbal sleep aids, acupoint acupuncture sleep aids, and transcranial current stimulation sleep aids have emerged. However, there is a lack of summarization and review of the latest research on sleep monitoring and sleep interventions in recent years, and this paper hopes to point out the limitations of the current technology and suggest under-explored research paths through the investigation of the latest studies. In this paper, relevant studies in the last 5-10 years have been well researched, and expertise in neuroscience, clinical medic...