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相关论文: A Review of the Non-Invasive Techniques for Monito…

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Sleep is an essential and vital element of a person life and health that helps to refresh and recharge the mind and body of a person. The quality of sleep is very important in every person lifestyle, removing various diseases. Bad sleep is…

其他计算机科学 · 计算机科学 2022-09-13 Abdur Rab Dhruba , Kazi Nabiul Alam , Md Shakib Khan , Sami Bourouis , Mohammad Monirujjaman Khan

Sleep behaviour and in-bed movements contain rich information on the neurophysiological health of people, and have a direct link to the general well-being and quality of life. Standard clinical practices rely on polysomnography for sleep…

信号处理 · 电气工程与系统科学 2023-01-10 Omar Elnaggar , Roselina Arelhi , Frans Coenen , Andrew Hopkinson , Lyndon Mason , Paolo Paoletti

Sleep is a crucial aspect of our overall health and well-being. It plays a vital role in regulating our mental and physical health, impacting our mood, memory, and cognitive function to our physical resilience and immune system. The…

Sleep has a profound influence on the physiology of body systems and biological processes. Molecular studies have shown circadian-regulated shifts in protein expression patterns across human tissues, further emphasizing the unique…

定量方法 · 定量生物学 2021-02-11 Nitai Bar , Jonathan A. Sobel , Thomas Penzel , Yosi Shamay , Joachim A. Behar

Sleep monitoring provides valuable insights into the general health of an individual and helps in the diagnostic of sleep-derived illnesses. Polysomnography, is considered the gold standard for such task. However, it is very unwieldy and…

This paper proposes a practical approach for automatic sleep stage classification based on a multi-level feature learning framework and Recurrent Neural Network (RNN) classifier using heart rate and wrist actigraphy derived from a wearable…

机器学习 · 统计学 2017-11-03 Xin Zhang , Weixuan Kou , Eric I-Chao Chang , He Gao , Yubo Fan , Yan Xu

Sleep plays a vital role in our physical, cognitive, and psychological well-being. Despite its importance, long-term monitoring of personalized sleep quality (SQ) in real-world contexts is still challenging. Many sleep researches are still…

计算机与社会 · 计算机科学 2022-11-24 Wenbin Gan , Minh-Son Dao , Koji Zettsu

Accurate sleep stage classification is crucial for diagnosing sleep disorders and evaluating sleep quality. While polysomnography (PSG) remains the gold standard, photoplethysmography (PPG) is more practical due to its affordability and…

Sleep and mental health are highly related concepts, and it is an important research and clinical priority to understand their interactions. In-bed sensors using ballistocardiography provide the possibility of unobtrusive measurements of…

信号处理 · 电气工程与系统科学 2023-11-23 Samuel Askjer , Kim Mathiasen , Ali Amidi , Christine Parsons , Nicolai Ladegaard

Sleep disorder diagnosis relies on the analysis of polysomnography (PSG) records. As a preliminary step of this examination, sleep stages are systematically determined. In practice, sleep stage classification relies on the visual inspection…

机器学习 · 统计学 2021-06-21 Antoine Guillot , Valentin Thorey

The ability to assess sleep at home, capture sleep stages, and detect the occurrence of apnea (without on-body sensors) simply by analyzing the radio waves bouncing off people's bodies while they sleep is quite powerful. Such a capability…

Recently, growing health awareness, novel methods allow individuals to monitor sleep at home. Utilizing sleep sounds offers advantages over conventional methods like smartwatches, being non-intrusive, and capable of detecting various…

机器学习 · 计算机科学 2024-10-18 Shintaro Tamai , Masayuki Numao , Ken-ichi Fukui

Accurate sleep stage classification is essential for diagnosing sleep disorders, particularly in aging populations. While traditional polysomnography (PSG) relies on electroencephalography (EEG) as the gold standard, its complexity and need…

计算机视觉与模式识别 · 计算机科学 2025-06-10 Olivier Papillon , Rafik Goubran , James Green , Julien Larivière-Chartier , Caitlin Higginson , Frank Knoefel , Rébecca Robillard

Sleep staging is essential for diagnosing sleep disorders and assessing neurological health. Existing automatic methods typically extract features from complex polysomnography (PSG) signals and train domain-specific models, which often lack…

信号处理 · 电气工程与系统科学 2025-09-30 Jianheng Zhou , Chenyu Liu , Jinan Zhou , Yi Ding , Yang Liu , Haoran Luo , Ziyu Jia , Xinliang Zhou

Study Objectives: Polysomnography (PSG) currently serves as the benchmark for evaluating sleep disorders. Its discomfort makes long-term monitoring unfeasible, leading to bias in sleep quality assessment. Hence, less invasive,…

As sleep disorders are becoming more prevalent there is an urgent need to classify sleep stages in a less disturbing way.In particular, sleep-stage classification using simple sensors, such as single-channel electroencephalography (EEG),…

信号处理 · 电气工程与系统科学 2023-02-27 Iksoo Choi , Wonyong Sung

Polysomnography (PSG), the gold standard test for sleep analysis, generates vast amounts of multimodal clinical data, presenting an opportunity to leverage self-supervised representation learning (SSRL) for pre-training foundation models to…

The availability of commercial wearable trackers equipped with features to monitor sleep duration and quality has enabled more useful sleep health monitoring applications and analyses. However, much research has reported the challenge of…

信号处理 · 电气工程与系统科学 2022-11-17 Camellia Zakaria , Gizem Yilmaz , Priyanka Mammen , Michael Chee , Prashant Shenoy , Rajesh Balan

Sleep apnea is a serious and severely under-diagnosed sleep-related respiration disorder characterized by repeated disrupted breathing events during sleep. It is diagnosed via polysomnography which is an expensive test conducted in a sleep…

Sleep is essential for good health throughout our lives, yet studying its dynamics requires manual sleep staging, a labor-intensive step in sleep research and clinical care. Across centers, polysomnography (PSG) recordings are traditionally…

机器学习 · 计算机科学 2025-12-17 Niklas Grieger , Jannik Raskob , Siamak Mehrkanoon , Stephan Bialonski