Sleep Quality Monitoring Research Articles

Fabric and Fiber-Integrated, Washable Hydrogel Electrodes for Clinically Accurate Sleep Monitoring in-Home

Longitudinal tracking of sleep metrics is important for detecting and managing various diseases, spanning cardiorespiratory disorders to dementia. However, at present, sleep monitoring primarily occurs in specialized medical facilities that are not conducive to longterm studies. In-home solutions either compromise user comfort or signal accuracy in tracking sleep variables and have not yet provided reliable longitudinal data. We believe that human-centered design of multimodal, low-form-factor, comfortable sensing systems is needed for this increasingly-important area of preventative health monitoring. Our lab developed a suite of fabric-based and/or garment-integrated sensors and sensing modalities that accurately and reliably extract important sleep metrics, such as posture, cardiorespiratory signals, eye movement and brain activity, over the course of an eight-hour sleep session. Our garment-integrated sensing arrays do not require a medical professional for on-body positioning, maintain their function independent of sizing and fit on individual users, and can be laundered or cleaned with antibacterial wipes without compromising its varied sensing elements. Here, we describe one of these two key sensors, a fabric or fiber-based electrochemical hydrogel electrode that enables wearable biopotential monitoring, including electrocardiography (ECG), eletrooculography (EOG) and electroencephalography (EEG), from which the aforementioned sleep metrics can be recorded and quantified with clinical precision and accuracy. The hydrogel is fabricated as a coating on either commodity fabrics or threads using a low-temperature reactive deposition process, termed photoinitiated chemical vapor deposition (piCVD), during which hydrogel monomers react with a photoinitator in the vapor phase to create a polymeric hydrogel coating directly on the surface of fabrics or threads that have been temporarily surface modified with a skin-safe electrolyte gel. The resulting composite hydrogel coating isolated from this operation is ionically conductive, can be reversibly swelled in water and dried without losing ionic conductivity, and transduces the ionic signals (fluxes) experienced by the body into an electrical signal that can be captured by any commercial ECG, EOG or EEG monitoring instrument. An array of these fabric or thread-based hydrogel electrodes can be integrated into readily-available garments using simple cut-sew techniques and these garments can then be worn throughout the night to effect continuous ECG, EOG and EEG monitoring at home. Design elements of a custom-made circuit board that allows simultaneous capture of these signals will be described. Results from an ongoing user study of >50 adults will be presented to validate the clinical precision and accuracy of these garment sensor for sleep quality monitoring.

A Review of Patient Bed Sensors for Monitoring of Vital Signs.

The analysis of biomedical signals is a very challenging task. This review paper is focused on the presentation of various methods where biomedical data, in particular vital signs, could be monitored using sensors mounted to beds. The presented methods to monitor vital signs include those combined with optical fibers, camera systems, pressure sensors, or other sensors, which may provide more efficient patient bed monitoring results. This work also covers the aspects of interference occurrence in the above-mentioned signals and sleep quality monitoring, which play a very important role in the analysis of biomedical signals and the choice of appropriate signal-processing methods. The provided information will help various researchers to understand the importance of vital sign monitoring and will be a thorough and up-to-date summary of these methods. It will also be a foundation for further enhancement of these methods.

The Association Between Heart Rate Variability and Sleep Quality - a Narrative Review

Introduction Heart rate variability (HRV) serves as a non-invasive marker to assess autonomic nervous system (ANS) modulation on cardiac rhythm. Its link with sleep quality, particularly in the context of insomnia, posits HRV as a potential indicator of autonomic state variations during sleep disturbances. The prevalence of insomnia, affecting up to 20% of the general population, emphasizes the need to understand its extensive impact. Material and Methods For this review - 41 relevant titles from 1985 to 2024 were selected Analysis of the Literature: Recent studies highlight a bidirectional relationship between insomnia and ANS function, with increased sympathetic activity indicated by physiological and subjective measures in individuals with insomnia. The role of medications like beta-blockers in disrupting ANS and leading to sleep deprivation further connects measurable and perceived aspects of sleep quality, impacting health negatively. Moreover, HRV's application has expanded beyond professional athletics to daily activity and sleep quality monitoring by the general population, emphasizing its potential in evaluating stress and training intensity. Conclusion: The complex interplay between HRV, insomnia, and health outcomes necessitates further research. However, integrating HRV measurements into clinical and everyday monitoring may offer a promising avenue for improving sleep disorder management and enhancing quality of life.

The effects of Tai Chi exercise on sleep quality among the elderly: a study based on polysomnographic monitoring.

Sleep disorders contribute to an increased risk of depression, cardiovascular issues, and various other diseases among older individuals. Consequently, enhancing the sleep quality of this demographic population has become a pressing concern. The objective of this study was to investigate the influence of an 8-week Tai Chi exercise intervention in the sleep quality of older adults. Sixty individuals aged 60 years and above, recruited from the community around Southwest University in Beibei District, Chongqing City, were randomly assigned to either a control group (30 participants) or an intervention group (30 participants). The control group adhered to their normal daily routines during the 8-week experimental period, while the intervention group engaged in a 60-min Tai Chi practice three times a week for 8 weeks. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI), and the Epworth Sleepiness Scale (ESS). Additionally, the Polysomnographic Sleep Quality Monitoring System (PSG) was employed to monitor the sleep process before and after the Tai Chi intervention. After the experiment, significant differences were observed in PSQI and IEI scores between the intervention and control groups (p < 0.05). In the experimental group, the pre-post comparisons revealed a significant increase in time spent in bed (p < 0.05), total sleep time (p < 0.05), and non-REM sleep stage 2 (p < 0.05). The findings indicate that Tai Chi exercise may improve subjective reported sleep quality. In addition, Tai Chi exercise may alleviate general drowsiness, extend sleep duration, and optimize the sleep process and structure. Consequently, Tai Chi exercise may be a suitable exercise to improve sleep quality in older individuals.

Comparative analysis of sleep parameters and structures derived from wearable flexible electrode sleep patches and polysomnography in young adults.

Polysomnography (PSG) is the gold standard for clinical sleep monitoring, but its cost, discomfort, and limited suitability for continuous use present challenges. The flexible electrode sleep patch (FESP) emerges as an economically viable and patient-friendly solution, offering lightweight, simple operation, and self-applicable. Nevertheless, its utilization in young individuals remains uncertain. The objective of this study was to compare sleep data obtained by FESP and PSG in healthy young individuals and analyze agreement for sleep parameters and structure classification. Overnight monitoring with FESP and PSG recordings in 48 participants (mean age: 23 yr) was done. Correlation analysis, Bland-Altman plots, and Cohen's kappa coefficient assessed consistency. Sensitivity, specificity, and predictive values compared classification against PSG. FESP showed strong correlation and consistency with PSG for sleep monitoring. Bland-Altman plots indicated small errors and high consistency. Kappa values (0.70-0.84) suggested substantial agreement for sleep stage classification. Pearson correlation coefficient values for sleep stages (0.75-0.88) and sleep parameters (0.80-0.96) confirm that FESP has a strong application. Intraclass correlation coefficient yielded values between 0.65 and 0.97. In addition, FESP demonstrated an impressive accuracy range of 84.12-93.47% for sleep stage classification. The FESP also features a wearable self-test program with an error rate of no more than 8% for both deep sleep and wake. In young adults, FESP demonstrated reliable monitoring capabilities comparable to PSG. With its low cost and user-friendly design, FESP is a potential alternative for portable sleep assessment in clinical and research applications. Further studies involving larger populations are needed to validate its diagnostic potential.NEW & NOTEWORTHY By comparison with PSG, this study confirmed the reliability of an efficient, objective, low-cost, and noninvasive portable automatic sleep-monitoring device FESP, which provides effective information for long-term family sleep disorder diagnosis and sleep quality monitoring.

Impact of the COVID-19 pandemic on the psychological aspects and mental health of elite soccer athletes: a systematic review

IntroductionInvestigation of the psychological impact on soccer athletes during the pandemic is essential given their unique challenges, including training disruptions and competition postponements. Understanding these effects will allow the development of specific strategies to preserve the mental health and performance of elite athletes, contributing to effective interventions with both short and long-term benefits.ObjectiveTo analyze the impact of the COVID-19 pandemic on the psychological aspects and mental health of elite soccer athletes.MethodThe review adhered to PRISMA criteria, and the study protocol was registered in the International Prospective Register of Systematic Reviews (CRD42022341545). Searches were conducted until July 2023 in databases including Cochrane, PsycINFO, PubMed, Scopus, SPORTDiscus, and Web of Science. Only original, peer-reviewed studies in English, Portuguese, or Spanish assessing the impact of the COVID-19 pandemic on the psychological aspects and mental health of elite soccer athletes were included.ResultsThe search identified 1,055 records and 43 studies were included in this review between 2020 and 2023. In total, the sample included 16,321 soccer athletes of different age groups. Anxiety, depression, mood states, and mental well-being were the most investigated variables. Increased levels of anxiety, depression, and worsening mental well-being were observed in elite soccer athletes. Maintaining fitness during the pandemic showed positive results. Other variables, such as coping, resilience, and sleep quality monitoring, were less widely investigated. Evaluating methodological quality was considered regular for observational and experimental studies.ConclusionThe study reveals a negative impact of the COVID-19 pandemic on elite soccer athletes, considering psychological aspects and their mental health, notably heightened anxiety and depression. Observational methods predominated, showing mood swings linked to individual characteristics and fitness maintenance efforts. Studies with better-designed methodological approaches and controlled experimental interventions are recommended in the future to mitigate the negative effects of the pandemic on soccer players.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?, identifier (CRD42022341545).

Fabrication and characterization of polymer optical waveguide Bragg grating for pulse signal sensing.

Polymer materials have the advantages of a low Young's modulus and low-cost preparation process. In this paper, a polymer-based optical waveguide pressure sensor based on a Bragg structure is proposed. The change in the Bragg wavelength in the output spectrum of the waveguide Bragg grating (WBG) is used to linearly characterize the change in pressure acting on the device. The polymer-based WBG was developed through a polymer film preparation process, and the experimental results show that the output signal of the device has a sensitivity of 1.275 nm/kPa with a measurement range of 0-12 kPa and an accuracy of 1 kPa. The experimental results indicate that the device already perfectly responds to a pulse signal. It has significant potential application value in medical diagnostics and health testing, such as blood pressure monitoring, sleep quality monitoring, and tactile sensing.

The past, present, and future of sleep quality assessment and monitoring

Sleep quality is considered to be an individual's self-satisfaction with all aspects of the sleep experience. Good sleep not only improves a person's physical, mental and daily functional health, but also improves the quality-of-life level to some extent. In contrast, chronic sleep deprivation can increase the risk of diseases such as cardiovascular diseases, metabolic dysfunction and cognitive and emotional dysfunction, and can even lead to increased mortality. The scientific evaluation and monitoring of sleep quality is an important prerequisite for safeguarding and promoting the physiological health of the body. Therefore, we have compiled and reviewed the existing methods and emerging technologies commonly used for subjective and objective evaluation and monitoring of sleep quality, and found that subjective sleep evaluation is suitable for clinical screening and large-scale studies, while objective evaluation results are more intuitive and scientific, and in the comprehensive evaluation of sleep, if we want to get more scientific monitoring results, we should combine subjective and objective monitoring and dynamic monitoring.

Exploration of Perioperative Sleep Disturbance in 208 Patients Undergoing Non-Cardiac Surgery: Protocol for a Prospective Cohort Study.

BACKGROUND Sleep disorder is a common complication for postoperative patients, which can impact their recovery and prognosis. In the perioperative period of non-cardiac surgery, multiple factors can be involved in abnormal sleep in patients, including changes in sleep quality and quantity. Thus, the purpose of this study is to explore the incidence of postoperative sleep disturbance and related influencing factors in 208 patients undergoing non-cardiac surgery. MATERIAL AND METHODS This is a single-center prospective cohort study including 208 eligible patients who will undergo non-cardiac surgery. All participants will implement the assessment and monitoring of perioperative sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and a wearable electroencephalogram (EEG) sleep monitor on the night before surgery and on the first, third, and fifth nights after surgery (the first night is the day of surgery). Meanwhile, we will collect the patient's basic information, past history, and surgery-related data from the hospital electronic medical record and will perform follow-up before and after surgery. RESULTS The primary outcome is the occurrence of sleep disturbance on the first, third, and fifth nights after surgery. The secondary outcomes are the factors related to sleep disturbance and changes in sleep structure on the first, third, and fifth nights after surgery. CONCLUSIONS This study will record the incidence of postoperative sleep disturbance, explore the risk factors of postoperative sleep disturbance, and clarify the change of postoperative sleep structure, which will provide ideas for clinicians to manage patients' sleep disturbance during the perioperative period.

A novel approach to automatic sleep stage classification using forehead electrophysiological signals

BackgroundSleep stage scoring is very important for the effective diagnosis and intervention of sleep disorders. However, the current automatic sleep staging methods generally have the problems of poor model generalization ability and non-portable acquisition equipment. MethodIn this paper, we propose a novel automatic sleep scoring system based on forehead electrophysiological signals that is more effective and convenient than other systems. We extract 3 channel signals from the forehead, named forehead electroencephalogram 1 (Fh1), forehead electroencephalogram 2 (Fh2), and forehead center electrooculogram (Fhz). Spectral features, statistical features, and entropy features are extracted using the discrete wavelet transform (DWT) method. Light gradient boosting machine (LGB), random forest (RF), and support vector machine (SVM) are employed to classify four stages: awake, light sleep (LS), deep sleep (DS), and rapid eye movement (REM). ResultThe performance of the proposed method is validated using databases of the Sleep-EDFX and our Own-data, which include polysomnograms (PSGs) and forehead signals of 28 subjects. The overall classification accuracy of using the combination of Fh1, Fh2, and Fhz can reach up to 90.25% accuracy with a kappa coefficient of 0.857. ConclusionsThe proposed method could provide state-of-art multichannel sleep stage scoring performance with higher portability. This will facilitate the application of long-term monitoring of sleep quality in the future.

Stretchable, Skin-Breathable, and Ultrasensitive Respiration Sensor Using Graphite on Paper With Smart Structures

Healthy sleep is an important indicator of good physical and mental health. The current technology employed for monitoring sleep quality is typically expensive and invasive, which demands innovations in respiration monitoring. In addition, recent effort in developing wearable respiration sensors has faced great challenges in concurrently obtaining low cost, high stretchability, and high sensitivity. Herein, we demonstrate a simple fabrication strategy to construct low-cost, stretchable, skin-breathable and ultrasensitive respiration sensors using pencil drawing, electrode pasting, and laser cutting methods. With smart designs, the sensors exhibited high sensitivity, good stability, decent skin-breathability and capability to detect respiration rate and depth in real-time. The sensors fabricated by the simple low-cost method in this study can be utilized to measure sleep quality, providing warning signals for apnea and sleep disorders. The proposed technology holds promise for developing cost-effective wearable ultrasensitive sensors for sleep quality monitoring.

Multiple hydrogen bonds reinforced conductive hydrogels with robust elasticity and ultra-durability as multifunctional ionic skins

Ion-conductive (IC) hydrogels as ionic skins (I-skins) have shown vast potentials in wearable electronic devices, human-machine interfaces, and health monitoring. However, it is still challenging to fabricate IC hydrogels with high stretchability and robust elasticity to stably output electrical signals subjected to multiple mechanical cycles. In this work, profiting from the hydrophobicity-assisted multiple hydrogen bonds formation by N-acryloyl phenylalanine (APA), we develop an IC hydrogel sensor with comprehensive performances by one-pot radical polymerization of APA and acrylic acid (AA) in the presence of ferric chloride (FeCl3). The hydrogels show excellent mechanical properties with tensile strength of 210–400 kPa, fracture strain of 880–1100%, and elastic modulus of 71–94 kPa, and could withstand multiple mechanical cycles (1000 tensile cycles with 100% of strain and 1000 compressive cycles with 40% of strain) with robust elasticity. Moreover, the hydrogels feature high conductivity (0.55 S/m), excellent sensing performance (gauge factor (GF) = 7.95), and wide sensing range of strain (2.5–300%) and pressure (1–80 kPa), which can be utilized for the detection of large and tiny movements of human body and the monitoring of sleep quality with reliable signal outputs. Based on the adequate tissue adhesiveness, rapid self-recovery, excellent fatigue resistance and good biocompatibility, the IC hydrogels can serve as promising smart flexible electronics for the application in different fields.

A Smart Flexible Vital Signs and Sleep Monitoring Belt Based on MEMS Triaxial Accelerometer and Pressure Sensor

People spend about one third of their lifetime in sleep, and sleep quality has a great impact on people’s health. Therefore, vital signs and sleep quality monitoring are more and more important. In this article, a novel smart flexible sleep monitoring belt with MEMS triaxial accelerometer and pressure sensor is developed to detect vital signs, snore events, and sleep stages. Besides, the related algorithms and methods for data preprocessing, heart and respiration rates detection, snoring recognition, and sleep stages classification are proposed in detail. Then, a series of sleep experiments is performed based on the experimental platform for the smart flexible belt, and the test results measured by PolySomnoGraphy are used as the golden standards for comparison. The experimental results demonstrate that the detection accuracies of heart rate and respiration rate of the belt are about 1.5 and 0.7 bpm, respectively. The accuracy of 97.2% is achieved by the proposed snoring recognition method. In addition, as for 2-stage analysis, the sensitivities of awake and asleep stages are 90.2% and 100%, respectively; meanwhile, the corresponding accuracy of sleep stages prediction is as high as 95.1%. However, as for 4-stage analysis, the sensitivities of awake, rapid eye movement, light sleep, and deep sleep stages are 90.2%, 77.1%, 78.1%, and 73.5%, respectively; meanwhile, the corresponding accuracy of sleep stages prediction decreases to 79.7%. In general, the test results indicate that vital signs detection, snoring recognition, and sleep stages classification based on the sleep monitoring belt are feasible and effective. Hence, this smart flexible belt can be widely used for sleep monitoring at home due to low cost and high performance.

0229 Concerns about the future linked with poor sleep quality in U.S. Army Soldiers withdrawing from Afghanistan

Abstract Introduction A special operations unit of U.S. Soldiers rotated through Afghanistan from October, 2001 to the U.S. drawdown in 2020-2021. For these Soldiers, the drawdown has led to uncertainties about the future of the unit and their careers. Psychological stress resulting from these uncertainties could lead to sleep disturbances. This study assessed the relationship between attitudes about the Afghanistan drawdown and sleep. Methods A survey was broadly distributed in July-August 2021. To assess attitudes about the drawdown, participants were asked whether they felt changes in their personal readiness had occurred since the drawdown began. They were asked how they believed the unit should support Afghanistan in the future (remain in Afghanistan, support only through airstrikes, or no further support). Lastly, Soldiers were asked whether the drawdown made them more likely to switch to another unit, get out of the Army, or no change. Subjective sleep quality and duration from the month prior was assessed. Due to the abrupt fall of Kabul, the survey was discontinued earlier than planned, resulting in 35 participants. Results Soldiers were 32.80±5.99 years old. They had been in the unit for 8.89±5.71 years and had deployed to Afghanistan 5.14±3.14 times. The average sleep duration was 6.66±0.79 hours, and the average sleep quality was 63.39%±21.63%. There were no relationships between attitudes and sleep duration. However, regression analyses showed those who reported increased stress (B=18.16, p=.01), decreased morale (B=2.97, p=.006), and decreased motivation (B=2.69, p=.01) since the drawdown began had poorer sleep quality. ANOVA tests showed Soldiers who believed the unit should remain in Afghanistan had poorer sleep quality than those endorsing only air support or no involvement (F(2,29)=6.39, p=.005). Further, those who endorsed being more likely to make a career change had poorer sleep quality than those with no changes in career plans (F(2,29)=3.53, p=.04). Conclusion These results indicate that psychological distress resulting from the drawdown may be impacting sleep quality in this unit. Continuous monitoring of sleep quality may prove to be a sensitive indicator of elevated stress at the unit level. Support (If Any) Support for this study came from the Military Operational Medicine Research Program (MOMRP) of the United States Army Medical Research and Development Command (USAMRDC). Material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors, and are not to be construed as official, or as reflecting true views of the Department of the Army or the Department of Defense. The investigators have adhered to the policies for protection of human subjects as prescribed in AR 70–25. The authors have no conflicts of interest to disclose.

Using 24-h Heart Rate Variability to Investigate the Sleep Quality and Depression Symptoms of Medical Students.

There have been numerous studies on the relationship between sleep and depression, as well as the relationship between sleep and depression, and heart rate variability (HRV), respectively. Even so, few studies have combined 24-h HRV analysis to study sleep quality and depressive symptoms. The purpose of this cross-sectional study was to investigate the relationship between depressed symptoms, sleep quality, and 24-h HRV in medical students. The particiants were all students at a medical university in Guangdong province, China. A total of 74 college students participated. They were asked to complete a questionnaire that included the Pittsburgh Sleep Quality Index (PSQI), the Beck Depression Inventory-II (BDI-II), the Positive and Negative Affect Scale (PANAS), and 24-h ECG monitoring. The results showed that 41.7% of the medical students had poor sleep quality, with higher levels of depressive symptoms and more negative emotions, and there was no difference in 24-h HRV indices between the low PSQI group and the high one. Correlation analysis showed that there was a significant relationship between sleep quality and depressive symptoms (r = 0.617), but the relationship between 24-h HRV indices and PSQI global scores, BDI scores were not significant. However, the correlation analysis of PSQI components and 24-h HRV showed that sleep disturbance was significantly negatively correlated with SDNN and LF in waking period (r = −0.285, −0.235), and with SDNN in sleeping period (r = −0.317). In general, the sleep disturbance in PSQI components can sensitively reflect the relationship between sleep quality and 24-h HRV of medical students. Individuals with higher sleep disturance may have lower SDNN during awake period and bedtime period, and lower LF in awake period. Twenty-four hour HRV has certain application value in clinical sleep quality monitoring, and its sensitivity and specificity in clinical application and daily life are still worth further investigation.

Sleep Quality and Electroencephalogram Delta Power.

Delta activity on electroencephalogram (EEG) is considered a biomarker of homeostatic sleep drive. Delta power is often associated with sleep duration and intensity. Here, we reviewed the literature to explore how sleep quality was influenced by changes in delta power. However, we found that both the decrease and increase in delta power could indicate a higher sleep quality due to the various factors below. First, the differences in changes in delta power in patients whose sleep quality is lower than that of the healthy controls may be related to the different diseases they suffered from. We found that the patients mainly suffered from borderline personality disorder, and Rett syndrome may have a higher delta power than healthy individuals. Meanwhile, patients who are affected by Asperger syndrome, respiratory failure, chronic fatigue, and post-traumatic stress disorder have lower delta power. Second, if the insomnia patients received the therapy, the difference may be caused by the treatment method. Cognitive or music therapy shows that a better therapeutic effect is associated with decreased delta power, whereas in drug treatment, there is an opposite change in delta power. Last, for healthy people, the difference in delta change may be related to sleep stages. The higher sleep quality is associated with increased delta power during the NREM period, whereas a deceased delta change accompanies higher sleep quality during the REM period. Our work summarizes the effect of changes in delta power on sleep quality and may positively impact the monitoring and intervention of sleep quality.

Sensing, computing and intervention for sleep health

<p indent=0mm>As an instinctive part of human life, sleep not only is of great significance to the individual’s physical and mental health, but also could be a natural means of regulating, restoring and enhancing body functions. Accordingly, sleep quality not only affects people’s quality of life, but also is closely related to the occurrence and development of many physiological and psychological diseases. Statistics show that about one-third of the population in China has sleep disorders, and a growing number of people have sleep health requirements. There is a prominent contradiction between this demand and the backward daily sleep health management. Therefore, it is urgent to set up theories and methods ranging from sleep structure conversion mechanism to sleep quality monitoring and intervention. For this reason and based on the discussion of the Y5th Xiangshan Scientific Conference (Smart Sensing and Computing for Sleep Health), this paper provides an in-depth analysis of sleep perception, intelligent sleep computing and sleep intervention methods in recent years. It foresees the key scientific and technical issues in the three stages of this closed-loop system. Combining wearable sensing and medical artificial intelligence technology, we should form a platform and develop algorithms from sleep quality monitoring to objective diagnosis of sleep disorders. Principles and methods of physical and behavioral interventions should be also explored to improve the physical and mental state of sleep regulation, so as to establish a new paradigm of “active sleep health” comprehensively. Considering the feasibility of the next few years from the perspective of principle, mechanisms, methods and measures, we propose the following recommendations: (1) Sleep-wake transformation mechanism. The study of sleep-related electrophysiology biomarkers could reveal the sleep-wake transformation and regulatory mechanisms to guide the development of sleep health standards for the Chinese population. Based on such a mechanism, an objective assessment of people’s overall health status could be achieved. It will be used for national sleep health screening and prevention of sleep disorders, and provide a theoretical basis for active sleep health promotion. (2) Sleep health promotion for specific populations. In order to adapt to the sleep health of children, youth, elderly and special types of personnel, research on the brain neural mechanism of biological rhythm should be carried out for different groups in order to build personalized multi-physiological parameter monitoring devices, intelligent analysis algorithms and active intervention paradigms. (3) Sleep health promotes physical and mental health. Sleep is closely related to the development of many physiological diseases. To reduce the incidence of chronic diseases, we should explore the mechanism of its association with the cardiovascular system, respiratory system, nervous system and endocrine system. A multimodality data analysis system could be developed with independent intellectual property rights. This will promote the advancement of sleep-related industries in China and propose relevant technical standards and guidelines to achieve active health management.

Skin-inspired wearable self-powered electronic skin with tunable sensitivity for real-time monitoring of sleep quality

In modern times, it is essential to ensure excellent sleep quality and comfort, and a way to scientifically assess these conditions is urgently needed. However, most existing sleep monitoring devices are complicated and uncomfortable to wear. Here, a dermal papillae-bioinspired self-powered multifunctional electronic skin (e-skin) with an all-fibrous multilayer nanostructure based on a triboelectric nanogenerator is proposed, which is sensitive, lightweight, ultrathin, breathable, biocompatible, and low-cost. Owing to the bead polyvinylidene fluoride nanofibers of the e-skin simulating the dermal papillae of natural skin and the N-(2-aminoethyl)-3-aminopropyl trimethoxy silane-modified nature of the collagen aggregate nanofibers, the e-skin exhibits the highest sensitivity (0.32 V kPa−1) in the range of 0–135 kPa. Additionally, it has short response and recovery times (20 and 33 s, respectively) in the humidity range of 25–85% RH. More importantly, the e-skin converts mechanical energy into electrical energy for humidity detection via an energy circulation system. The e-skin can collect the heartbeat and respiration signals and perform an analysis on their frequency and stability, which can be used to accurately measure the different sleep phases. By analyzing the proportion of each phase and environmental humidity, the e-skin can be employed to scientifically assess the sleep quality and comfort of insomnia patients and night owls through real-time monitoring.

Sleep Quality in Patients Undergoing Transcatheter Aortic Valve Implantation (TAVI).

The present study aimed to analyze sleep quality and quality of Life (QoL) in patients undergoing Transcatheter Aortic Valve Implantation (TAVI). It was conducted at the Interventional Cardiology Unit of the Department of Cardiac, Thoracic, Vascular Sciences and Public Health of the University of Padova on 27 adult patients who underwent TAVI via the transfemoral approach. Patients completed two validated instruments, i.e., the Pittsburgh Sleep Quality Index (PSQI) and the EuroQoL (EQ-5D-5L), on the day of discharge and one month after the hospital discharge. Twenty-seven patients were enrolled with a severe aortic stenosis diagnosis, treated with transfemoral TAVI procedure. The study population included seventeen poor sleepers and ten good sleepers with a median age of 81.92 years overall. The global PSQI evaluation revealed a small significant improvement at follow-up (p-value 0.007). Small positive changes were detected in the Self-care and Usual activity domains of the EQ-5D-5L and the EQ-VAS. No correlation was detected between EQ-5D-5L and sleep quality. The present study confirms the importance of sleep quality monitoring in patients who undergo TAVI procedure for aortic stenosis treatment.

Sleep quality and glycaemic variability in a real-life setting in adults with type 1 diabetes.

Suboptimal subjective sleep quality is very common in adults with type 1 diabetes. Reducing glycaemic variability is a key objective in this population. To date, no prior studies have examined the associations between objectively measured sleep quality and overnight glycaemic variability in adults with type 1 diabetes. We aimed to test the hypothesis that poor sleep quality would be associated with greater overnight glycaemic variability. Data were collected in the home setting from 20 adults (ten male and ten female participants) with type 1 diabetes who were current insulin pump users. Simultaneous assessments of objective sleep quality (Zmachine Insight+) and continuous glucose monitoring (CGM) were performed over multiple nights (up to 15 nights) in each participant. Due to the real-life nature of this study, the participants kept their usual CGM alerts for out-of-range glucose values. Sleep quality was categorised as 'good' or 'poor' using a composite of objective sleep features (i.e. sleep efficiency, wake after sleep onset and number of awakenings) based on the National Sleep Foundation's consensus criteria. Glycaemic variability was quantified using SD and CV of overnight glucose values based on overnight CGM profiles. A total of 170 nights were analysed. Overall, 86 (51%) nights were categorised as good sleep quality, and 84 (49%) nights were categorised as poor sleep quality. Using linear mixed-effects models, poor sleep quality was significantly associated with greater glycaemic variability as quantified by SD (coefficient: 0.39 [95% CI 0.10, 0.67], p = 0.009) and CV (coefficient: 4.35 [95% CI 0.8, 7.9], p = 0.02) of overnight glucose values, after accounting for age, sex, BMI and overnight insulin dose. There was large inter- and intra-individual variability in sleep and glycaemic characteristics. Both pooled and individual-level data revealed that the nights with poor sleep quality had larger SDs and CVs, and, conversely, the nights with good sleep quality had smaller SDs and CVs. No associations were found between sleep quality and time spent in the target glucose range, or above or below the target glucose range, where CGM alarms are most likely to occur. Objectively measured sleep quality is associated with overnight glycaemic variability in adults with type 1 diabetes. These findings highlight an important role of sleep quality in overnight glycaemic control in type 1 diabetes. They also provide a strong incentive to both patients and healthcare providers for considering sleep quality in personalised type 1 diabetes glycaemic management plans. Future studies should investigate the mechanisms linking sleep quality to glycaemic variability.