Search Results (117)

The human circadian rhythm is connected to the body’s endogenous clock and can influence people’s natural sleeping habits as well as a variety of other biological functions. According to research, various electric light sources in interior locations can disrupt the human circadian rhythm. Many psychological studies, on the other hand, reveal that different colors can have varied connections with and a variety of effects on people’s emotions. In this study, the effects of light source attributes and interior space paint color on human circadian rhythm were studied using 24 distinct computer simulations. Simulations were performed using the ALFA plugin for Rhinoceros 6 on an unfurnished bedroom 3D model at night. Results suggest that cooler hues, such as blue, appear to have an unfavorable effect on human circadian rhythm at night, especially when utilized in spaces that are used in the evening, which contradicts what psychologists and interior designers advocate in terms of the soothing mood and nature of the color. Furthermore, the effects of Correlated Color Temperature (CCT) and the intensity of a light source might be significant in minimizing melanopic lux to prevent melatonin suppression at night. These insights are significant for interior designers, architects, and lighting professionals aiming to create healthier living environments by carefully selecting lighting and color schemes that support circadian health. Incorporating these considerations into design practices can help mitigate adverse effects on sleep and overall well-being, ultimately contributing to improved occupant comfort and health. Full article

Obstructive sleep apnea (OSA) is a prevalent and heterogeneous sleep disorder associated with significant health and societal burdens. While continuous positive airway pressure (CPAP) remains the gold standard treatment, its limitations in adherence and patient tolerance have highlighted the need for alternative therapies. Positional therapy (PT), which targets apneas that occur predominantly in the supine position, has emerged as a promising option for individuals with positional OSA (POSA). This narrative review synthesizes the current literature on PT, examining its clinical indications, typologies, comparative efficacy with CPAP, oral appliances, and hypoglossal nerve stimulation, as well as data on adherence and barriers to long-term use. Traditional methods such as the tennis ball technique have largely been replaced by modern vibrotactile devices, which demonstrate improved comfort, adherence, and comparable short-term outcomes in selected POSA subjects. While PT remains inferior to CPAP in reducing overall AHI and oxygen desaturation, it performs favorably in terms of mean disease alleviation (MDA) and sleep continuity. Importantly, treatment effectiveness is influenced by both anatomical and non-anatomical traits, underscoring the need for accurate phenotyping and individualized care. PT should be considered within a broader patient-centered model that incorporates preferences, lifestyle, and motivational factors. Further research is needed to validate long-term efficacy, optimize selection criteria, and integrate PT into personalized OSA management strategies. Full article

Eczema, or atopic dermatitis (AD), is a chronic inflammatory skin condition characterized by persistent itching and scratching, significantly impacting patients’ quality of life. Effective monitoring of scratching behaviour is crucial for assessing disease severity, treatment efficacy, and understanding the relationship between itch and sleep disturbances. This review explores current technological approaches for detecting and monitoring scratching and itching in AD patients, categorising them into contact-based and non-contact-based methods. Contact-based methods primarily involve wearable sensors, such as accelerometers, electromyography (EMG), and piezoelectric sensors, which track limb movements and muscle activity associated with scratching. Non-contact methods include video-based motion tracking, thermal imaging, and acoustic analysis, commonly employed in sleep clinics and controlled environments to assess nocturnal scratching. Furthermore, emerging artificial intelligence (AI)-driven approaches leveraging machine learning for automated scratch detection are discussed. The advantages, limitations, and validation challenges of these technologies, including accuracy, user comfort, data privacy, and real-world applicability, are critically analysed. Finally, we outline future research directions, emphasizing the integration of multimodal monitoring, real-time data analysis, and patient-centric wearable solutions to improve disease management. This review serves as a comprehensive resource for clinicians, researchers, and technology developers seeking to advance objective itch and scratch monitoring in AD patients. Full article

Workplace contextual emotions are structured ways of emotionally thinking about specific cues in the context that employees share within their organization. These dynamics reflect how employees emotionally interpret and respond to organizational environments. Contextual emotions may shape working relationships into different types of toxic emotional dynamics (e.g., claiming, controlling, distrusting, provoking) or, conversely, positive emotional dynamics (i.e., exchanging), thus setting the emotional tone that affects employees’ actions and their level of comfort/discomfort. The present study uses latent profile analysis (LPA) to identify subpopulations of employees who may experience differing levels of both positive and negative emotional dynamics (i.e., different configurations of emotional patterns of workplace behavior). Moreover, it examines whether the emergent profiles predict work-related (i.e., job satisfaction, burnout) and health-related outcomes (i.e., sleep disturbances, physical and mental health). Using data from 801 Italian employees, we identified four latent profiles: “functional dynamics” (low toxic emotions and high exchange), “dialectical dynamics” (co-existence of medium toxic emotions and medium exchange), “mild dysfunctional dynamics” (moderately high toxic emotions and low exchange), and “highly dysfunctional dynamics” (extremely high toxic emotions and extremely low exchange). Moreover, employees in the dialectical, mild dysfunctional, and highly dysfunctional groups reported progressively higher levels of poor health outcomes and progressively lower levels of satisfaction, whereas the functional group was at low risk of stress and was the most satisfied group. The theoretical and practical implications of the LPA-classified emotional patterns of workplace behavior are discussed in light of the relevance of identifying vulnerable subpopulations of employees diversely exposed to toxic configurations of emotional/relational ambience. Full article

Work-related well-being is an important research topic, as it is linked to various aspects of individuals’ lives, including job performance. To measure it effectively, unobtrusive sensors are desirable to minimize the burden on employees. Because there is a lack of consensus on the definitions of well-being in the psychological literature in terms of its dimensions, our work begins by proposing a conceptualization of well-being based on the refined definition of health provided by the World Health Organization. We focus on reviewing the existing literature on the unobtrusive measurement of well-being. In our literature review, we focus on affect, engagement, fatigue, stress, sleep deprivation, physical comfort, and social interactions. Our initial search resulted in a total of 644 studies, from which we then reviewed 35, revealing a variety of behavioral markers such as facial expressions, posture, eye movements, and speech. The most commonly used sensory devices were red, green, and blue (RGB) cameras, followed by microphones and smartphones. The methods capture a variety of behavioral markers, the most common being body movement, facial expressions, and posture. Our work serves as an investigation into various unobtrusive measuring methods applicable to the workplace context, aiming to foster a more employee-centric approach to the measurement of well-being and to emphasize its affective component. Full article

This study investigates the impact of heatwaves on the thermal comfort and well-being of elderly individuals living alone during heatwaves, focusing on two contrasting residential typologies in the Atlantic climate of Spain: a dense urban area and low-density peri-urban setting. A mixed-methods approach was used, combining in situ environmental monitoring, adaptive comfort modelling, and user-centred data from surveys and interviews based on the De Jong-Gierveld Loneliness Scale. The results show that both dwellings exceeded recommended indoor temperature thresholds during heatwaves, especially at night, contributing to sleep disturbance, cardiovascular stress, and emotional discomfort. Despite 85% of participants indicating that outdoor activities help them to mitigate not-wanted loneliness, architectural barriers often hinder such engagement. Over half reported having no balcony or terrace, which may have further intensified social isolation. Field data collected during 2022 summer heatwaves recorded maximum daytime temperatures of 30 °C and night-time peaks of 28.7 °C, exceeding the 25 °C threshold. The adaptive comfort evaluation classified both cases as Class 4 (severe discomfort). The urban dwelling showed consistent moderate discomfort (Category 3), likely due to poor ventilation and urban heat island effects. The peri-urban case, despite lacking the heat island influence, showed worse thermal conditions, especially during the day. Architectural barriers, poor thermal performance, and the lack of semi-outdoor spaces may exacerbate isolation among elderly people during extreme heat events. Full article

Sleep posture detection is a potentially important component of sleep quality assessment and health monitoring. Accurate identification of sleep postures can offer valuable insights into an individual’s sleep patterns, comfort levels, and potential health risks. For example, improper sleep postures may lead to musculoskeletal issues, respiratory disturbances, and even worsen conditions like sleep apnea. Additionally, for long-term bedridden patients, continuous monitoring of sleep postures is essential to prevent pressure ulcers and other complications. Traditional methods for sleep posture detection have several limitations: wearable sensors can disrupt natural sleep and cause discomfort, camera-based systems raise privacy concerns and are sensitive to environmental conditions, and pressure-sensing mats are often complex and costly. To address these issues, we have developed a low-cost non-contact sleeping posture detection system. Our system features eight optimally distributed triaxial accelerometers, providing a comfortable and non-contact front-end data acquisition unit. For sleep posture classification, we employ an improved density peak clustering algorithm that incorporates the K-nearest neighbor mechanism. Additionally, we have constructed a Parallel Convolutional Spatiotemporal Network (PCSN) by integrating Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Bidirectional Long Short-Term Memory (Bi-LSTM) modules. Experimental results demonstrate that the PCSN can accurately distinguish six sleep postures: prone, supine, left log, left fetus, right log, and right fetus. The average accuracy is 98.42%, outperforming most state-of-the-art deep learning models. The PCSN achieves the highest scores across all metrics: 98.64% precision, 98.18% recall, and 98.10% F1 score. The proposed system shows considerable promise in various applications, including sleep studies and the prevention of diseases like pressure ulcers and sleep apnea. Full article

Measurement of respiratory patterns during sleep plays a critical role in assessing sleep quality and diagnosing sleep disorders such as sleep apnea syndrome, which is associated with many adverse health outcomes, including cardiovascular disease, diabetes, and cognitive impairments. Traditional methods for measuring breathing often rely on expensive and complex sensors, such as polysomnography equipment, which can be cumbersome and costly and are typically confined to clinical settings. These factors limit the performance of respiratory monitoring in routine settings and prevent convenient and extensive screening. Recognizing the need for accessible and cost-effective solutions, we developed a portable sleep sensor that uses an electret condenser microphone (ECM), which is inexpensive and easy to obtain, to measure nasal airflows. Constant current circuits that bias the ECM and circuit constants suitable for measurement enable special uses of the ECM. Furthermore, data transmission through the XBee wireless communication module, which employs the ZigBee short-range wireless communication standard, enables highly portable measurements. This customized configuration allows the ECM to detect subtle changes in airflow associated with breathing patterns, enabling the monitoring of respiratory activity with minimal invasiveness and complexity. Furthermore, the wireless module not only reduces the size and weight of the device, but also facilitates continuous data collection during sleep without disturbing user comfort. This portable wireless sensor runs on batteries, providing approximately 50 h of uptime, a ±50 Pa pressure range, and 20 Hz real-time sampling. Our portable sleep sensor is a practical and efficient solution for respiratory monitoring outside of the traditional clinical setting. Full article

Introduction: Hypoglossal nerve stimulation (HNS) “Inspire_© therapy” has garnered popularity among obstructive sleep apnea (OSA) patients seeking an alternative to continuous positive airway pressure (CPAP) therapy. The growth in HNS has been particularly high in older adults living with OSA. Consistent and proper use of HNS in the geriatric population faces unique age-associated barriers: a high rate of multiple chronic conditions (MCC) and polypharmacy (being on five or more drugs). Early recognition and patient-centered management of these barriers will allow older patients to obtain maximum benefits from HNS. HNS has distinct advantages in the geriatric population because it overcomes many concerns related to CPAP therapy adherence, such as mechanical limitations due to manual dexterity, maxillofacial anatomy, dental issues such as usage of dentures, allergy/otolaryngology-related disorders, and pre-existing post-traumatic stress disorder-related claustrophobia. This paper describes how we worked with older patients with OSA and their care partners to overcome these barriers so patients can continue to derive cardiovascular, neurologic, and quality of life benefits resulting from optimal OSA management. These benefits are especially important in the older population because of higher rates of comorbidities (dementia, coronary artery disease, and atrial fibrillation) exacerbated by sub-optimally treated OSA. In this article, we describe our clinical experience with elderly patients on Inspire_© therapy, with a focus on the everyday difficulties faced by these patients and the measures implemented to address and mitigate these barriers. Methods: A retrospective chart review was conducted to identify patients aged 65 and above who underwent hypoglossal nerve stimulator insertion. Experiences of older patients during and after the insertion procedure were documented and compared to a younger population of patients on HNS therapy. We specifically collected information on difficulties encountered during activation or follow-up visits and compared them between the different age groups. Using this information, we identified areas to improve treatment adherence from the patients’ perspectives. Results: We identified 43 geriatric (65 to 86 years old) patients who received the Inspire implant at a tertiary academic medical center and compared them to a younger population of 23 patients. Most common challenges noted—with a potential to impact adherence—included orofacial and lingual neuropraxia (ischemic or demyelination-induced neuropathy) at activation, cognitive dysfunction (memory problems), preexisting anxiety, and insomnia. Other difficulties that are less commonly reported but equally important to consistent and proper use of HNS included headaches, concerns of device malfunction, change in comfort levels after cardiac procedures, and general intolerance of the device. The older patient population had a statistically significant higher incidence of cognitive difficulties (30.2% vs. 4.4%) and a smaller social support system (62.8% vs. 91.3%) affecting device usage compared to the younger population. There were no statistically significant differences in the rates of other more commonly reported adverse effects such as headaches, dry mouth, and anxiety between the two age groups. Conclusion: Despite several challenges faced by geriatric patients, Inspire_© hypoglossal nerve stimulation remains a viable, alternative treatment option for OSA with improved tolerance and adherence compared to CPAP. After identifying less commonly reported barriers such as cognitive decline, sensory deficits, and decreased social support systems, minor adjustments and appropriate education on use allows older patients to correctly use and benefit from Inspire_© device therapy, with subsequent improvement in sleep and overall quality of life. Full article

This study investigates the potential of a novel sleep endoscope, NasoLens, to eliminate the need for anesthesia in sleep endoscopy. We assess NasoLens’ safety, maneuverability, and ability to allow sleep without sedatives, aiming to improve the overall patient experience and reduce risks associated with anesthesia. Sleep endoscopy is commonly performed under anesthesia, which introduces risks, increases costs, and can limit accessibility. NasoLens’ design aims to address these challenges by improving patient comfort and enhancing maneuverability, eliminating the need for anesthesia. This could provide a safer, more cost-effective alternative for patients, particularly those at higher risk for anesthesia-related complications. NasoLens distinguishes itself with its smaller size, teardrop-shaped head, specialized camera angle for better visualization, and an integrated microphone for real-time auditory monitoring. These features enable NasoLens to offer improved maneuverability and comfort, compared to traditional nasopharyngoscopes, while enhancing diagnostic accuracy. These design innovations could revolutionize clinical practice by minimizing anesthesia-related risks, reducing procedural costs, and improving both procedural efficiency and patient satisfaction. With its ability to allow natural sleep without sedation, NasoLens has the potential to improve patient satisfaction, procedural outcomes, and expand the feasibility of sleep endoscopy into more accessible clinical settings, making it a promising alternative to traditional models. Full article

Electroencephalography (EEG) remains an essential method for monitoring brain activity, but the limitations of conventional systems due to the complexity of installation and lack of portability have led to the introduction and development of in-ear EEG technology. In-ear EEG is an emerging method of recording electrical activity in the brain and is an innovative concept that offers multiple advantages both from the point of view of the device itself, which is easily portable, and from the user’s point of view, who is more comfortable with it, even in long-term use. One of the fundamental components of this type of device is the electrodes used to capture the EEG signal. This innovative method allows bioelectrical signals to be captured through electrodes integrated into an earpiece, offering significant advantages in terms of comfort, portability, and accessibility. Recent studies have demonstrated that in-ear EEG can record signals qualitatively comparable to scalp EEG, with an optimized signal-to-noise ratio and improved electrode stability. Furthermore, this review provides a comparative synthesis of performance parameters such as signal-to-noise ratio (SNR), common-mode rejection ratio (CMRR), signal amplitude, and comfort, highlighting the strengths and limitations of in-ear EEG systems relative to conventional scalp EEG. This study also introduces a visual model outlining the stages of technological development for in-ear EEG, from initial research to clinical and commercial deployment. Particular attention is given to current innovations in electrode materials and design strategies aimed at balancing biocompatibility, signal fidelity, and anatomical adaptability. This article analyzes the evolution of EEG in the ear, briefly presents the comparative aspects of EEG—EEG in the ear from the perspective of the electrodes used, highlighting the advantages and challenges of using this new technology. It also discusses aspects related to the electrodes used in EEG in the ear: types of electrodes used in EEG in the ear, improvement of contact impedance, and adaptability to the anatomical variability of the ear canal. A comparative analysis of electrode performance in terms of signal quality, long-term stability, and compatibility with use in daily life was also performed. The integration of intra-auricular EEG in wearable devices opens new perspectives for clinical applications, including sleep monitoring, epilepsy diagnosis, and brain–computer interfaces. This study highlights the challenges and prospects in the development of in-ear EEG electrodes, with a focus on integration into wearable devices and the use of biocompatible materials to improve durability and enhance user comfort. Despite its considerable potential, the widespread deployment of in-ear EEG faces challenges such as anatomical variability of the ear canal, optimization of ergonomics, and reduction in motion artifacts. Future research aims to improve device design for long-term monitoring, integrate advanced signal processing algorithms, and explore applications in neurorehabilitation and early diagnosis of neurodegenerative diseases. Full article

This study aims to experimentally evaluate a personal comfort system based on a radiant panel (R-PCS) that can regulate the thermal environment of the sleep zone during summer, with a focus on improving both the thermal comfort and energy efficiency of this system. To investigate thermal comfort under the coupling effect of different covering conditions and operating parameters of the R-PCS, the changing pattern of thermal environment parameters in the berth area and human skin temperature are analyzed. Then, the Predicted Mean Vote (PMV) -Predicted Percent Dissatisfied (PPD) index is employed for assessing the thermal comfort of the human body and energy-saving efficiency of the system. The results show that this system can satisfy the thermal comfort requirements of the human body in the berth area. Meanwhile, the corresponding cooling energy consumption of the R-PCS is significantly lower than that of the traditional HVAC system, indicating that the developed system has significant energy-saving potential in building design. Full article

Women exhibit unique vulnerabilities in health, especially regarding mental health and neurodegenerative diseases. Biological, hormonal, and metabolic differences contribute to sex-specific risks that remain underrepresented in clinical studies. Diseases such as major depressive disorder (MDD) and Alzheimer’s disease (AD) are more prevalent in women and may be influenced by hormonal transitions, particularly during menopause. Chronic low-grade inflammation is emerging as a shared mechanism underlying both conditions, and this inflammatory state can be worsened by dietary habits. During menopause, mood and sleep disturbances can influence dietary behavior, leading to enhanced snacking and consumption of high-glycemic and comfort foods. Such foods, low in nutritional value, promote weight gain and elevated inflammatory markers. Their consumption combined (or not) with a preexisting Western diet pattern—already linked to inflammation—could reinforce systemic inflammation involving the gut–brain axis. Moreover, the symptoms “per se” could act on inflammation as well. Peripheral inflammation may cross the blood–brain barrier, sustaining mood disorders and promoting neurodegenerative changes. Finally, MDD and AD are both associated with conditions such as obesity and diabetes, which occur more frequently in women. The review highlights how menopause-related changes in mood, sleep, and diet may heighten susceptibility to mental and neurodegenerative diseases. Full article

The wheel–rail contact is an intrinsic characteristic of rail transport. This contact is one of the main reasons why rails are so efficient for transportation, mainly due to the very low friction coefficient between them and the wheels. However, this strong argument also leads to a disadvantage: the wheel contact is also associated with excessive vibration and noise, which have a strong impact on the passengers’ comfort and especially the surrounding community. These noises and vibrations impact the public in several ways, like disturbing sleep, increasing stress and heart-associated diseases. The main objective of the present work is to investigate the rail vibration attenuation by applying particle dampers. Four different particles will be studied, and their effectiveness in reducing the rail vibrations will be analysed. Promising results were found, where under certain conditions, the particle dampers, such as lead and magnetite particles, were able to reduce peak vibration levels by more than an order of magnitude. The application of this system may have a strong impact on the communities using and in the vicinity of rail systems by reducing the noise and vibration, consequently improving people’s health and well-being. Full article

Non-visual techniques for identifying sleep postures have become essential for enhancing sleep health. Conventional methods depend on a costly professional medical apparatus that is challenging to adapt for domestic use. This study developed an economical airbag mattress and introduced a method for detecting sleeping positions via restricted body pressure data. The methodology relies on distributed body pressure data obtained from barometric pressure sensors positioned at various locations on the mattress. Two combinations of base learners were chosen based on the complementary attributes of the model, each of which can be amalgamated through a soft-voting strategy. Additionally, the architectures of Autoencoder and convolutional neural networks were integrated, collectively constituting the base learning layer of the model. Gradient enhancement was utilized in the meta-learner layer to amalgamate the output of the basic learning layer. The experimental findings indicate that the suggested holistic learning model has high classification accuracy of up to 95.95%, precision of up to 96.13%, and F1 index of up to 95.01% in sleep posture recognition assessments and possesses considerable merit. In the subsequent application, the sleep monitoring device identified the sleep posture and employed an air conditioner and an air purifier to create a more comfortable sleep environment. The user can utilize the sleep posture data to improve the quality of sleep and prevent related diseases. Full article