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The aim of this review is to present together the studies on textile-based moisture sensors developed using innovative technologies in recent years.

The integration levels of the sensors studied with the textile materials are changing. Some research teams have used a combination of printing and textile technologies to produce sensors, while a group of researchers have used traditional technologies such as weaving and embroidery. Others have taken advantage of new technologies such as electro-spinning, polymerization and other techniques. In this way, they tried to combine the good working efficiency of the sensors and the flexibility of the textile. All these approaches are presented in this article.

The presentation of the latest technologies used to develop textile sensors together will give researchers an idea about new studies that can be done on highly sensitive and efficient textile-based moisture sensor systems.

In this paper humidity sensors have been explained in terms of measuring principle as capacitive and resistive. Then, studies conducted in the last 20 years on the textile-based humidity sensors have been presented in detail. This is a comprehensive review study that presents the latest developments together in this area for researchers.

This study aimed to characterize the concentrations of indoor pollutants (such as carbon dioxide (CO₂), ozone (O₃), nitrogen dioxide (NO₂) and sulfur dioxide (SO₂), as well as particulate matter (PM) (PM₁, PM_2.5 and PM₁₀) in Akure, Nigeria, as well as the relationship between the parameters’ concentrations.

The evaluation, which lasted four months, used a low-cost air sensor that was positioned two meters above the ground. All sensor procedures were correctly carried out.

CO₂ (430.34 ppm), NO₂ (93.31 ppb), O₃ (19.94 ppb), SO₂ (40.87 ppb), PM₁ (29.31 µg/m3), PM_2.5 (43.56 µg/m³), PM₁₀ (50.70 µg/m³), temperature (32.4°C) and relative humidity (50.53%) were the average values obtained. The Pearson correlation depicted the relationships between the pollutants and weather factors. With the exception of April, which had significant SO₂ (18%) and low PM₁₀ (49%) contributions, NO₂ and PM₁₀ were the most common pollutants in all of the months. The mean air quality index (AQI) for NO₂ indicated that the AQI was “moderate” (51–100). In contrast to SO₂, whose AQI ranged from “moderate” to “very unhealthy,” O₃'s AQI ranged from “good” (50) to “unhealthy” (151–200). Since PM₁, PM_2.5 and PM₁₀ made up the majority of PC1’s contribution, both PM_2.5 and PM₁₀ were deemed “hazardous.”

The practical implication of indoor air pollution is long-term health effects, including heart disease, lung cancer and respiratory diseases such as emphysema. Indoor air pollution can also cause long-term damage to people’s nerves, brain, kidneys, liver and other organs.

Lack of literature in terms of indoor air quality (IAQ) in Akure, Ondo State. With this work, the information obtained will assist all stakeholders in policy formulation and implementation. Again, the low-cost sensor used is new to this part of the world.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.

Nursing homes experience high nursing staff turnover. Nursing staff in nursing homes is comprised of gray and blue collar workers that include registered nurses (RNs), licensed practical nurses (LPNs), and certified nurse assistants (CNAs). The relationship between human resource management (HRM)practices, organizational culture, and nursing staff turnover is examined in underresourced (high Medicaid) nursing homes. Survey data from 348 nursing home administrators (NHAs) of USA high Medicaid (85% or higher) facilities were merged with secondary data sources for 2017–2018. The dependent variables (nursing staff turnover rates) consisted of the percentages of RNs, LPNs, and CNAs that had voluntarily quit the organization during the past year. The independent variables were: (1) HRM practices (employee-centered and high involvement practices); and (2) organizational culture: clan, market, hierarchical, and non-dominant. Organizational and market variables were controlled for. Data were modeled using Poisson log-linear regression, and propensity score weights were used to adjust for potential survey non-response bias. Results show high involvement HRM practices and having a clan culture are associated with lower RN, LPN, and CNA staffing turnover. Study findings suggest that organizational culture and HRM practices may be instrumental in reducing nursing turnover in underresourced nursing homes.

This study aims to investigate the working way of the e-Pulse portal in Türkiye as a sample of a next-generation digital tool for health data management. Accordingly, this study focuses on explaining the structure and key services of the e-Pulse portal in the context of health data management.

This study is a technical paper that will explain how the e-Pulse portal works in Türkiye. Accordingly, the data are based on secondary sources and mostly the official website of the e-Pulse portal. As a sample case, this study investigates the e-Pulse portal from Türkiye. The data are categorized by tables, and some key factors are classified based on review results.

As a result of the review of the e-Pulse portal's sample account, it is seen that the e-Pulse portal provides comprehensive data for personal health data for both individuals and healthcare professionals. By permitting healthcare professionals, users or patients can share their personal health data on specific dates and numbers whenever they need and want. When sharing recorded personal health data, citizens or patients can get more efficient healthcare service on the time.

By giving descriptive evidence and review through the e-Pulse portal, countries with high-populated can see the key e-services and elements to manage health data through digital tools. On the other side, this study has some limitations. This study investigated the e-Pulse portal and its e-services for Türkiye and gave some findings mostly based on subjective deduction. Another digital portal can give different findings for the literature.

Based on the e-Pulse portal case, it is determined that by creating a digital portal with recorded personal up-to-date health data, healthcare services can be ensured more efficiently among high-populated countries in the long term. While population growth and pandemic possibilities such as COVID-19 increase throughout the world, serving more patients with these portals will increase efficiency and service quality, provided that patient information is well protected.

This study reveals key e-services and segments to provide personal health data management by a next-generation digital tool based on the e-Pulse portal. The main contribution of this study is expected to guide other countries when adapting next-generation technology or systems to manage health data in the future.

Flexible pressure sensor arrays have promising applications in analog haptics, reconfiguration of sensory functions, artificial intelligence, wearable devices and human-computer interaction. The force disturbance generated by the connecting material between the sensor array units will reduce the detection accuracy of the unit. The purpose of this paper is to propose a flexible pressure sensor with interference immunity capability. A C-type bridge flexible piezoelectric structure is used to improve the pressure perturbation. The interference immunity capability of the sensor has been improved.

In this paper, a C-type pressure sensor array structure by rapid injection moulding is manufactured through the positive piezoelectric effect of a piezoelectric material. The feasibility of C-type interference immunity structure in a flexible sensor array is verified by further analysis and experiment. A flexible pressure sensor array with C-type interference immunity structure has been proposed.

In this paper, we present the results of the perturbation experiment results of the C-type pressure sensor array, showing that the perturbation error is less than 8%. The test of the flexible sensor array show that the sensor can identify the curved angle of up to 120 °, and the output sensitivity of the sensor in the horizontal state reaches 0.12 V/N, and the sensor can withstand the pressure of 80 N. The flexible sensor can work stably in the stretch rate range of 0–8.6% and the stretch length range of 0–6 mm.

In this paper, C-type pressure sensor array structure is fabricated by rapid injection moulding for the first time. The research in this paper can effectively reduce the disturbance of input pressure on the sensor’s internal array and improve the output accuracy. The sensor can intuitively reflect the number of fingers sliding on the sensor by the order in which the maximum voltage appears. Due to the strong interference immunity capability and flexibility of the flexible sensor array mechanism, it has a broad application prospect in the practical fields of haptic simulation, perceptual function reconstruction, artificial intelligence, wearable devices and human–computer interaction.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Ubiquitous health-care monitoring systems can provide continuous surveillance to a person using various sensors, including wearables and implantable and fabric-woven sensors. By assessing the state of many physiological characteristics of the patient’s body, continuous monitoring can assist in preparing for the impending emergency. To address this issue, this study aims to propose a health-care system that integrates the treatment of the impending heart, stress and alcohol emergencies. For this purpose, this study uses readings from sensors used for electrocardiography, heart rate, respiration rate, blood alcohol content percentage and blood pressure of a patient’s body.

For heart status, stress level and alcohol detection, the parametric values obtained from these sensors are preprocessed and further divided into four, five and six phases, respectively. A final integrated emergency stage is derived from the stages that were interpreted to examine at a person’s state of emergency. A thorough analysis of the proposed model is carried out using four classification techniques, including decision trees, support vector machines, k nearest neighbors and ensemble classifiers. For all of the aforementioned detections, four metrics are used to evaluate performance: classification accuracy, precision, recall and fmeasure.

Eventually, results are validated against the existing health-care systems. The empirical results received reveal that the proposed model outperforms the existing health-care models in the context of metrics above for different detections taken into consideration.

This study proposes a health-care system capable of performing data processing using wearable sensors. It is of great importance for real-time systems. This study assures the originality of the proposed system.

The purpose of this paper is to optimize the key parameters (mesh count, paper type and ink type) in screen printing, which are affecting the printed ink volume. The objective of the optimization was to maximize the color reliability by decreasing the color difference (ΔE value) of the prints while minimizing the ink consumption. Screen printing is still dominating the printing industry to make cost-effective production when high volumes are needed.

The experiment was designed using the Taguchi method, and the samples were prepared with screen-printing by using the standard squeegee angle and pressure. The effect of mesh count, ink type and paper type on ink consumption was evaluated with using analysis of variances and main effects plots of S/N ratio and standard deviation.

The factors ink type, paper type and mesh count were found significant for ink consumption due to their Probability (P) values which were lower than 0.05. It was determined that the mesh count was the most critical variable with the analysis of variance. The analysis showed that the selection of an optimum mesh count was the key to controlling the amount of the deposited ink. Although mesh counts were inversely proportional with the ink consumptions, they did not affect the color differences as expected.

The optimization of process parameters, that are most effective on the print quality, is necessary to minimize the ink usage and lower the costs and environmental impact without exceeding the desired ΔE value limits.

The purpose of this research is to analyze consumers’ post-purchase reviews of the Owlet Smart Sock (OSS) and investigate the factors influencing continued use and product recommendation.

The unified theory of acceptance and use of technology 2 and the privacy calculus model were used to focus both on technology and privacy aspects of OSS – a wearable technology product for baby monitoring. A sample of 450 online consumer review data was collected from Owletcare.com and Amazon.com. The data analysis was done by using NVivo 11.

Findings show that effort expectancy, price value and performance expectancy played the most striking role during adoption, continued future use and recommendation to others, whereas perceived privacy risk had the least importance.

Consumer empowerment through online reviews plays a crucial role in conveying their specific needs and desires to both manufacturers and other prospective consumers. The research is also expected to contribute research and development of technology-integrated products.

The research findings will provide valuable insights for manufacturers and retailers to understand consumers’ actual preferences and acceptance during the use of wearable technology.

This study extends research work on consumer use behavior by evaluating online reviews that provide them the opportunity to express their satisfaction and concerns. Insights from experience consumers’ reviews facilitate designers, developers and manufacturers to have a strategic focus during wearable technology development.