Search Results (1,004)

Stroke is a significant global health concern characterized by the abrupt disruption of cerebral blood flow, leading to neurological impairment. Accurate and timely diagnosis—enabled by imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI)—is essential for differentiating stroke types and initiating interventions like thrombolysis, thrombectomy, or surgical management. In parallel, recent advancements in wearable technology, particularly smart clothing, offer new opportunities for stroke prevention, real-time monitoring, and rehabilitation. These garments integrate various sensors, including electrocardiogram (ECG) electrodes, electroencephalography (EEG) caps, electromyography (EMG) sensors, and motion or pressure sensors, to continuously track physiological and functional parameters. For example, ECG shirts monitor cardiac rhythm to detect atrial fibrillation, smart socks assess gait asymmetry for early mobility decline, and EEG caps provide data on neurocognitive recovery during rehabilitation. These technologies support personalized care across the stroke continuum, from early risk detection and acute event monitoring to long-term recovery. Integration with AI-driven analytics further enhances diagnostic accuracy and therapy optimization. This narrative review explores the application of smart clothing in conjunction with traditional imaging to improve stroke management and patient outcomes through a more proactive, connected, and patient-centered approach. Full article

The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery Management Systems (BMS). This review paper explores how artificial intelligence (AI) and digital twin (DT) technologies can be integrated to enable the intelligent BMS of the future. It investigates how powerful data approaches such as deep learning, ensembles, and models that rely on physics improve the accuracy of predicting state of charge (SOC), state of health (SOH), and remaining useful life (RUL). Additionally, the paper reviews progress in AI features for cooling, fast charging, fault detection, and intelligible AI models. Working together, cloud and edge computing technology with DTs means better diagnostics, predictive support, and improved management for any use of EVs, stored energy, and recycling. The review underlines recent successes in AI-driven material research, renewable battery production, and plans for used systems, along with new problems in cybersecurity, combining data and mass rollout. We spotlight important research themes, existing problems, and future drawbacks following careful analysis of different up-to-date approaches and systems. Uniting physical modeling with AI-based analytics on cloud-edge-DT platforms supports the development of tough, intelligent, and ecologically responsible batteries that line up with future mobility and wider use of renewable energy. Full article

The rapidly changing dynamics of the digital age reshape the addiction relationship that high school students establish with technology. While smartphones remove boundaries in terms of communication and access to information, their usage triggers a source of anxiety and nomophobia. The increase in students’ anxiety levels because of their over-reliance on mobile phone use leads to significant behavioral changes in their mental health, academic performance, social interactions and financial dependency. This study examined the nomophobia levels of high school students according to selected socio-demographic indicators. Using the relational screening model, the multistage sampling technique was used to select a sample of 884 participants: 388 from Science High School and 496 from Anatolian High School (459 female, 425 male, Mage = 16.45 ± 1.14 year). Independent sample test and One-way ANOVA were applied. Depending on the homogeneity assumption of the data, Welch values were considered, and Tukey tests were applied as a second-level test from post hoc analyses. Comprehensive analyses of nomophobia levels revealed that young individuals’ attitudes towards digital technology differ significantly according to their demographic and behavioral characteristics. Variables such as gender, physical activity participation, grade level and duration of smartphone use are among the main factors affecting nomophobia levels. Female individuals and students who do not participate in physical activity exhibit higher nomophobia scores. Full article

The incorporation of digital health into the medical curricula is becoming more important to better prepare doctors in the future. Digital health comprises a wide range of tools such as electronic health records, health information technology, telemedicine, telehealth, mobile health applications, wearable devices, artificial intelligence, and virtual reality. The present study aimed to explore the medical and biomedical students’ perspectives on the integration of digital health in medical curricula. A cross-sectional study was conducted on the medical and biomedical undergraduate students at the College of Medicine and Health Sciences at Sultan Qaboos University. Data was collected using a self-administered questionnaire. The response rate was 37%. The majority of respondents were in the MD (Doctor of Medicine) program (84.4%), while 29 students (15.6%) were from the BMS (Biomedical Sciences) program. A total of 55.38% agreed that they were familiar with the term ‘e-Health’. Additionally, 143 individuals (76.88%) reported being aware of the definition of e-Health. Specifically, 69 individuals (37.10%) utilize e-Health technologies every other week, 20 individuals (10.75%) reported using them daily, while 44 individuals (23.66%) indicated that they never used such technologies. Despite having several benefits, challenges exist in integrating digital health into the medical curriculum. There is a need to overcome the lack of infrastructure, existing educational materials, and digital health topics. In conclusion, embedding digital health into medical curricula is certainly beneficial for creating a digitally competent healthcare workforce that could help in better data storage, help in diagnosis, aid in patient consultation from a distance, and advise on medications, thereby leading to improved patient care which is a key public health priority. Full article

Water systems serve as multifaceted environmental pools for antibiotic-resistant bacteria (ARB) and resistance genes (ARGs), influencing human, animal, and ecosystem health. This review synthesizes current understanding of how antibiotics, ARB, and ARGs enter surface, ground, and drinking waters via wastewater discharge, agricultural runoff, hospital effluents, and urban stormwater. We highlight key mechanisms of biofilm formation, horizontal gene transfer, and co-selection by chemical stressors that facilitate persistence and spread. Case studies illustrate widespread detection of clinically meaningful ARB (e.g., Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae) and mobile ARGs (e.g., sul1/2, tet, bla variants) in treated effluents, recycled water, and irrigation return flows. The interplay between treatment inefficiencies and environmental processes underscores the need for advanced treatment technologies, integrated monitoring, and policy interventions. Addressing these challenges is critical to curbing the environmental dissemination of resistance and protecting human and ecosystem health. Full article

Background: Type 2 diabetes (T2D) and overweight or obesity are strongly associated, with a high prevalence of these concomitant conditions contributing significantly to global healthcare costs. Given this burden, there is an urgent need for effective interventions. Mobile health (mHealth) technologies represent a promising strategy to address both conditions simultaneously. Objectives: This systematic review and meta-analysis aimed to evaluate the effectiveness of mHealth-based interventions for the management of adults with T2D and overweight/obesity. Specifically, it assessed the quantitative impact of these interventions on glycosylated hemoglobin (HbA1c), body weight, triglycerides, total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) levels. Methods: A systematic search was conducted in PubMed, Web of Science, and Scopus databases from inception to 9 July 2025. The inclusion criteria focused on randomized controlled trials (RCTs) using mHealth interventions in adults with T2D and overweight/obesity, reporting HbA1c or weight as primary or secondary outcomes. The risk of bias was assessed using the Cochrane Risk of Bias tool 2. A total of 13 RCTs met the inclusion criteria. Results: Meta-analysis indicated significant improvements after 6–12 months of intervention in HbA1c (MD −0.23; 95% CI −0.36 to −0.10; p < 0.001; I² = 72%), body weight (MD −2.47 kg; 95% CI −3.69 to −1.24; p < 0.001; I² = 79%), total cholesterol (MD −0.23; 95% CI −0.39 to −0.07; p = 0.004; I² = 0%), and LDL (MD −0.27; 95% CI −0.42 to −0.12; p < 0.001; I² = 0%). Conclusions: mHealth interventions are effective and scalable for managing T2D and obesity, particularly when incorporating wearable technologies to improve adherence. Future research should focus on optimizing personalization, engagement strategies, and long-term implementation. Full article

Introduction: Adolescents and young adults (AYAs), especially those from underserved communities, often face barriers to sexual and reproductive health (SRH). This pilot study evaluated the implementation of mobile health technologies to promote SRH care, including the integration of the Rapid Adolescent Prevention Screening^TM (RAAPS) and the Health-E You/Salud iTu^TM (Health-E You) app at a School-Based Health Center (SBHC) in Los Angeles using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework. Methods: This multi-method pilot study included the implementation of an integrated tool with two components, the RAAPS electronic health screening tool and the Health-E You app, which delivers tailored SRH education and contraceptive decision support to patients (who were sex-assigned as female at birth) and provides an electronic summary to clinicians to better prepare them for the visit with their patient. Quantitative data on tool usage were collected directly from the back-end data storage for the apps, and qualitative data were obtained through semi-structured interviews and in-clinic observations. Thematic analysis was conducted to identify implementation barriers and facilitators. Results: Between April 2024 and June 2024, 60 unique patients (14–19 years of age) had a healthcare visit. Of these, 35.00% used the integrated RAAPS/Health-E You app, and 88.33% completed the Health-E You app only. All five clinic staff were interviewed and expressed that they valued the tools for their educational impact, noting that they enhanced SRH discussions and helped uncover sensitive information that students might not disclose face-to-face. However, the tools affected clinic workflows and caused rooming delays due to the time-intensive setup process and lack of integration with the clinic’s primary electronic medical record system. In addition, they also reported that the time to complete the screener and app within the context of a 30-min appointment limited the time available for direct patient care. Additionally, staff reported that some students struggled with the two-step process and did not complete all components of the tool. Despite these challenges, clinic staff strongly supported renewing the RAAPS license and continued use of the Health-E You app, emphasizing the platform’s potential for improving SRH care and its educational value. Conclusions: The integrated RAAPS and Health-E You app platform demonstrated educational value and improved SRH care but faced operational and technical barriers in implementing the tool. These findings emphasize the potential of such tools to address SRH disparities among vulnerable AYAs while providing a framework for future implementations in SBHCs. Full article

Radio frequency (RF)-based wireless systems are broadly used in communication systems such as mobile networks, satellite links, and monitoring applications. These systems offer outstanding advantages over wired systems, particularly in terms of ease of installation. However, researchers are looking for safer alternatives as a result of worries about possible health problems connected to high-frequency radiofrequency transmission. Using the visible light spectrum is one promising approach; three cutting-edge technologies are emerging in this regard: Optical Camera Communication (OCC), Light Fidelity (Li-Fi), and Visible Light Communication (VLC). In this paper, we propose a Multiple-Input Multiple-Output (MIMO) modulation technology for Internet of Things (IoT) applications, utilizing an LED array and time-domain on-off keying (OOK). The proposed system is compatible with both rolling shutter and global shutter cameras, including commercially available models such as CCTV, webcams, and smart cameras, commonly deployed in buildings and industrial environments. Despite the compact size of the LED array, we demonstrate that, by optimizing parameters such as exposure time, camera focal length, and channel coding, our system can achieve up to 20 communication links over a 20 m distance with low bit error rate. Full article

Total Knee Arthroplasty (TKA) is a well-established surgical intervention for the management of end-stage knee osteoarthritis. While the procedure is generally successful, postoperative rehabilitation remains a key determinant of long-term functional outcomes. Traditional rehabilitation protocols, particularly those requiring in-person clinical visits, often encounter limitations in accessibility, patient adherence, and personalization. In response, emerging sensor technologies have introduced innovative solutions to support and enhance recovery following TKA. This review provides a thematically organized synthesis of the current landscape and future directions of sensor-assisted rehabilitation in TKA. It examines four main categories of technologies: wearable sensors (e.g., IMUs, accelerometers, gyroscopes), smart implants, pressure-sensing systems, and mobile health (mHealth) platforms such as ReHub^® and BPMpathway. Evidence from recent randomized controlled trials and systematic reviews demonstrates their effectiveness in tracking mobility, monitoring range of motion (ROM), detecting gait anomalies, and delivering real-time feedback to both patients and clinicians. Despite these advances, several challenges persist, including measurement accuracy in unsupervised environments, the complexity of clinical data integration, and digital literacy gaps among older adults. Nevertheless, the integration of artificial intelligence (AI), predictive analytics, and remote rehabilitation tools is driving a shift toward more adaptive and individualized care models. This paper concludes that sensor-enhanced rehabilitation is no longer a future aspiration but an active transition toward a smarter, more accessible, and patient-centered paradigm in recovery after TKA. Full article

The air quality within urban public transport is a critical determinant of passenger health. In the crowded and poorly ventilated cabins of Almaty’s metro, buses, and trolleybuses, concentrations of CO₂ and PM_2.5 often accumulate, elevating the risk of respiratory and cardiovascular diseases. This study investigates the air quality along three of the city’s busiest transport corridors, analyzing how the concentrations of CO₂, PM_2.5, and PM₁₀, as well as the temperature and relative humidity, fluctuate with the passenger density and time of day. Continuous measurements were collected using the Tynys mobile IoT device, which was bench-calibrated against a commercial reference sensor. Several machine learning models (logistic regression, decision tree, XGBoost, and random forest) were trained on synchronized environmental and occupancy data, with the XGBoost model achieving the highest predictive accuracy at 91.25%. Our analysis confirms that passenger occupancy is the primary driver of in-cabin pollution and that these machine learning models effectively capture the nonlinear relationships among environmental variables. Since the surveyed routes serve Almaty’s most densely populated districts, improving the ventilation on these lines is of immediate importance to public health. Furthermore, the high-temporal-resolution data revealed short-term pollution spikes that correspond with peak ridership, advancing the current understanding of exposure risks in transit. These findings highlight the urgent need to combine real-time monitoring with ventilation upgrades. They also demonstrate the practical value of using low-cost IoT technologies and data-driven analytics to safeguard public health in urban mobility systems. Full article

Obesity is a global epidemic with substantial health and economic impacts, making scalable weight management strategies essential. A comprehensive synthesis of eHealth interventions for weight management is needed to guide clinical practice. This umbrella review evaluated mobile and web-based interventions for weight loss in adults with overweight or obesity, compared to conventional or non-intervention controls. Systematic reviews were identified across five electronic databases from inception to February 2025. Two reviewers independently selected studies and assessed methodological quality using AMSTAR 2. Pooled estimates were calculated using random-effects models. Eleven systematic reviews (261 primary studies, 62,407 participants) were included. Mobile app interventions yielded a significant reduction in body weight (MD = −1.32 kg; I² = 82%), as did long-term eHealth interventions (MD = −1.13 kg; I² = 76%). Most meta-analyses showed high heterogeneity. Web-based interventions showed no significant effect. In conclusion, mobile apps and long-term eHealth interventions resulted in modest but statistically significant reductions in body weight, body mass index, and waist circumference. The evidence for web-based approaches remains inconclusive. Further research should focus on low-resource settings, primary care, and the integration of emerging technologies such as artificial intelligence. (PROSPERO CRD42025644218). Full article

Background: Standing has medical and psychosocial benefits for people with lower limb impairments; however, systemic, logistical, and economic barriers often limit opportunities to stand in daily life. This study explored how users perceive standing and standing-assistive technologies. Methods: This study used a mixed-methods approach: in-person interviews (n = 18) and a nationwide web-based survey (n = 125; 74.4% male, mean age 52.2 ± 13.9 years, diagnoses: spinal cord injury 37.6%, cerebrovascular disease 27.2%, and cerebral palsy 16.8%). Results: Participants described the psychosocial values of standing, such as feeling more confident and being able to interact with others at eye level. The web survey revealed that most participants believed that standing was beneficial for health (76.8%) and task efficiency (76.0%), although only 49.6% showed an interest in standing wheelchairs. The multivariate analysis revealed that ongoing standing training was the strongest predictor of positive perceptions of health benefits, task efficiency, and interest in standing wheelchairs. Younger participants showed a greater interest in standing wheelchairs. The reported barriers include a lack of awareness, high costs, and difficulty in accessing training. Conclusions: These findings suggest the need for a user-centered design and improved support systems to integrate standing into the daily lives of people with mobility impairments. Full article

Assessing a city’s level of smartness according to global indices is a relatively new area of investigation. It is useful in encouraging a rethinking of urban digital strategies, although the different approaches to global smart city rankings have been subject to criticism. This paper highlights the methodological features of constructing the Smart City Index (SCI) from the IMD (International Institute for Management Development) based on residents’ assessments, their satisfaction with electronic services, and their perception of the priority of urban infrastructure areas. The Central European cities of the Visegrad region (Prague/Czech Republic, Budapest/Hungary, Bratislava/Slovakia, Warsaw and Krakow/Poland) were chosen as the basis for an in-depth analysis. The architectonics, i.e., the internal system of constructing and calculating city rankings by SCI, is analyzed. A comparative analysis of the technology indicators (e-services) in five cities of the Visegrad region, presented in the SCI, showed the smart features of each city. The progressive and regressive trends in the dynamics of smartness in the cities in the Visegrad region were identified in five urban spheres indicated in the Index: Government, Activity, Health and Safety, Mobility, and Opportunities. This also made it possible to identify certain methodological gaps in the SCI in establishing interdependencies between the data on the residents’ perception of the priority of areas of life in a particular city and the residents’ level of satisfaction with electronic services. In particular, the structural indicators “Affordable housing” and “Green spaces” are not supported by e-services. This research aims to bridge this methodological gap by proposing a model for evaluating the e-service according to the degree of coverage of different spheres of life in the city. The application of the project, as well as cross-sectoral and systemic approaches, made it possible to develop basic models for assessing the value of e-services. These models can be implemented by municipalities to assess and monitor e-services, as well as to select IT projects and elaborate strategies for smart sustainable city development. Full article

In Korea, the Public Health Center Mobile Healthcare Project was implemented in 2016. This project utilizes Information and Communication Technology (ICT) and big data to establish a health-related service foundation and a healthcare service operation system. Equipment and methods: This study recruited 1261 adolescents (660 males (13.40 ± 1.14 years, 156.12 ± 10.59 cm) and 601 females (13.51 ± 1.23 years, 154.45 ± 7.48 cm)) from 22 public health centers nationwide. Smart bands were provided, and the ‘Future Health’ application (APP) was installed on personal smartphones to assess body composition, physical fitness, and physical activity. Results: A paired sample t-test revealed height, 20 m shuttle run, grip strength, and long jump scores significantly differed after 24 weeks in males. Females exhibited significant height, 20 m shuttle run, grip strength, sit-ups, and long jump differences. Moderate physical activity (MPA, p < 0.001), vigorous physical activity (VPA, p < 0.001), and moderate-to-vigorous physical activity (MVPA, p < 0.001) were significantly different after 24 weeks in adolescents. These results establish that an ICT-based health promotion service can provide adolescent students with individual information from a centralized organization to monitor health behaviors and receive feedback regardless of location in South Korea. Full article

Per- and polyfluoroalkyl substances (PFAS) have been reported to contaminate soil as a result of improper management of waste, wastewater, landfill leachate, biosolids, and a large and indiscriminate use of aqueous film-forming foams (AFFF), posing potential risks to human health. However, their high chemical and thermal stability pose a great challenge for remediation. As a result, there is an increasing interest in identifying and optimizing very effective and sustainable technologies for PFAS removal. This review summarizes both traditional and innovative remediation strategies and technologies for PFAS-contaminated soils. Unlike existing literature, which primarily focuses on the effectiveness of PFAS remediation, this review critically discusses several techniques (based on PFAS immobilization, mobilization and extraction, and destruction) with a deep focus on their sustainability and scalability. PFAS destruction technologies demonstrate the highest removal efficiencies; however, thermal treatments face sustainability challenges due to high energy demands and potential formation of harmful by-products, while mechanical treatments have rarely been explored at full scale. PFAS immobilization techniques are less costly than destruction methods, but issues related to the regeneration/disposal of spent sorbents should be still addressed and more long-term studies conducted. PFAS mobilization techniques such as soil washing/flushing are hindered by the generation of PFAS-laden wastewater requiring further treatments, while phytoremediation is limited to small- or medium-scale experiments. Finally, bioremediation would be the cheapest and least impactful alternative, though its efficacy remains uncertain and demonstrated under simplified lab-scale conditions. Future research should prioritize pilot- and full-scale studies under realistic conditions, alongside comprehensive assessments of environmental impacts and economic feasibility. Full article