Search Results (5,639)

Context: Different studies on football players with fifth metatarsal stress fractures have found that hip internal rotation (HIR)range of motion is significantly reduced, while lateral forefoot pressure is significantly increased; therefore, the purpose of this study was to determine whether HIR range of motion is related to lateral plantar pressure. Methods: The study included 120 college students (60 males and 60 females). HIR was measured using a smartphone inclinometer app in the prone position and a compass app in the supine position. Plantar pressure was assessed using the Gaitview AFA-50 system during standing and walking. Correlation analysis was performed using SPSS 27.0. Results: Among all subjects, HIR activity in the prone position was significantly negatively correlated with standing second through fourth metatarsophalangeal joints(MTPJ2-4), fifth metatarsophalangeal joint (MTPJ5), and midfoot (FM)pressures and significantly positively correlated with standing first toe (T1)pressure. During walking, there is a significant negative correlation between HIR in the prone position and MTPJ2-4, MTPJ5, FM, and lateral heel (LH). Similarly, in the supine position, HIR is significantly negatively correlated with MTPJ2-4, MTPJ5, FM, medial heel (MH), and LH. Conclusion: There is a significant negative correlation between HIR and lateral plantar pressure, indicating that reduced HIR is associated with increased lateral plantar pressure. Improving HIR through targeted rehabilitation may reduce lateral plantar pressure, offering new approaches for non-surgical treatment of little toe capsulitis and reducing the risk of fifth metatarsal stress fractures. Full article

Detecting non-line-of-sight (NLOS) signals is essential for improving the accuracy and reliability of smartphone Global Navigation Satellite System (GNSS) positioning in dense urban areas. This paper presents a practical method for NLOS detection based on skymasks derived from smartphone observations. The observable rates of satellite observation series are first computed using precise ephemeris, and the observations are then classified into blocked and unblocked groups. A smoothing spline is then applied to fit the building boundary from the categorized series. Based on the fitted boundary, a skymask is constructed and used for NLOS detection. Datasets collected at three locations using three different smartphones are used for validation. The results show that both the number and proportion of NLOS signals decrease significantly after applying the proposed method. As the degree of obscuration increases, the detection accuracy remains stable across different smartphones. In some cases, single-point positioning accuracy is improved after excluding NLOS signals. In addition, the derived skymask can be used to estimate sky visibility and support the selection of positioning strategies. Overall, the proposed method can be combined with the consistency checking method for NLOS detection, as it does not require additional information. Full article

Shooting activities offer educational and recreational value; however, their application in school physical education and recreational settings remains limited due to safety concerns, high costs, and restricted access to specialized facilities and equipment. To address these constraints, this study designed and implemented a low-cost laser shooting system suitable for school physical education and recreational use. The proposed system comprises a laser-gun module, a physical electronic target providing immediate on-site feedback using an illuminance sensor, a Fresnel lens, and RGB LEDs, and a web-based electronic target that enables real-time scoring, logging, and visualization via smartphone or tablet cameras and browser-based processing. By adopting a low-power, projectile-free laser structure with pulse-limited emission, the system enhances operational safety, while the use of general-purpose components and web standards reduces cost and lowers barriers to adoption. Technical verification conducted under controlled indoor conditions demonstrated stable single-shot operation, reliable hit detection, and accurate score calculation for both the physical and web-based targets. Expert validation involving specialists in physical education, educational technology, and sports technology yielded consistently high evaluations across safety, cost efficiency, functional completeness, and field applicability. These findings suggest that the proposed system represents a practical and scalable alternative for school physical education classes and recreational programs. Future research should examine user-level usability, learning outcomes, system robustness under diverse environmental conditions, and structured expert consensus processes. Full article

Serious games and negotiation simulations such as the Phosphorus Negotiation Game (P-Game) are increasingly used to support sustainability-oriented education. To broaden accessibility, a smartphone-based version of the face-to-face P-Game was developed and is presented here. A comparative design integrating quantitative pre–post survey measures with analysis of open-ended responses was employed to examine self-reported knowledge gains and learning experiences among participants who completed the P-Game in face-to-face workshops and those who played the virtual version. Both formats were associated with significant increases in participants’ perceived understanding of phosphorus science and negotiation science/practice. Self-reported knowledge of phosphorus science increased by 92.3% (global face-to-face), 70.7% (Hungarian face-to-face), and 88.4% (online), with comparable gains observed in negotiation science and practice across groups. Qualitative findings complemented these results, indicating that while learning gains were broadly similar, the modes differed in experiential emphasis: face-to-face delivery elicited performance-oriented and socially embedded reflections, whereas the online format was more frequently described in terms of structured participation and reflective processing. User satisfaction with the virtual P-Game was high, reflected by a System Usability Scale (SUS) score above 80. Overall, the findings suggest that the virtual P-Game represents a viable and accessible complement to traditional face-to-face implementation, maintaining educational impact while extending reach. Further research with larger and more diverse participant samples is recommended to strengthen generalizability and explore long-term learning outcomes in sustainability contexts. Full article

Background/Objectives: Excessive smartphone use has emerged as an important behavioral health concern during adolescence, a developmental period characterized by heightened psychosocial vulnerability. This study aimed to identify psychosocial and behavioral factors associated with excessive smartphone use among Korean adolescents using nationally representative data. Methods: Data were obtained from the 2024 Korean Youth Risk Behavior Web-based Survey (KYRBS), including 54,653 adolescents. Excessive smartphone use was operationally defined as average daily smartphone use of ≥300 min. Multivariable logistic regression was conducted to examine associated factors. An exploratory machine learning analysis using a Light Gradient Boosting Machine included 52,450 participants with complete predictor data. Results: Female sex, higher grade level, lower perceived socioeconomic status, higher perceived daily stress, higher anxiety symptoms, poorer sleep-related recovery, suicidal ideation, and more frequent vigorous physical activity were associated with higher odds of excessive smartphone use. The supplementary modeling approach showed patterns consistent with the regression findings, with grade level, socioeconomic status, and sex contributing prominently. Vigorous physical activity demonstrated a nonlinear association with predicted risk. Conclusions: Excessive smartphone use among adolescents appears to be shaped by developmental stage, socioeconomic context, and psychological vulnerability. These findings support prevention strategies that address emotional well-being and sleep health alongside broader structural and school-based approaches. Full article

(1) Background: Idiopathic scoliosis is a three-dimensional deformity, yet clinical and research decision-making still relies largely on radiographic Cobb angle measurements. As a radiation-free alternative, clinical assessment of transverse and sagittal plane deformities has gained importance. This study evaluated the concurrent validity and intra- and interrater reproducibility of continuous measurements of rib hump, thoracic kyphosis, and lumbar lordosis obtained using a smartphone application in adolescents with spinal deformities. (2) Methods: Adolescents aged 10–17 years with scoliosis (>10° Cobb) or hyperkyphosis (>50° Cobb) were recruited. Continuous measurements of angle of trunk rotation (ATR) during the Adams forward bend test and in standing position, as well as sagittal profile, were collected using the ISICO app mounted on a standardized plastic tool. Concurrent validity was assessed against a scoliometer using Spearman correlation, root mean square error, and Bland–Altman analysis, while reproducibility was evaluated using intraclass correlation coefficients, standard error of measurement, and minimal detectable change. (3) Results: Thirty-two adolescents were included for validation and intrarater analyses and 34 for interrater analyses. ATR measured during the Adams test showed very high correlation with the scoliometer and minimal bias, while standing ATR showed moderate correlation. Reliability was excellent for rib hump during forward bending and moderate for sagittal parameters, with the lowest values observed for lumbar lordosis. (4) Conclusions: These findings support the clinical use of continuous app-based ATR assessment and suggest that sagittal measurements may be useful with appropriate examiner training. Full article

The detection of surface defects on smartphone components is a critical step in quality assurance for industrial manufacturing. However, existing deep learning-based methods struggle with the extreme variations in defect morphology and scale, while labeled training data remains scarce due to the high cost of expert annotation. To address these challenges, we propose a twofold solution. First, we introduce MSAdaNet, a Multi-Scale Adaptive Defect Detection Network, which integrates three novel modules: a Parallel Multi-Scale Feature Aggregation (PMSFA) backbone, a Focusing Diffusion Pyramid Network (FDPN) neck, and a Scale-Adaptive Shared Detection (SASD) head. Second, to combat data scarcity, we propose a novel data generation pipeline, creating the synthetic Smartphone Camera Bezel Dataset (SCBD) of 4936 images. Extensive experiments on both real-world and synthetic datasets validate our approach. On the challenging public SSGD, MSAdaNet achieves a state-of-the-art mAP@0.5 of 54.8%, outperforming prominent frameworks and improving upon the strong YOLOv11m baseline by +10.6 points in mAP@0.5 and +18.3 points in recall. Furthermore, on our synthetic SCBD, the model achieves an impressive 94.0% mAP@0.5, confirming the quality of our data generation pipeline and the robustness of our architecture across different data distributions. Ablation studies systematically confirm the significant contribution of each proposed module, validating MSAdaNet as an effective and efficient solution for industrial defect detection. Full article

Background/Objectives: The mediating role of the diverse range of screen-based sedentary behaviors (SBs) remains understudied, particularly at younger ages. The present study examined the direct and indirect effects of parental BMI and education on ultra-processed food (UPF) consumption among preschoolers, testing the potential mediating role of screen time. Methods: The cross-sectional study sample comprised 919 kindergarten children (484 boys, 52.7%), with ages ranging from 2.2 to 6.8 years (mean: 4.7 ± 1.0 years). Screen-based sedentary behaviors (television viewing, smartphone use, tablet use, computer use, and playing electronic games) were measured by proxy-report fulfilled by parents, separately for weekdays and weekends. UPF consumption (drinks/yogurts, packaged/fast foods, and sweet/salty snacks) was assessed via 24 h recall scales. Path analysis mediation models tested direct effects of maternal/paternal BMI and education on UPF intake, and indirect effects through screen time, controlling for child age and sex. Results: Lower parental education and higher parental BMI were associated with increased mobile device use and UPF consumption (r = 0.10–0.28). Screen-based sedentary behaviors mediated the association between maternal BMI and UPF pathways (15–90% of total effects), particularly for sweet and salty snacks (50–90%). Parental education effects were also mediated by screen time (9–23% indirect effects), with paternal education showing stronger protection against packaged/fast foods. Conclusions: Mobile devices and watching television partially mediate intergenerational transmission of obesogenic dietary patterns from parental BMI/education to preschoolers’ UPF consumption. Findings of the current study support family-centered interventions targeting screen-time limits and UPF exposure, mainly at the weekends, to prevent early obesity trajectories. Full article

This scoping review summarizes current computational image analysis and artificial intelligence (AI) approaches for the assessment of hair and scalp disorders, with emphasis on quantitative trichoscopy and operator-independent evaluation. A deep Medline search was performed using a citation network-based approach using MeSH terms and complementary keywords covering diagnostic imaging, trichoscopy/videodermoscopy, image processing, algorithms, AI, and mobile/smartphone-based workflows. Overall, relatively few studies assess algorithms in real-world clinical pathways, and much of the retrieved literature is predominantly pre-clinical or methodology-driven. In parallel, commercially available AI-assisted trichoscopy platforms have little or no traceable peer-reviewed evidence; their validation methods and underlying datasets are often proprietary, undisclosed, and not directly comparable, limiting independent verification and cross-platform benchmarking. The most mature academic applications focus on follicular unit quantification (hair density, shaft diameter distribution, vellus-to-terminal ratio, and severity mapping), mainly using convolutional neural networks with object detection and instance segmentation. In conclusion, AI-assisted trichoscopy may support a shift toward standardized quantitative outputs, but clinical translation remains early and constrained by small or proprietary datasets, heterogeneous acquisition/annotation protocols, limited external validation, and scarce prospective studies. Full article

(1) Background: The local divergence exponent (LDE) is a sensitive measure of walking stability deterioration and risk of falling in older adults. We aim to determine the validity the LDE measured using a mobile phone and to assess its ability to discriminate between healthy young and older adults; (2) Methods: 20 older adults (76.4 ± 4.6 years) and 20 young adults (29.1 ± 6.5 yrs) walked for 6 min on a 20-m walkway while wearing a research-grade inertial measurement unit (IMU) and a mobile phone placed on the sternum to record 3D acceleration data. The LDE was calculated using data from both devices for 3D, vertical (VT), mediolateral (ML), anteroposterior (AP), and norm (N) accelerations. ICC (3,1) was used to determine the validity of the mobile phone’s LDE. Mann–Whitney U tests were used to determine age-group discriminability of LDE measures; (3) Results: LDEs demonstrated excellent absolute agreement between the wearable IMU and mobile phone (ICC = 0.844). Mobile phone-derived LDEs demonstrated excellent validity relative to the wearable IMU (ICC > 0.75). No significant age-related differences in LDE were observed; wearable or mobile sensors (both p > 0.05); (4) Conclusions: LDEs measures obtained with a mobile phone are valid. No age group differences were identified. Full article

This paper introduces a compact sub-6 GHz multiple-input multiple-output (MIMO) antenna array developed for 5G smartphone applications. The design employs eight planar inverted-F antenna (PIFA) elements arranged to realize dual-band and dual-polarized operation. The antenna achieves impedance bandwidths of 3.3–3.7 GHz (11.4%) and 5.3–5.8 GHz (10%), covering key sub-6 GHz fifth-generation (5G) bands. To enhance diversity performance, the elements are distributed along the edges of the smartphone mainboard, enabling excitation of orthogonal polarization modes while maintaining an overall board size of 75 mm × 150 mm on an FR4 substrate. Even without the use of dedicated decoupling structures, the closely spaced antenna elements exhibit satisfactory isolation levels, varying between −12 dB and −22 dB across the operating bands. The antenna array achieves wide impedance bandwidths of approximately 400 MHz at 3.5 GHz and more than 500 MHz at 5.5 GHz, supporting high data-rate communication. In addition, the proposed system demonstrates very low correlation and active reflection, with envelope correlation coefficient (ECC) values below 0.002 and total active reflection coefficient (TARC) levels better than −20 dB. User interaction effects are also investigated, and the results confirm acceptable SAR levels and stable radiation behavior in the presence of the human body. Owing to its planar, dual-band/dual-polarization capability and compliance with safety requirements, the proposed antenna represents a promising practical solution for contemporary 5G handheld devices and future multi-band mobile platforms. Full article

Accurately monitoring physical activity, including stationary cycling on an exercise bike, is important in managing chronic diseases and rehabilitation after lower limb surgery. This study aimed to validate a new smartphone-based sensor application (the BeSAFE+) for activity recognition and step counting across five phone placements, using the SENS Motion^® system as a reference standard, and observed activity time as ground truth. In a laboratory-based study, 20 participants performed walking, brisk walking, running, high- and low-intensity cycling, sitting, standing, and lying activities while carrying five smartphones placed in the front and back trouser pockets, a backpack, a running armband, and a fanny pack, and wearing the activity tracker. The front pocket placement had the most accurate classification during cycling activities (89–93%) versus SENS Motion^® (96–98%). For other activities, the highest overall classification accuracy was achieved with the phone in the back pocket. Overall, the SENS Motion^® activity tracker demonstrated higher classification accuracy than most smartphone placements across all activities, except for running. Nevertheless, several smartphone placements and Application Programming Interface (API) approaches achieved activity recognition and step count estimates that were not significantly different from the SENS Motion^® activity tracker, indicating that smartphone-based activity recognition can be valid under specific conditions. Full article

The unchecked and uncontrolled global spread of multidrug-resistant (MDR) bacteria is a serious challenge to healthcare and modern medicine, and demands diagnostic approaches that are rapid, sensitive, multiplexed, and reliable in point-of-care (POC) settings. At the interface of nanomaterials and aptamer-based biosensing, significant advances have been reported. The convergence of portable electrochemical sensing technologies, smartphone-based readout systems, and artificial intelligence (AI)- and machine learning (ML)-based data analysis is also playing a significant role in advancing this area. This perspective reflects on the most recent breakthroughs and translational developments in electrochemical nano-aptasensors for MDR bacterial detection, covering diagnostic targets and translation trends, nanomaterials advancements, aptamer engineering-integration, POC strategies and microfluidics platforms, and novel multimodal strategies that enhance accuracy, reliability, and efficiency in POC testing. Moreover, limitations and knowledge gaps in this area, as well as key considerations for sustainable development, large-scale manufacturing, and deployment of integrated electrochemical nano-aptasensors, are also highlighted. Electrochemical nano-aptasensors can pave the way for the transformation of MDR bacterial diagnosis, but need coordinated translational efforts for POC diagnostic advancements towards real-world applications. Full article

Background: Unwanted loneliness and social isolation in older adults are public health problems with negative effects on physical and mental health. The usual assessment tools, based on self-report questionnaires, have limitations in capturing these phenomena continuously and objectively. Objective: We aimed to critically analyze recent scientific evidence on the use of passive sensor technologies combined with artificial intelligence for the detection of unwanted loneliness and social isolation in older adults. Methods: Studies were reviewed in databases (PubMed, Scopus, Web of Science, and IEEE Xplore) that used wearable devices, environmental sensors in the home, smartphones, and multimodal fusion approaches. This systematic review was conducted following the PRISMA 2020 guidelines. Results: Behavioral variables derived from passive monitoring, such as mobility, time away from home, sleep patterns, and digital interactions, are consistently associated with measures of loneliness and social isolation. Likewise, artificial intelligence models based on the combination of multiple data sources show better predictive performance than unimodal approaches. Conclusions: Sensor-based technologies can complement traditional assessment methods, although their practical application requires overcoming challenges related to methodological validation, user acceptance, and ethical considerations. Full article

Background/Objectives: Nomophobia, the irrational fear of being without a mobile phone, is increasingly prevalent among university students and has emerged as a concerning form of digital dependence. Among nursing students, this condition is particularly relevant due to the emotional demands and cognitive challenges of healthcare education. Nomophobia has been linked with adverse psychological outcomes, sleep disturbances, and impaired academic and clinical performance. However, existing evidence remains fragmented and lacks an integrated conceptual synthesis. This review aimed to synthesize current evidence on the prevalence, correlates, and outcomes of nomophobia among nursing students. Methods: An integrative review was conducted following Whittemore and Knafl’s methodology and PRISMA guidelines. A systematic search was performed in PubMed, CINAHL, PsycINFO, PsycArticles, and Medline (between 2015 and 2025), supplemented by Google Scholar. Cross-sectional studies and literature focusing on nomophobia in nursing students were included. The primary studies and selected review articles were considered when no overlap with the included primary evidence was identified. Methodological quality appraisal was assessed using validated tools (QuADS and JBI). Results: Twenty-two studies were included (19 cross-sectional and 3 reviews). Four thematic areas emerged: prevalence and severity (50–90% moderate to severe); psychological correlates (anxiety, depression, stress, insomnia, alexithymia, fear of missing out); academic and cognitive outcomes (impaired performance, procrastination, reduced decision-making); and behavioural predictors (excessive smartphone use and emotional dysregulation). The Nomophobia Questionnaire (NMP-Q) was the most frequently used instrument. Conclusions: Nomophobia represents a relevant dimension of the mind–technology relationship in nursing education, with implications for students’ mental health, academic engagement, and clinical readiness. Addressing nomophobia may support healthier learning environments and contribute to the development of emotionally competent and safe future healthcare professionals. However, significant gaps remain, particularly regarding longitudinal evidence and intervention-based approaches. Full article