Examination of Cardiac Activity with ECG Monitoring Using Heart Rate Variability Methods.

The paper presents a system for analyzing cardiac activity with the possibility of continuous and remote monitoring. The created sensor mobile device monitors heart activity by means of the convenient and imperceptible registration of cardiac signals. At the same time, the behavior of the human body is also monitored through the accelerometer and gyroscope built into the device, thanks to which it is possible to signal in the event of loss of consciousness or fall (in patients with syncope). Conducting real-time cardio monitoring and the analysis of recordings using various mathematical methods (linear, non-linear, and graphical) enables the research, accurate diagnosis, timely assistance, and correct treatment of cardiovascular diseases. The paper examines the recordings of patients diagnosed with arrhythmia and syncope recorded by electrocardiography (ECG) sensors in real conditions. The obtained results are subjected to statistical analysis to determine the accuracy and significance of the obtained results. The studies show significant deviations in the patients with arrhythmia and syncope regarding the obtained values of the studied parameters of heart rate variability (HRV) from the accepted normal values (for example, the root mean square of successive differences between normal heartbeats (RMSSD) in healthy individuals is 24.02 ms, while, in patients with arrhythmia (6.09 ms) and syncope (5.21 ms), it is much lower). The obtained quantitative and graphic results identify some possible abnormalities and demonstrate disorders regarding the activity of the autonomic nervous system, which is directly related to the work of the heart.

The design and implementation of a multi-center, pragmatic, individual-level randomized controlled trial to evaluate Baby2Home, an mHealth intervention to support new parents.

BACKGROUND: Becoming a parent is a transformative experience requiring multiple transitions, including the need to navigate several components of health care, manage any mental health issues, and develop and sustain an approach to infant feeding. Baby2Home (B2H) is a digital intervention built on the collaborative care model (CCM) designed to support families during these transitions to parenthood. OBJECTIVES: We aim to investigate the effects of B2H on preventive healthcare utilization for the family unit and patient-reported outcomes (PROs) trajectories with a focus on mental health. We also aim to evaluate heterogeneity in treatment effects across social determinants of health including self-reported race and ethnicity and household income. We hypothesize that B2H will lead to optimized healthcare utilization, improved PRO trajectories, and reduced racial, ethnic, and income-based disparities in these outcomes as compared to usual care. METHODS: B2H is a multi-center, pragmatic, individual-level randomized controlled trial. We will enroll 640 families who will be randomized to: [1] B2H + usual care, or [2] usual care alone. Preventive healthcare utilization is self-reported and confirmed from medical records and includes attendance at the postpartum visit, contraception use, depression screening, vaccine uptake, well-baby visit attendance, and breastfeeding at 6 months. PRO trajectories will be analyzed after collection at 1 month, 2 months, 4 months, 6 months and 12 months. PROs include assessments of stress, depression, anxiety, self-efficacy and relationship health. IMPLICATIONS: If B2H proves effective, it would provide a scalable digital intervention to improve care for families throughout the transition to new parenthood.

Mobile device screen time is associated with poorer language development among toddlers: results from a large-scale survey.

BACKGROUND: Despite young children's widespread use of mobile devices, little research exists on this use and its association with children's language development. The aim of this study was to examine the associations between mobile device screen time and language comprehension and expressive language skills. An additional aim was to examine whether three factors related to the domestic learning environment modify the associations. METHODS: The study uses data from the Danish large-scale survey TRACES among two- and three-year-old children (n = 31,125). Mobile device screen time was measured as time spent on mobile devices on a normal day. Measurement of language comprehension and expressive language skills was based on subscales from the Five to Fifteen Toddlers questionnaire. Multivariable linear regression was used to examine the association between child mobile device screen time and language development and logistic regression to examine the risk of experiencing significant language difficulties. Joint exposure analyses were used to examine the association between child mobile device screen time and language development difficulties in combination with three other factors related to the domestic learning environment: parental education, reading to the child and child TV/PC screen time. RESULTS: High mobile device screen time of one hour or more per day was significantly associated with poorer language development scores and higher odds for both language comprehension difficulties (1-2 h: AOR = 1.30; ≥ 2 h: AOR = 1.42) and expressive language skills difficulties (1-2 h: AOR = 1.19; ≥ 2 h: AOR = 1.46). The results suggest that reading frequently to the child partly buffers the negative effect of high mobile device screen time on language comprehension difficulties but not on expressive language skills difficulties. No modifying effect of parental education and time spent by the child on TV/PC was found. CONCLUSIONS: Mobile device screen time of one hour or more per day is associated with poorer language development among toddlers. Reading frequently to the child may have a buffering effect on language comprehension difficulties but not on expressive language skills difficulties.

Mobile version of the Battery for the Assessment of Auditory Sensorimotor and Timing Abilities (BAASTA): Implementation and adult norms.

Timing and rhythm abilities are complex and multidimensional skills that are highly widespread in the general population. This complexity can be partly captured by the Battery for the Assessment of Auditory Sensorimotor and Timing Abilities (BAASTA). The battery, consisting of four perceptual and five sensorimotor tests (finger-tapping), has been used in healthy adults and in clinical populations (e.g., Parkinson's disease, ADHD, developmental dyslexia, stuttering), and shows sensitivity to individual differences and impairment. However, major limitations for the generalized use of this tool are the lack of reliable and standardized norms and of a version of the battery that can be used outside the lab. To circumvent these caveats, we put forward a new version of BAASTA on a tablet device capable of ensuring lab-equivalent measurements of timing and rhythm abilities. We present normative data obtained with this version of BAASTA from over 100 healthy adults between the ages of 18 and 87 years in a test-retest protocol. Moreover, we propose a new composite score to summarize beat-based rhythm capacities, the Beat Tracking Index (BTI), with close to excellent test-retest reliability. BTI derives from two BAASTA tests (beat alignment, paced tapping), and offers a swift and practical way of measuring rhythmic abilities when research imposes strong time constraints. This mobile BAASTA implementation is more inclusive and far-reaching, while opening new possibilities for reliable remote testing of rhythmic abilities by leveraging accessible and cost-efficient technologies.

Assessing the Quality and Behavior Change Potential of Vaping Cessation Apps: Systematic Search and Assessment.

Background: An increasing number of people are using vapes (e-cigarettes), and with growing evidence of associated harms, there is a need for acceptable cessation support and interventions. Smartphone apps for health and well-being have increased in popularity and use. Limited published literature assesses the potential of apps to support vaping cessation. Objective: A systematic search of vaping cessation apps currently available in Australia for iOS and Android platforms was conducted. Apps were assessed against established health app assessment tools for quality and behavior change potential. Methods: A systematic search through the Australian Apple iTunes and Google Play stores was conducted using the search terms "vape"; "vaping"; "e-cigarette"; and "cessation," "quit," or "quitting" in May 2023. Only apps that encouraged the cessation of vaping were included. App descriptions were reviewed to determine if they were relevant for inclusion in this study, and relevant apps were downloaded onto the appropriate mobile device for review. The Mobile App Rating Scale (MARS) was used to rate the quality (engagement, functionality, aesthetics, and information) of the apps using an overall score out of 5. The App Behavior Change Scale (ABACUS) was used to assess the behavior change potential of each app using a score out of 21. Results: An initial search of the app stores yielded 220 Android apps and 124 iOS apps. Screening against the inclusion criteria left 20 iOS apps and 10 Android apps for review. Six apps were available on both operating systems, and these were downloaded, reviewed, and reported separately for each operating system. The average MARS score for all apps assessed in this review was 3.1 (SD 0.41) out of 5. The reviewed apps overall performed well for the MARS elements relating to functionality, such as ease of use and navigation, but had the lowest scores for information-related elements, such as credibility. The number of ABACUS behavior change features per app ranged from 0 to 19 out of 21, with a mean of 8.9 (SD 4.51). The apps commonly included information-related features, such as requesting baseline information. The least common behavior change features were those relating to goal-setting, such as asking about the user's willingness for behavior change and providing feedback on current actions in comparison to future goals. Conclusions: The identified vaping cessation apps had moderate levels of quality and some behavior change components. Future vaping cessation apps could benefit from including more features that are known to support behavior change, such as goal-setting, to improve the potential benefit of these apps to support people to stop vaping. As guidelines for vaping cessation continue to be established, future apps need to reference these in their development.

Tracked and self-reported nighttime smartphone use, general health, and healthcare utilization: results from the SmartSleep Study.

STUDY OBJECTIVES: Nighttime smartphone use is an increasing public health concern. We investigated whether nighttime smartphone use is associated with general health and primary healthcare utilization. METHODS: 4,520 individuals (age 35.6 ± 9.7 years, 35% male) provided self-reported information on smartphone use frequency, symptoms of depression, and general health (one-item perceived health and cross-symptom composite score). A subset of the study sample (n=3,221) tracked their nighttime smartphone use. Primary healthcare utilization, i.e., the number of weeks in which at least one service from the patient's general practitioner was billed in 2020, was extracted from Danish population registries. Statistical analysis comprised logistic and multiple linear regression, controlling for sociodemographics. RESULTS: 319 individuals (7%) reported using their smartphone almost every night or more. More frequent self-reported nighttime smartphone use was associated with poor general health across all measures. Using the smartphone almost every night or more was associated with 2.8 [95CI: 1.9,4.1] fold higher odds of reporting poor health and with an average of 1.4 [95CI: 0.7,2.1] additional GP utilizations per year compared to no use. Associations were also found for the cross-symptom composite score across all symptoms. Further adjustment for symptoms of depression attenuated some associations. Smartphone use towards the end of the sleep period (sleep-offset use) was associated with poorer self-reported general health, but not with healthcare utilization. CONCLUSION: Nighttime smartphone use frequency is associated with poor general health and healthcare utilization. Further studies should investigate the underlying causal structure and nighttime smartphone use as a transdiagnostic intervention target.

Cocreating an Automated mHealth Apps Systematic Review Process With Generative AI: Design Science Research Approach.

BACKGROUND: The use of mobile devices for delivering health-related services (mobile health [mHealth]) has rapidly increased, leading to a demand for summarizing the state of the art and practice through systematic reviews. However, the systematic review process is a resource-intensive and time-consuming process. Generative artificial intelligence (AI) has emerged as a potential solution to automate tedious tasks. OBJECTIVE: This study aimed to explore the feasibility of using generative AI tools to automate time-consuming and resource-intensive tasks in a systematic review process and assess the scope and limitations of using such tools. METHODS: We used the design science research methodology. The solution proposed is to use cocreation with a generative AI, such as ChatGPT, to produce software code that automates the process of conducting systematic reviews. RESULTS: A triggering prompt was generated, and assistance from the generative AI was used to guide the steps toward developing, executing, and debugging a Python script. Errors in code were solved through conversational exchange with ChatGPT, and a tentative script was created. The code pulled the mHealth solutions from the Google Play Store and searched their descriptions for keywords that hinted toward evidence base. The results were exported to a CSV file, which was compared to the initial outputs of other similar systematic review processes. CONCLUSIONS: This study demonstrates the potential of using generative AI to automate the time-consuming process of conducting systematic reviews of mHealth apps. This approach could be particularly useful for researchers with limited coding skills. However, the study has limitations related to the design science research methodology, subjectivity bias, and the quality of the search results used to train the language model.

Aplicación de tecnologías móviles (m-Salud) y salud electrónica (e-Salud) en el manejo y en la prevención de la litiasis renal: revisión sistemática / Mobile and eHealth technologies in the management and prevention of nephrolithiasis: A systematic review

Introducción La litiasis renal (LR) es una enfermedad urológica común, que a menudo requiere de cuidados a largo plazo. Las tecnologías de salud móvil (m-Salud) y salud electrónica (e-Salud) tienen el potencial de mejorar el manejo de las enfermedades crónicas e impactar sobre los patrones de la conducta. Para evaluar la aplicabilidad de estas herramientas en la mejora del tratamiento y la prevención de la LR, nos propusimos evaluar los datos actuales sobre el uso, los beneficios y las limitaciones de la m-Salud y la e-Salud en la LR. Métodos Se realizó una revisión sistemática de los estudios de investigación primaria sobre m-Salud y e-Salud en la evaluación y tratamiento de la LR. Dos investigadores independientes examinaron las citas por título y resumen para determinar su pertinencia y, a continuación, se realizó una revisión del texto completo para obtener un resumen descriptivo de los estudios. Resultados Se incluyeron 37 artículos para el análisis. Las principales áreas de interés fueron: 1) botellas de agua «inteligentes» y aplicaciones de dispositivos móviles para el seguimiento del consumo de líquidos, que mostraron un aumento de la ingesta en la mayoría de los estudios; 2) plataformas de seguimiento de stent ureterales, que mejoraron la tasa de stent retenidos a largo plazo; 3) clínicas virtuales para el tratamiento de la LR, las cuales han mejorado el acceso, han reducido costes y han mostrado resultados satisfactorios; 4) plataformas de endoscopia para teléfonos inteligentes, que ofrecieron una buena calidad de imagen respecto a sus costes en entornos de recursos limitados, y 5) información sobre la LR en línea para pacientes, la cual generalmente se caracterizó por ser de mala calidad y/o precisión, particularmente en YouTube®. La mayoría de los estudios eran pruebas de concepto o estudios de intervención de un solo brazo, con una evaluación limitada de la eficacia o de los resultados clínicos a largo plazo. Conclusiones ... (AU)

Introduction Kidney stone disease (KSD) is a common urological condition that often requires long-term care. Mobile health (mHealth) and eHealth technologies have the potential to enhance chronic disease management and behavioral change. To assess opportunities to apply these tools to improve KSD treatment and prevention, we aimed to assess current evidence on the use, benefits, and limitations of mHealth and eHealth in KSD. Methods We performed a systematic review of primary research studies of mHealth and eHealth in the evaluation and management of KSD. Two independent researchers screened citations by title and abstract for relevance, then full-text review was performed for descriptive summary of the studies. Results A total of 37 articles were included for analysis. Primary domains of evidence included: 1) “smart” water bottles and mobile-device apps for tracking fluid consumption, which showed increased intake in most studies; 2) ureteral stent tracking platforms, which improved the rate of long-term retained stents; 3) virtual stone clinics, which have been suggested to increase access, lower costs, and have satisfactory outcomes; 4) smartphone-based endoscopy platforms, which offered cost-effective image quality in resource-limited settings; 5) patient information about KSD online, which was typically characterized as poor quality and/or accuracy, particularly on YouTube. Most studies were proof-of-concept or single-arm intervention designs, with limited assessment of effectiveness or long-term clinical outcomes. Conclusions Mobile and eHealth technologies have significant real-world applications to KSD prevention, intervention, and patient education. A lack of rigorous effectiveness studies currently limits evidence-based conclusions and incorporation in clinical guidelines. (AU)

Association of mobile device proficiency and subjective cognitive complaints with financial management ability among community-dwelling older adults: a population-based cross-sectional study.

BACKGROUND: Mobile devices have been used by many older adults and have the potential to assist individuals with subjective cognitive complaints (SCCs) in daily living tasks. Financial management is one of the most complex daily activity for older adults, as it is easily impaired in the prodromal stage of dementia and cognitive impairment. AIM: To investigate financial management ability among older adults from SCCs and mobile device proficiency. METHODS: A self-administered questionnaire was sent to 529 participants who were ≥ 65 years and regularly use mobile devices. Participants were divided into four groups based on SCC prevalence and scores of the Mobile Device Proficiency Questionnaire (MDPQ-16). Financial management abilities were compared between groups using the Process Analysis of Daily Activities for Dementia subscale. Regression model and crosstabulation table were used to investigate associations in detail. RESULTS: A significant difference in financial management ability was observed among the four groups (p < 0.001), with the dual impairment group showed significantly lower than the robust and SCC groups (p < 0.001). Educational history, sex, and MDPQ-16 score were significantly associated with participants' financial management ability (p ≤ 0.01). The proportion of participants who could use ATMs and electronic money independently was significantly lower among those with low proficiency in mobile devices (LPM), regardless of SCC (p < 0.05). CONCLUSION: The LPM group showed an impaired ability to manage their finances, particularly in situations where they would use information devices. Therefore, healthcare professionals should assess not only the SCC but also their proficiency with mobile devices to predict their impairment in activities of daily living.

Road-MobileSeg: Lightweight and Accurate Road Extraction Model from Remote Sensing Images for Mobile Devices.

Current road extraction models from remote sensing images based on deep learning are computationally demanding and memory-intensive because of their high model complexity, making them impractical for mobile devices. This study aimed to develop a lightweight and accurate road extraction model, called Road-MobileSeg, to address the problem of automatically extracting roads from remote sensing images on mobile devices. The Road-MobileFormer was designed as the backbone structure of Road-MobileSeg. In the Road-MobileFormer, the Coordinate Attention Module was incorporated to encode both channel relationships and long-range dependencies with precise position information for the purpose of enhancing the accuracy of road extraction. Additionally, the Micro Token Pyramid Module was introduced to decrease the number of parameters and computations required by the model, rendering it more lightweight. Moreover, three model structures, namely Road-MobileSeg-Tiny, Road-MobileSeg-Small, and Road-MobileSeg-Base, which share a common foundational structure but differ in the quantity of parameters and computations, were developed. These models varied in complexity and were available for use on mobile devices with different memory capacities and computing power. The experimental results demonstrate that the proposed models outperform the compared typical models in terms of accuracy, lightweight structure, and latency and achieve high accuracy and low latency on mobile devices. This indicates that the models that integrate with the Coordinate Attention Module and the Micro Token Pyramid Module surpass the limitations of current research and are suitable for road extraction from remote sensing images on mobile devices.

Mobile and eHealth technologies in the management and prevention of nephrolithiasis: A systematic review.

INTRODUCTION: Kidney stone disease (KSD) is a common urological condition that often requires long-term care. Mobile health (mHealth) and eHealth technologies have the potential to enhance chronic disease management and behavioral change. To assess opportunities to apply these tools to improve KSD treatment and prevention, we aimed to assess current evidence on the use, benefits, and limitations of mHealth and eHealth in KSD. METHODS: We performed a systematic review of primary research studies of mHealth and eHealth in the evaluation and management of KSD. Two independent researchers screened citations by title and abstract for relevance, then full-text review was performed for descriptive summary of the studies. RESULTS: A total of 37 articles were included for analysis. Primary domains of evidence included: 1) "smart" water bottles and mobile-device apps for tracking fluid consumption, which showed increased intake in most studies; 2) ureteral stent tracking platforms, which improved the rate of long-term retained stents; 3) virtual stone clinics, which have been suggested to increase access, lower costs, and have satisfactory outcomes; 4) smartphone-based endoscopy platforms, which offered cost-effective image quality in resource-limited settings; 5) patient information about KSD online, which was typically characterized as poor quality and/or accuracy, particularly on YouTube. Most studies were proof-of-concept or single-arm intervention designs, with limited assessment of effectiveness or long-term clinical outcomes. CONCLUSIONS: Mobile and eHealth technologies have significant real-world applications to KSD prevention, intervention, and patient education. A lack of rigorous effectiveness studies currently limits evidence-based conclusions and incorporation in clinical guidelines.

Use of Telemedicine Among Hand Surgeons and Their Patients.

PURPOSE: Initially designed to address geographic obstacles to patient care, reliance on telemedicine rapidly increased during the coronavirus pandemic. The purpose of this study was to analyze the proficiency of computer and mobile device usage among a cohort of surgeons and their patients who either used telemedicine or had in-person visits. METHODS: We retrospectively identified patients who had an outpatient telemedicine visit (T group), or in-person visit (NT group) with a hand and wrist orthopedic surgeon, between March 2020 and July 2020. These patients and their surgeons were sent the Computer Proficiency Questionnaire (CPQ-12) and the Mobile Device Questionnaire (MDPQ-16) via email. A total of 602 survey responses were collected, 279 of which belonged to patients in the T group and 323 to patients in the NT group. RESULTS: The two groups were similar in demographics, including age and sex. Scores on the CPQ-12 and MDPQ-16 did not significantly differ between the two groups. In the patient sample, there was no correlation between CPQ-12 and MDPQ-16 scores and the proportion of telehealth visits. The orthopedic surgeon group also had no observed correlation between the CPQ-12 and MDPQ-16 scores and number or proportion of telemedicine visits. CONCLUSIONS: Overall proficiency with computer and mobile devices was not correlated with the likelihood of patients or orthopedic surgeons using telemedicine visits. Patient selection appears to be driven by other factors, which could include limitations in transportation, convenience, and time constraints. CLINICAL RELEVANCE: Orthopedic surgeons should continue to offer telehealth visits to their patients regardless of estimated capabilities with electronic devices of both the patient and the surgeon.

Gluu Essentials Digital Skills Training for Middle-Aged and Older Adults That Makes Skills Stick: Results of a Pre-Post Intervention Study.

BACKGROUND: A number of real-world digital literacy training programs exist to support engagement with mobile devices, but these have been understudied. OBJECTIVE: The purpose of this study was to examine the effectiveness and program acceptability of a digital skills training program among middle-aged and older adults (aged ≥50 years) and to gather participants' recommendations for lifelong digital skills promotion. METHODS: The Gluu Essentials digital skills training program includes learning resources to support tablet use. Through pre-post surveys, this study assessed mobile device proficiency, confidence in going online and in avoiding frauds and scams, the frequency of engaging in online activities, program engagement, acceptability, and suggestions for continued support. RESULTS: A total of 270 middle-aged and older adults completed baseline surveys. Of these 270 participants, 145 (53.7%) completed follow-up surveys. Our findings indicate that mobile device proficiency increased (P<.001), whereas confidence was unchanged. Participants also reported going online more frequently to shop (P=.01) and access government services (P=.02) at follow-up. Program engagement varied considerably, but program acceptability was high. Participants' recommendations included the need for providing ongoing programs for support and training because technology constantly changes, reducing costs for technology and internet access, and keeping learning resources simple and easy to access. CONCLUSIONS: The Gluu Essentials digital skills training program increased mobile device proficiency and frequency of web-based activities (shopping and accessing government services) among middle-aged and older adults.

Real-World Navigation With Application: Characteristics of Gaze Behavior and Associated Factors in Older Adults.

Background and Objectives: Advancing age might impair real-world navigation ability. The use of mobile devices by older adults has grown rapidly in recent years. Navigation applications (apps) in mobile devices may facilitate the freedom of outings for older adults. Our aim is to investigate age-related differences in real-world app-based navigation walking in terms of accuracy, efficiency, and gaze behavior; and to explore clinical factors associated with navigation walking in older adults. Research Design and Methods: A total of 20 community-dwelling older adults and 16 young adults completed a route navigation task using a navigation app while recording their gaze behavior. Outcomes were compared in both groups and a general linear regression was used to explore clinical factors associated with app-based navigation walk in older adults. Results: Compared with young participants, older participants had more stops and root errors and less fixation time, smaller amplitude of saccades. Additionally, older adults were more likely to glance at their smartphones while app-based navigation walking. Furthermore, gait speed and the following assessment scores were significantly associated with navigation walking in older adults: Mini-Mental State Examination, Life-Space Assessment, and the short version of the Mobile Device Proficiency Questionnaire. Discussion and Implications: For app-based navigation walks, differences in accuracy and gaze behavior were found to exist with age. Additionally, efficient real-world navigation walks in older adults require the extent of life space and proficiency with mobile devices, along with walking speed and cognitive function. It is possible that age-related functional decline, such as the visual field and shifting attention between mobile devices and the real world, may have influenced the results. The study also suggests the need to understand the level of proficiency with mobile devices so that older adults can continue to go out freely. These findings give the basis for providing older adults with appropriate navigation assistance.

Use of Peer-Led Web-Based Platforms for Peer-Assisted Learning Among Canadian Anesthesia Residents and Fellows: Cross-Sectional Study.

BACKGROUND: Peer-assisted learning (PAL) using peer-led web-based platforms (PWPs), including social media, can be a highly effective method of supporting medical trainees. PWPs, such as mobile apps for sharing anesthesia resources and social media groups or discussion forums pertaining to anesthesia training, may play a role in facilitating anesthesia trainee-led web-based education. However, there have been many challenges facing anesthesia trainees when it comes to incorporating PWPs, especially social media and mobile apps for PAL. OBJECTIVE: The primary objective of this survey was to assess the proportion of trainees that use social media and mobile apps. The secondary objective was to identify the trainees' perceptions on the use of social media and mobile apps for educational purposes, including PAL. METHODS: This cross-sectional study was conducted through a survey administered via email at a single large academic center. The survey tool collected data between 2016 and 2017 on the following: demographic data (year of study, field of specialty), use of technology and web-based resources for medicine, use of social media platforms for anesthesia or training, benefits and barriers to future uses of social media for training, and ideas for trainee-led websites. Descriptive statistics were reported. RESULTS: In total, 80 anesthesia trainees (51 residents and 29 fellows) responded to the survey (response rate of 33% of out 240 trainees contacted). All trainees reported having a mobile device that most (n=61, 76%) reported using multiple times a day to access medical resources. The highest perceived benefits of PWPs according to residents were that the most valuable information was available on-demand (n=27, 53%), they saved time (n=27, 53%), and they improved their overall learning experience within anesthesia (n=24, 47%). In comparison, fellows thought that PWPs were beneficial because they provided multiple perspectives of a single topic (n=13, 45%) and served as an additional platform to discuss ideas with peers (n=13, 45%). The most popular platforms used by both residents and fellows were Facebook (residents: n=44, 86%; fellows: n=26, 90%) followed by LinkedIn (residents: n=21, 42%; fellows: n=9, 29%). Even though most anesthesia trainees used social media for personal reasons, only 26% (n=21) reported having used resident- or fellow-driven PWP resources. Examples of PWPs that trainees used included anesthesia groups and a resident Dropbox resource folder. CONCLUSIONS: There was generally an acceptance for using PWPs for PAL as they provided various benefits for trainees at all levels of learning. PWPs have the potential to garner an increased sense of community and sharing within learning experiences throughout all levels of training. The information gained from this survey will help inform the basis for developing an anesthesia trainee-led e-learning platform.

Taiwanese parents' perspectives on young children's use of information communication technology.

Introduction: How parents think and feel about their children's use of technology can influence how their kids behave online. The family's socioeconomic status (SES) may also affect this influence. In light of this, this research emphasizes the need for more investigation into parental attitudes and the role of SES in shaping how children consume media. Methods: This study surveyed 629 Taiwanese parents to explore their attitudes toward their young children's use of information communication technology (ICT), usage patterns, and the interplay with socioeconomic status. Results: The findings revealed a significant disconnect: although approximately 50% of parents considered above six years old to be a suitable age for children to start ICT, over 80% of children had already engaged with ICT before that age, indicating a large disparity between parental expectations and actual initiation. Furthermore, parents highlighted "learning interest" and "various content" as the most positive impacts of children's ICT use, while "addiction and overreliance" emerged as their primary concern. Notably, parents, as a whole, tended to perceive their child's ICT use more negative than positively, with fathers displaying greater acceptance of negative viewpoints than mothers. Parental attitudes toward children's ICT use were categorized into five clusters, ranging from balanced and optimistic views to value emphasis, conservatism, and negative doubts. This classification underscores the intricate and multifaceted nature of parental perspectives, encompassing both positive and negative outlooks on children's ICT utilization. Discussion: The findings underscore the nuanced character of parents' attitudes toward technology, shaped by the intricacies and challenges posed by the digital era. These insights emphasize that parental attitudes go beyond a simplistic positive-negative divide, reflecting a comprehensive response to the opportunities and complexities inherent in the digital age.

A Novel Inexpensive Camera-Based Photoelectric Barrier System for Accurate Flying Sprint Time Measurement.

This paper introduces a novel approach to addressing the challenge of accurately timing short distance runs, a critical aspect in the assessment of athletic performance. Electronic photoelectric barriers, although recognized for their dependability and accuracy, have remained largely inaccessible to non-professional athletes and smaller sport clubs due to their high costs. A comprehensive review of existing timing systems reveals that claimed accuracies beyond 30 ms lack experimental validation across most available systems. To bridge this gap, a mobile, camera-based timing system is proposed, capitalizing on consumer-grade electronics and smartphones to provide an affordable and easily accessible alternative. By leveraging readily available hardware components, the construction of the proposed system is detailed, ensuring its cost-effectiveness and simplicity. Experiments involving track and field athletes demonstrate the proficiency of the proposed system in accurately timing short distance sprints. Comparative assessments against a professional photoelectric cells timing system reveal a remarkable accuracy of 62 ms, firmly establishing the reliability and effectiveness of the proposed system. This finding places the camera-based approach on par with existing commercial systems, thereby offering non-professional athletes and smaller sport clubs an affordable means to achieve accurate timing. In an effort to foster further research and development, open access to the device's schematics and software is provided. This accessibility encourages collaboration and innovation in the pursuit of enhanced performance assessment tools for athletes.

Validating Wound Severity Assessment via Region-Anchored Convolutional Neural Network Model for Mobile Image-Based Size and Tissue Classification.

Evaluating and tracking the size of a wound is a crucial step in wound assessment. The measurement of various indicators on wounds over time plays a vital role in treating and managing crucial wounds. This article introduces the concept of utilizing mobile device-captured photographs to address this challenge. The research explores the application of digital technologies in the treatment of chronic wounds, offering tools to assist healthcare professionals in enhancing patient care and decision-making. Additionally, it investigates the use of deep learning (DL) algorithms along with the use of computer vision techniques to enhance the validation results of wounds. The proposed method involves tissue classification as well as visual recognition system. The wound's region of interest (RoI) is determined using superpixel techniques, enabling the calculation of its wounded zone. A classification model based on the Region Anchored CNN framework is employed to detect and differentiate wounds and classify their tissues. The outcome demonstrates that the suggested method of DL, with visual methodologies to detect the shape of a wound and measure its size, achieves exceptional results. By utilizing Resnet50, an accuracy of 0.85 percent is obtained, while the Tissue Classification CNN exhibits a Median Deviation Error of 2.91 and a precision range of 0.96%. These outcomes highlight the effectiveness of the methodology in real-world scenarios and its potential to enhance therapeutic treatments for patients with chronic wounds.

An Artificial Intelligence Exercise Coaching Mobile App: Development and Randomized Controlled Trial to Verify Its Effectiveness in Posture Correction.

BACKGROUND: Insufficient physical activity due to social distancing and suppressed outdoor activities increases vulnerability to diseases like cardiovascular diseases, sarcopenia, and severe COVID-19. While bodyweight exercises, such as squats, effectively boost physical activity, incorrect postures risk abnormal muscle activation joint strain, leading to ineffective sessions or even injuries. Avoiding incorrect postures is challenging for novices without expert guidance. Existing solutions for remote coaching and computer-assisted posture correction often prove costly or inefficient. OBJECTIVE: This study aimed to use deep neural networks to develop a personal workout assistant that offers feedback on squat postures using only mobile devices-smartphones and tablets. Deep learning mimicked experts' visual assessments of proper exercise postures. The effectiveness of the mobile app was evaluated by comparing it with exercise videos, a popular at-home workout choice. METHODS: Twenty participants were recruited without squat exercise experience and divided into an experimental group (EXP) with 10 individuals aged 21.90 (SD 2.18) years and a mean BMI of 20.75 (SD 2.11) and a control group (CTL) with 10 individuals aged 22.60 (SD 1.95) years and a mean BMI of 18.72 (SD 1.23) using randomized controlled trials. A data set with over 20,000 squat videos annotated by experts was created and a deep learning model was trained using pose estimation and video classification to analyze the workout postures. Subsequently, a mobile workout assistant app, Home Alone Exercise, was developed, and a 2-week interventional study, in which the EXP used the app while the CTL only followed workout videos, showed how the app helps people improve squat exercise. RESULTS: The EXP significantly improved their squat postures evaluated by the app after 2 weeks (Pre: 0.20 vs Mid: 4.20 vs Post: 8.00, P=.001), whereas the CTL (without the app) showed no significant change in squat posture (Pre: 0.70 vs Mid: 1.30 vs Post: 3.80, P=.13). Significant differences were observed in the left (Pre: 75.06 vs Mid: 76.24 vs Post: 63.13, P=.02) and right (Pre: 71.99 vs Mid: 76.68 vs Post: 62.82, P=.03) knee joint angles in the EXP before and after exercise, with no significant effect found for the CTL in the left (Pre: 73.27 vs Mid: 74.05 vs Post: 70.70, P=.68) and right (Pre: 70.82 vs Mid: 74.02 vs Post: 70.23, P=.61) knee joint angles. CONCLUSIONS: EXP participants trained with the app experienced faster improvement and learned more nuanced details of the squat exercise. The proposed mobile app, offering cost-effective self-discovery feedback, effectively taught users about squat exercises without expensive in-person trainer sessions. TRIAL REGISTRATION: Clinical Research Information Service KCT0008178 (retrospectively registered); https://cris.nih.go.kr/cris/search/detailSearch.do/24006.

Concurrent validity and reliability of new application for 6-min walk test in healthy adults.

Background: Evaluation assessments for physical performance, such as walking tests, are important for measuring a person's well-being. As of current, medical technology is primarily used to administer these assessments. However, medical devices are not easily accessible and are intended for research purposes only, and hence inconvenient for clinical use. Therefore, we aimed to develop a prototype physical performance assessor device with a mobile application and explored concurrent validity and reliability between the standard 6-min walk test (6MWT) and wearable sensor 6MWT using 6-min walk distance in healthy adults. Methods: Sixty healthy males and females, above 18 years of age, were required to attach a sensor to their dominant ankle while the standard protocol for 6MWT was performed. After completing the walking test, the distance from the wearable sensor 6MWT with a mobile application and the standard 6MWT were recorded and compared. Results: There was no significant difference between the distance between the standard 6MWT (410.12 ± 74.03 m) and the distance obtained with the wearable sensor. Concurrent validity was found to be moderate, and Cronbach's alpha was 0.79, which indicated good internal consistency. Conclusion: The innovative prototype wearable walking sensor with a mobile application can effectively evaluate physical performance in healthy individuals.Clinical trial registration number: TCTR20220801002.