Video Devices Research Articles

The association of time to key prehospital interventions recorded by EMT-worn video devices and sustained return of spontaneous circulation in out-of-hospital cardiac arrests

ABSTRACT OBJECTIVES The quality of prehospital resuscitation provided by emergency medical technicians (EMTs) is essential to ensure better outcomes following out-of-hospital cardiac arrests (OHCA). We assessed the quality of prehospital resuscitation by recording time to key prehospital interventions using EMT-worn video devices and investigated its association with outcomes of patients with OHCA. METHODS This retrospective, cross-sectional study included cases of non-traumatic OHCA in adults treated by EMS in Hsinchu City, Taiwan, during 2022 and 2023. We used data from high-resolution, chest-mounted wearable cameras to define and measure six Quality Indices (QIs) for prehospital resuscitation interventions (i.e., time spent recognizing OHCA). To evaluate the association between QI performance and sustained return of spontaneous circulation (ROSC), we used multivariable logistic regression. RESULTS Of 745 patients eligible for this study, 187 (25.1%) achieved sustained ROSC. Six core QIs were analyzed: recognition of OHCA (median time: 9.0 seconds), time from recognizing OHCA to initiating cardiopulmonary resuscitation (CPR; 9.0 seconds), automated external defibrillator setup (34.0 seconds), time from recognizing OHCA to beginning ventilation (160.0 seconds), advanced airway management (300 seconds), and deploying a mechanical CPR device (50 seconds). The performance of the six QIs were not associated with sustained ROSC (Adjusted odds ratio [95% confidence interval]: 1.00 [0.99-1.00], 0.99 [0.98-1.00], 1.00 [1.00-1.01], 1.00 [1.00-1.00], 1.00 [1.00-1.00] and 0.99 [0.99-1.00], respectively). CONCLUSIONS This study describes the rate of sustained ROSC and time to key interventions captured by EMT-worn video devices in non-traumatic OHCA patients. Although we found no direct link between QI performance and improved OHCA outcomes, this study highlights the potential of video-assisted QIs to enhance the documentation and understanding of prehospital resuscitation processes. These findings suggest that further refinement and application of these QIs could support more effective resuscitation strategies and training programs.

Leisure Screen Time and Food Consumption among Brazilian Adults.

Screen time, involving activities like watching television (TV), and using tablets, mobile phones, and computers (electronic devices), is associated with the consumption of unhealthy foods. This study aimed to analyze the association between prolonged leisure screen time and healthy and unhealthy food consumption indicators among Brazilian adults (≥18 years). Data from the National Health Survey (NHS), conducted in 2019 (n = 88,531), were used. Prolonged leisure screen time (screen time ≥ 3 h/day) was analyzed in three dimensions: watching TV; use of electronic devices; and total screen time (TV and electronic devices). Food consumption was analyzed in two dimensions: healthy (in natura and minimally processed foods) and unhealthy (ultra-processed foods). Poisson regression models were used to calculate prevalence ratios (crude and adjusted (PRa)) by sociodemographic factors (sex, age, schooling, income, area of residence, and race/color) and health factors (weight status, self-rated health, and presence of noncommunicable disease), to assess the association between prolonged screen time and food consumption indicators. Among Brazilian adults, the prevalence of prolonged screen time was 21.8% for TV and 22.2% for other electronic devices for leisure. The highest frequency of watching TV for a prolonged time was observed among women, older adults, and those with a lower income and schooling. Prolonged use of electronic devices was more common among young adults and those with intermediate schooling and income. Prolonged screen time was associated with an unhealthy diet, due both to the higher consumption of unhealthy foods (PRa = 1.35 for TV, PRa = 1.21 for electronic devices, and PRa = 1.32 for both types) and the lower consumption of healthy foods (PRa = 0.88 for TV, PRa = 0.86 for electronic devices, and PRa = 0.86 for both). Prolonged screen time was negatively associated with the consumption of healthy foods and favored the consumption of unhealthy foods among Brazilian adults.

Evolution of research related to how a sedentary lifestyle influences the aging process: a bibliometric review

Abstract Aim The world’s population suffers greatly from sedentary lifestyles, which are becoming more common as a result of factors such as a lack of easily accessible places to exercise, a rise in sedentary work practices such as office work, and the pervasive use of television and video devices. Consequently, associated health problems are escalating. The primary goal of this study was to examine the state and features of current trends in international publications regarding the effects of sedentary behavior on the elderly. Subject and methods A bibliometric analysis spanning the years 1994–2022, identifying a total of 311 documents, was carried out using the Web of Science Core Collection. Results The findings showed an exponential increase of 79% from 1997 to the present. The most productive journal categories, authors, and countries were Geriatrics & Gerontology and Public, Environmental & Occupational Health; authors S. Amagasa, N. Fukushima, S. Inoue, and H. Kikuchi; and the United States, respectively. Considerable variation was found in the keywords; “aging” and “sedentary lifestyle” were the most frequent terms, with 97 and 37 instances, respectively. Conclusion Maximum investment in programs promoting physical activity is necessary to improve quality of life as people age. Participants’ mental health will improve as a result of these programs, and their risk of illness will decrease.

Сравнение условий организации совместной деятельности в очном и цифровом пространстве

<p>This article presents a review of a pilot study comparing the features of organizing collaborative activities in a digital environment among students in grades 7-9 and the theoretical foundations for organizing joint activities. In the pilot study, students construct a model of a ship according to the rules specified in the task conditions. The reasons for the discomfort experienced by students when integrating into the digital space are examined and analyzed. The lack of means to mediate their activities in the online space is overcome by creating common linguistic models. Subsequently, students develop their own system of signs and symbols, and the number of digital tools used in their activities increases. This leads to increased productivity; some students who did not use video or audio devices affected the behavior of the entire group. Analysis of scientific works allows us to conclude that the organization of joint activities in the digital space is conditioned by the internalization of digital tools by students and the construction of common orientation systems in the digital environment based on them.</p>

Development of Augmented Reality-based Learning Media to Improve Students' Understanding of Moral Affairs Lessons in Class IX MTs

The product developed in this media is an Augmented Reality-based learning medium that is an application. Basically, Augmented Reality media is a software to create 3D image, video, text and audio devices into a program created.The study aims to determine the effectiveness and level of students' understanding of the material of faith to the last days using the Augmented Reality media. Research and development techniques, or simply "research and development," are employed in this kind of study. The development product validated by the media expert receives a 79% rating with a valid category, while the media validation receives a 97.5% rating with the highly valid category used. Samples from class IX students are then used, using one group pretest and posttest design patterns. Dick and Carey's nine-stage development design model is used. The daily repeat values before and after the therapy were the data, which were then subjected to t test analysis. The study's findings demonstrated the high degree of efficacy and comprehension of the augmented reality-based learning resources employed, particularly in the academic areas

Sedentary Lifestyle as a Leading cause of Some Diseases and Disability

The prevalence of inactive lifestyles has increased, leading to detrimental effects on health. Sedentary behavior refers to any action that involves extended periods of sitting, reclining, or lying down and requires minimal energy expenditure. Insufficient physical activity is prevalent among one-third of the global population aged 15 years and older, leading to adverse health effects. Nevertheless, there is a lack of awareness regarding the health hazards associated with sedentary behaviors. The prevalence of sedentary lifestyles is expanding globally due to limited opportunities for physical activity, the rise in sedentary work environments including office jobs, and the growing prevalence of television and video devices. As a result, the related health issues are increasing. Sedentary behaviors have a broad range of negative effects on the human body, including an increased risk of death from any cause, death from cardiovascular disease, cancer, and metabolic disorders such as diabetes mellitus, hypertension, and dyslipidemia. They also increase the risk of musculoskeletal disorders like arthralgia and osteoporosis, as well as depression and cognitive impairment. Therefore, minimizing sedentary behaviors and boosting physical exercise are both vital to promote public health.

Sedentary Habits and Their Detrimental Impact on Global Health: A Viewpoint

With limited areas where people can work out, an increase in sedentary work with the growing popularity of desk jobs and television and video devices, inactive lifestyles are becoming more and more common around the world. The objective of the current review is to explore the role of sedentary habits in the causation of different diseases and their impact on global health standards. Consequently, the associated health problems are becoming more serious. Inactivity has a significant influence on the human body in numerous ways. It disrupts lipolysis, transporter proteins, muscle glucose, the metabolic process, and lipoprotein lipase functionality. Prolonged sedentary behavior directly impacts the gravity, body weight balance, and can lead to fluid retention, obesity, and an increase in oxidative stress. An inactive lifestyle has a range of adverse impacts on our bodies, including a surge in all-cause mortality, coronary heart disease mortality, and the probability of contracting diseases like diabetes mellitus, hypertension, and dyslipidemia, in addition to physical ailments like arthralgia and osteoporosis, mental health issues like depression, and mental retardation. Consequently, to advance public health, we need to reduce sedentary practices and increase physical activity.

VISUAL DATA COMPUTER PROCESSING IN EDUCATIONAL DIY PROJECTS

The software tools for processing visual data in an educational chemical experiment, the experience of their usage, and a number of DIY (Do it yourself) projects developed on their basis were analyzed. Particular attention was paid to the role of self-made devices during the forced online education caused by COVID-19 and the full-scale war in Ukraine. The results of the development of the software tool ColorKit, which is being developed at the Department of Physics and Chemistry of H.S. Skovoroda Kharkiv National Pedagogical University are presented. The basic principles were covered, the interface was described, the main functions of the application and their areas of usage were given. The principle of operation of the modules: "Spectrophotometer", "Colorimeter", "Refractometer", "Polarimeter" was characterized. The features of the structure of optical computer devices for physico-chemical analysis developed by teachers, students of higher education and students, members of the Academy of Medical Sciences were considered, and the results of their testing were highlighted. The design of an absorption spectrophotometer based on a reflective diffraction grating made from a DVD disc was described; a new method of its calibration using a diamond green solution was proposed. The operating model was tested and it was established that the accuracy of the device was sufficient for demonstration and educational chemical experiments. The operating principle of the "Colorimeter" module of the ColorKit software tool was considered. It was shown that, unlike other software tools, it had built-in approximation tools, which significantly facilitated the processing of visual data; displaying the results of mathematical processing in a graphic form, which made the experiment visual. It should be noted that for the correct operation of the virtual spectrophotometer and colorimeter in real time, the correct setting of the video device driver is quite important. A number of optical schemes of refractometers developed on the basis of the ColorKit software tool were presented: with liquid and V-prisms; i.e. the device whose principle of action is based on changing the optical properties of the lens in contact with the solution. It was shown that the simultaneous display of the course of the rays and the results of mathematical processing provides a high level of visibility. The results of the approval of the LED DIE refractometer with a V-prism are outlined. Further prospects for the development of the ColorKit project are planned.

WIFI-Based Human Identification of gait recognition in muti-scenario

With the development of 5G and the maturity of embedded technology, the Internet of Things has become the most promising technology at present, and human motion recognition and fingerprint feature recognition are hot research topics in the Internet of Things. At the same time, the way of human-computer interaction no longer satisfies the interaction only through screens and our computing devices. We hope to achieve human-computer interaction through simpler and more direct operations. For example, gestures, speech, etc., while the current methods of human recognition are mostly achieved through video or wearable devices, both of which have certain limitations. For example, when using video devices to recognize human bodies, it is necessary to ensure that there are no obstacles on the line of sight (LOS) in the video and sufficient ambient light is available. The Wi-Fi recognition method proposed in this article has the advantages of non-wearable, no light source restriction, and the ability to achieve human recognition using non-line-of-sight paths. Wi-Fi is ubiquitous in modern society, so using Wi-Fi signals for indoor human sensing has important research value. Based on existing Wi-Fi gait recognition work, this paper proposes a Wi-Fi-RSMID system for indoor human recognition. By analyzing the channel state information of Wi-Fi signals during human walking, the Wi-Fi-RSMID system extracts key feature information through PCA principal component analysis of thirty subcarriers of CSI. It collects 155 feature points from five principal components of PAC using a method that combines time-frequency domain information, and achieves human recognition through random subspace method. Experiments show that the system can effectively identify the identities of 15 people in different scenarios, with an average recognition rate of about 75.3% - 85.6%.

A Framework for Multi-Task Learning in Dynamic Adaptive Streaming Over HTTP

This paper presents a framework with a taxonomy for multi-task learning in the context of Dynamic Adaptive Streaming over HTTP (DASH). DASH is a widely used technology for video streaming, and multi-task learning has emerged as a promising approach to enhance the performance and user experience of DASH systems by jointly optimizing multiple related tasks. The framework provides a structured approach to design, train, and evaluate multi-task learning models in DASH, while the taxonomy categorizes the key components and approaches within the framework. The taxonomy includes task types, multitask learning approaches, input features, and training strategies. Task types encompass video quality adaptation, buffer management, bandwidth estimation, content pre-fetching, and resource allocation, representing the specific tasks involved in DASH. Multi-task learning approaches encompass methodologies such as shared representation learning, task-specific layers, multi-head architectures, knowledge distillation, and reinforcement learning, offering flexibility in model design and optimization. Input features cover video characteristics, network conditions, device capabilities, and user preferences, providing the necessary information for informed decision-making across tasks. Training strategies include joint training, alternate training, hierarchical training, task weighting, and task balancing, determining how the multi-task learning model is trained and optimized. By following the presented framework and taxonomy, researchers and practitioners can systematically approach the design, training, and evaluation of multi-task learning models in DASH. The framework enables the development of efficient and adaptive video streaming systems by leveraging the interdependencies among tasks. The taxonomy helps organize the components and approaches within the framework, aiding in a better understanding of the various aspects of multi-task learning in the DASH context. Overall, this framework and taxonomy provide a valuable resource for advancing the field of multitask learning in the dynamic and complex domain of video streaming over HTTP.

Development of a Construction Site Hazard Warning Model Based on Deep Learning

近期因營建現場工安意外頻傳，2023年2月高雄市一處建築工地，施工人員在進行吊掛作業時，因吊車傾斜翻覆，吊臂壓到一名李姓勞工，造成職業災害；同年4月高雄市發生李姓工人正在焊接鋼筋時，遭吊車不慎碰撞，而發生工安意外；5月新北市吳姓磁磚公司老闆疑似誤觸操作堆高機，導致整個人懸空卡在機器上方，而發生憾事；因此施工人員與機具於現場作業時的安全距離與位置，常因為營建職場環境之複雜，而存有許多潛在風險，造成長期面臨職業災害的問題，包含重大公安事等發生。<br>在整個施工階段中，大多營造廠皆採用相機或攝影機等影像裝置來記錄現場的施工進度狀況，因影像資料較大、處理時間長，所以多數處於被動使用的狀態，最後僅於存查而未臻理想，所以本研究提出透過深度學習之影像辨識技術，利用卷積神經網路(CNN)具有強力的特徵提取功能，藉由濾波器(Filters)從輪廓、邊緣線條到局部特徵自動進行提取，再以全連接(Fully Connected)方式，將特徵資料輸入至整個神經網路進行訓練的一套工程現場施工危害警示系統，其對於施工影像辨識處理效果佳，達到即時監測施工現場的影像數據，並運用安全評估區塊模組快速識別潛在的危害情況，並發出警示信號，提醒工地管理人員立即採取適當的措施，確保職業安全。本研究將與營建公司合作，蒐集正在施工的建案影像和場地分析，驗證危害警示模型的可行性，並評估其對職業安全管理的實際效果，協助工地管理人員結合科技進步，運用更為有效的管理工具保障施工人員安全，減少工安意外發生，同時提高營建業的生產效率和競爭力。Recently, there has been a high frequency of construction site occupational accidents. In February 2023, at a construction site in Kaohsiung City, a crane tilted and overturned during lifting operations, causing the crane arm to press against nearby construction workers, resulting in occupational injuries. In April, a worker was welding steel bars and was accidentally struck by a crane, leading to a work safety accident. In May, the owner of a tile company in New Taipei City was suspected of mistakenly operating a forklift, causing the person to be suspended above the machine and resulting in a tragic incident. Therefore, the safety distance and positioning between construction workers and machinery during on-site operations are often compromised due to the complexity of the construction workplace environment, posing numerous latent risks and leading to long-term occupational hazard issues, including severe public safety incidents. <br>In the construction industry, cameras or video devices are commonly used to record the progress of construction activities throughout the entire construction phase. However, due to the large size of image data and time-consuming processing, these devices are often passively utilized, resulting in suboptimal outcomes where the data is merely stored for reference purposes. To address this issue, this study proposes a construction hazard warning system that leverages deep learning techniques, specifically convolutional neural networks (CNNs), known for their powerful feature extraction capabilities. By automatically extracting features from contours, edges, and local characteristics through filters and subsequently inputting the extracted features into a fully connected neural network, a practical framework for on-site construction hazard recognition is established. The system enables real-time monitoring of construction sites by processing and analyzing image data. It utilizes a safety assessment module to identify potential hazards and issue warning signals quickly, alerting site managers to take immediate actions to ensure occupational safety. In collaboration with construction companies, this research collects construction project images. It conducts site analysis to validate the feasibility of the hazard warning model and evaluate its practical effectiveness in occupational safety management. By integrating technological advancements, this research aims to assist site managers in adopting more efficient management tools, safeguarding the safety of construction personnel, reducing work-related accidents, and enhancing productivity and competitiveness in the construction industry.

Legal Guarantees of Police Officers when Citizens Take Photos and Videos of their Official Activities

The object of the study is the interaction of employees of the internal affairs bodies with the mass media. The subject of the study is the legal basis for the interaction of internal affairs officers with the media, the requirements and the procedure for preparing for such interaction. The purpose of the study is to identify the legitimate grounds for the use of photo–video devices in the activities of police officers, as well as the procedure for training police officers to interact with the media. The study uses theoretical research methods (interdisciplinary analysis of literature and normative legal documents, systematization, comparison, generalization. In this article, the authors reviewed the regulatory documents explaining the rights to carry out photo and video fixation within the professional activities of police officers. The practical significance of this study lies in: the legal justification of the legality of the use of photo-video fixation tools in the activities of police officers made by the authors on the basis of the analyzed normative legal acts; generalized on the basis of the studied Federal laws and departmental orders communicative requirements for police communication with the media, as well as the experience presented by the authors on the formation of the readiness of future police officers to interact with the media. Mass media at the stage of training in educational organizations of the Ministry of Internal Affairs of Russia. So, according to the authors, for the successful preparation of future police officers for interaction with the media, it is necessary to create special pedagogical conditions, which include: conducting communication trainings, creating a cadet press center, studying a special academic discipline, as well as the constant involvement of students in interaction with the media.

Digital tools for delivery of dementia education for caregivers of persons with dementia: A systematic review and meta-analysis of impact on caregiver distress and depressive symptoms.

Continuing education for dementia has been shown to be beneficial by improving informal caregiver knowledge, dementia care, management, and caregiver physical and mental health. Technology-based dementia education has been noted to have equivalent effects as in-person education, but with the added benefit of asynchronous and/or remote delivery, which increases accessibility. Using Cochrane review methodology, this study systematically reviewed the literature on technology-based dementia education and its impacts on caregivers. Technology-based delivery included dementia education delivered via the Internet, telephone, telehealth, videophone, computer, or digital video device (DVD). In the review, twenty-eight studies were identified with fourteen included in a meta-analysis, and these data revealed a significant small effect of technologically based dementia education on reducing caregiver depression, and a medium effect on reducing caregiver distress in response to caregivers' observations of behavioral problems displayed by persons with dementia. No evidence was found for a significant effect of the educational intervention on caregiver burden or self-efficacy, which are known to be gendered aspects of caregiving. None of the studies included in the meta-analysis reported separate outcomes for male and female care providers, which has implications for gendered caregiving norms and aspects of care. Registration number: PROSPERO 2018 CRD42018092599.

Structural modal identification using a portable laser-and-camera measurement system

Vision-based techniques for modal analysis of full-scale civil infrastructure have been constrained by the challenge of collecting measurements of all points on a large structure using limited-resolution video devices. This paper proposes a portable, simple-to-assemble laser-and-camera (LAC) system capable of measuring multipoint displacements at a low cost. An efficient video processing flow with an improved binarization strategy for pinpointing the laser spot's center is provided to extract the displacement from the video collected by LAC devices. In addition, the laser-assisted vision-based measurement technique is implemented for structural modal identification for the first time. To evaluate the performance of LAC devices in displacement measurement and structural modal identification, an error analysis test, a measurement accuracy test, and a scaled bridge model experiment are conducted in succession. The results with different types of laser receiving panels and under variable light environments demonstrate the feasibility and application potential of the proposed LAC system and approach for structural health monitoring.

Differences Between Traditional and Modern Technology in the Acquisition of New Ski Knowledge

Purpose: Video materials have been used as teaching tools for many years. With the development of modern technology, new video devices have appeared that have greatly improved the quality and capabilities of video materials. This study was conducted with the purpose of investigating and comparing the current traditional and modern ways of recording ski elements. In the traditional way of recording, the cameraman stands on the ski slope and uses a camera to record a demonstration of the ski element of the skier moving toward him. On the other hand, the modern way of recording was made with the Gopro 360 max, which allows you to record video while skiing.
 Methods: The sample of respondents who evaluated the quality of the traditional and the Gopro 360 max videos for three skiing elements consisted of 149 students (105 male and 44 female) from the Faculty of Kinesiology Osijek. Prior to the video quality assessment test, the performance of the ski elements was explained to the students using traditional and modern video footage. When solving the ski knowledge test, students had the opportunity to watch and use traditional and/or modern videos.
 Results: The average score that students achieved on the ski knowledge test was 8.9 ± 2.48 points (74.16 ± 0.21%). When evaluating the quality and contribution of the videos, students rated the usefulness of the traditional method of video recording with an average score of 3.01 ± 1.25, while the modern method of video recording received an average usefulness score of 3.79 ± 1.07. The difference between the traditional and modern video recording was statistically significant at the p < 0.01 level.
 Conclusion: The obtained results indicate that the way the Gopro360 max records and presents the skiing elements contributes significantly to the quality of the presentation and the acquisition of specific skiing knowledge compared to the traditional recording method.
 Keywords: Gopro360 max, ski elements, knowledge test

Hybrid Traffic Accident Classification Models

Traffic closed-circuit television (CCTV) devices can be used to detect and track objects on roads by designing and applying artificial intelligence and deep learning models. However, extracting useful information from the detected objects and determining the occurrence of traffic accidents are usually difficult. This paper proposes a CCTV frame-based hybrid traffic accident classification model that enables the identification of whether a frame includes accidents by generating object trajectories. The proposed model utilizes a Vision Transformer (ViT) and a Convolutional Neural Network (CNN) to extract latent representations from each frame and corresponding trajectories. The fusion of frame and trajectory features was performed to improve the traffic accident classification ability of the proposed hybrid method. In the experiments, the Car Accident Detection and Prediction (CADP) dataset was used to train the hybrid model, and the accuracy of the model was approximately 97%. The experimental results indicate that the proposed hybrid method demonstrates an improved classification performance compared to traditional models.

The associations between place-based measures of walkability and physical activity across a range of diverse streetscapes

Walkability relates to aspects of a physical environment that have the potential to influence walking in that environment. In 2019, the Environmental Protection Agency developed the National Walkability Index (NWI), an easily accessible, U.S. Census block-group-level indicator of walkability. Although the NWI could be the metric of choice for researchers and urban planners, there is a lack of empirical evidence for its validity. The current study examined the validity of the NWI and Walk Score for predicting physical activity (PA) occurring along urban streetscapes. A wearable video device (Gogloo E7 SMART eyewear) was used to capture videos of streetscapes in 24 U.S. Census block groups in three different sized cities. The block groups varied in walkability, income level, and minority composition. The videos, collected over 10 months during 2019 at different times on weekdays and weekends, were reviewed by experts to obtain counts of walkers/h and individuals performing leisure PA/h (dependent variables). The independent variables were the NWI, its components - transit stop proximity, intersection density, employment/household occupancy mix, and employment mix, and Walk Score. Block group was the level of analysis. Linear regression indicated Walk Score, employment/household occupancy mix, and employment mix were associated with walkers/h (p < .001) while only employment/household occupancy mix, and employment mix were associated with leisure PA/h (p < .001). The NWI did not account for a significant portion of the variance in PA outcomes. A place-based examination of PA and walkability indexes favors the use of Walk Score and a modified version of the NWI.

Video-capillaroscopy, a promising tool for the clinical evaluation of patients with chronic venous insufficiency.

The cutaneous microangiopathy plays a key role in the development of the skin clinical lesions of venous insufficiency. Capillaroscopy allows a non-invasive observation of the superficial skin capillaries of the lower leg, which have previously been shown to be altered in patients with advanced venous disease. As it is now available in a friendly, easy to handle way through modern video devices, we report our findings in a short series of patients with C3-C5 chronic venous disorders using this technique. A total of 21 patients with venous insufficiency (C3-C5 on at least one leg) underwent a capillaroscopic examination of both legs and pictures recorded from the sites of the most severe venous skin lesions. This was performed with a CapXview handheld video-capillaroscope (×100 magnification), allowing easy manual measurement of maximum capillary bulk diameter and capillary density. Dramatic changes in capillary density, size, and shape were easily observed at the site of the venous skin lesions. A significant negative linear relationship was found between capillary density and the "C" classes (r = -0.45; P < 0.001). A significant negative correlation was also found between capillary density and bulk diameter (r = -0.52; P < 0.001). The area under the ROC curve for the mathematical prediction of venous skin changes by capillary density was 0.842, which shows the strength of the link between the microvascular and the clinical status. Video-capillaroscopy allows a direct observation of the cutaneous venous microangiopathy and provides the possibility to measure capillary density which allows its quantification. This simple to use technique shows the potential for a more precise follow-up and treatment evaluation of the cutaneous consequences of venous disease, which remains to be further investigated.

Privacy by design in systems for assisted living, personalised care, and wellbeing: A stakeholder analysis.

Privacy by design within a system for assisted living, personalised care, and wellbeing is crucial to protect users from misuse of the data collected about their health. Especially if the information is collected through audio-video devices, the question is even more delicate due to the nature of these data. In addition to guaranteeing a high level of privacy, it is necessary to reassure end users about the correct use of these streams. The evolution of data analysis techniques began to take on an important role and increasingly defined characteristics in recent years. The purpose of this paper is twofold: on the one hand, it presents a state of the art about privacy in European Active Healthy Ageing/Active Healthy Ageing projects, with a focus on those related to audio and video processing. On the other hand, it proposes a methodology, developed in the context of the European project PlatfromUptake.eu, to identify clusters of stakeholders and application dimensions (technical, contextual, and business), define their characteristics, and show how privacy constraints affect them. From this study, we then generated a Strengths, Weaknesses, Opportunities, and Threats analysis in which we aim to identify the critical features connected to the selection and involvement of relevant stakeholders for the success of a project. Applying this type of methodology to the initial stages of a project allows understanding of which privacy issues could be related to the various stakeholder groups and which problems can then affect the correct development of the project. The idea is, therefore, to suggest a privacy-by-design approach according to the categories of stakeholders and project dimensions. The analysis will cover technical aspects, legislative and policies-related aspects also regarding the point of view of the municipalities, and aspects related to the acceptance and, therefore, to the perception of the safety of these technologies by the final end users.

Intelligent SLAM Algorithm Fusing Low-Cost Sensors at Risk of Building Collapses

When firefighters search inside a building that is at risk of collapse due to abandonment or disasters such as fire, they use old architectural drawings or a simple monitoring method involving a video device attached to a robot. However, using these methods, the disaster situation inside a building at risk of collapse is difficult to detect and identify. Therefore, we investigate the generation of digital maps for a disaster site to accurately analyze internal situations. In this study, a robot combined with a low-cost camera and two-dimensional light detection and ranging (2D-lidar) traverses across a floor to estimate the location of obstacles while drawing an internal map of the building. We propose an algorithm that detects the floor and then determines the possibility of entry, tracks collapses, and detects obstacles by analyzing patterns on the floor. The robot’s location is estimated, and a digital map is created based on Hector simultaneous localization and mapping (SLAM). Subsequently, the positions of obstacles are estimated based on the range values detected by 2D-lidar, and the position of the obstacles are identified on the map using the map update method in semantic SLAM. All equipment are implemented using low-specification devices, and the experiments are conducted using a low-cost robot that affords near-real-time performance. The experiments are conducted in various actual internal environments of buildings. In terms of obstacle detection performance, almost all obstacles are detected, and their positions identified on the map with a high accuracy of 89%.