Daily Activity Lifelogs of People With Heart Failure: Observational Study.

BACKGROUND: Globally, heart failure (HF) affects more than 64 million people, and attempts to reduce its social and economic burden are a public health priority. Interventions to support people with HF to self-manage have been shown to reduce hospitalizations, improve quality of life, and reduce mortality rates. Understanding how people self-manage is imperative to improve future interventions; however, most approaches to date, have used self-report methods to achieve this. Wearable cameras provide a unique tool to understand the lived experiences of people with HF and the daily activities they undertake, which could lead to more effective interventions. However, their potential for understanding chronic conditions such as HF is unclear. OBJECTIVE: This study aimed to determine the potential utility of wearable cameras to better understand the activities of daily living in people living with HF. METHODS: The "Seeing is Believing (SIB)" study involved 30 patients with HF who wore wearable cameras for a maximum of 30 days. We used the E-Myscéal web-based lifelog retrieval system to process and analyze the wearable camera image data set. Search terms for 7 daily activities (physical activity, gardening, shopping, screen time, drinking, eating, and medication intake) were developed and used for image retrieval. Sensitivity analysis was conducted to compare the number of images retrieved using different search terms. Temporal patterns in daily activities were examined, and differences before and after hospitalization were assessed. RESULTS: E-Myscéal exhibited sensitivity to specific search terms, leading to significant variations in the number of images retrieved for each activity. The highest number of images returned were related to eating and drinking, with fewer images for physical activity, screen time, and taking medication. The majority of captured activities occurred before midday. Notably, temporal differences in daily activity patterns were observed for participants hospitalized during this study. The number of medication images increased after hospital discharge, while screen time images decreased. CONCLUSIONS: Wearable cameras offer valuable insights into daily activities and self-management in people living with HF. E-Myscéal efficiently retrieves relevant images, but search term sensitivity underscores the need for careful selection.

Expert Consensus on the Resource Needs of Autistic Children and Young People in Ireland During the Early Months of the COVID-19 Pandemic.

The COVID-19 pandemic has brought significant changes across society. This Delphi study aimed to gain expert consensus on challenges faced and resource needs for autistic children during the COVID-19 pandemic. Round 1 of the Delphi method employed semi-structured interviews with experts (N = 24) which were thematically analysed in order to identify needs, resource targets and resource development. In a follow-up Round 2 survey participants rated emergent need and resource in order of priority. Round 2 provided consensus on challenges faced with anxiety, routine and wellbeing ranked most important. Direction on resource design was also obtained. Consensus on the challenges and resources was achieved and is being integrated into a needs-based transition resources toolkit. Future studies could make use of the Delphi method to quickly gain consensus on focus of needs in other contexts and communities.

Now you see it! Using wearable cameras to gain insights into the lived experience of cardiovascular conditions.

Wearable cameras offer an innovative way to discover new insights into the lived experience of people with cardiovascular conditions. Wearable cameras can be used alone or supplement more traditional research methods, such as interviews and participant observations. This paper provides an overview of the benefits of using wearable cameras for data collection and outlines some key considerations for researchers and clinicians interested in this method. We provide a case study describing a study design using wearable cameras and how the data were used.

Interactive video retrieval evaluation at a distance: comparing sixteen interactive video search systems in a remote setting at the 10th Video Browser Showdown.

The Video Browser Showdown addresses difficult video search challenges through an annual interactive evaluation campaign attracting research teams focusing on interactive video retrieval. The campaign aims to provide insights into the performance of participating interactive video retrieval systems, tested by selected search tasks on large video collections. For the first time in its ten year history, the Video Browser Showdown 2021 was organized in a fully remote setting and hosted a record number of sixteen scoring systems. In this paper, we describe the competition setting, tasks and results and give an overview of state-of-the-art methods used by the competing systems. By looking at query result logs provided by ten systems, we analyze differences in retrieval model performances and browsing times before a correct submission. Through advances in data gathering methodology and tools, we provide a comprehensive analysis of ad-hoc video search tasks, discuss results, task design and methodological challenges. We highlight that almost all top performing systems utilize some sort of joint embedding for text-image retrieval and enable specification of temporal context in queries for known-item search. Whereas a combination of these techniques drive the currently top performing systems, we identify several future challenges for interactive video search engines and the Video Browser Showdown competition itself.

Study protocol for autism specific transition resources (T-Res Study): developing a flexible resource package for dealing with the loosening and/or lifting of COVID-19 related restrictions.

Autism specific transition resources (T-Res) aims to develop a flexible resource package to support children and young people with a diagnosis of autism spectrum disorder (ASD), as well as their families and educators, during the loosening and/or lifting of coronavirus disease 2019 (COVID-19) related restrictions on movement. A secondary aim is to determine the current and long-term impacts of the COVID-19 related restrictions on the wellbeing of individuals with autism spectrum disorders and their parents/caregivers. Measuring and addressing the psychosocial impact of the COVID-19 pandemic and related restrictions in movement is of prime importance at this time.  The impacts of this crisis will be far reaching and many may not be realised for many years. The proposed research will focus on children and young people with a diagnosis of ASD, their families and educators.  The ASD population alone is sizable with 14,000 (or 1.55%) of students in schools holding a diagnosis. When parents, teachers, tutors and special needs assistants (SNAs) are also considered this is a considerable group. The proposed research has the potential to have impacts that are social, psychological, educational and economic. This will be achieved through development of an online transition package to guide parents and educators in preparing children and young people for the resumption of regular daily routines following the lifting of COVID-19 restrictions.  This resource will be developed based on the needs of families and young people, as measured through surveys, as well as expert consensus on the targets and means of intervention.  This ambitious project can be commenced quickly and is designed to produce outputs quickly, which will in turn be disseminated to key stakeholders.

The use of wearable cameras in assessing children's dietary intake and behaviours in China.

The use of lifelogging device in dietary assessments can reduce misreporting and underreporting, which are common in the previous studies conventional methods. We performed the first study in Chinese children (primary school Grade 4) that applied the wearable cameras in assisting dietary recall. Children (n = 52) wore the wearable cameras (Narrative Clip 2) for seven consecutive days, during which they completed a 3-day 24-h dietary recall at home. Then children modified their dietary recalls at school by reviewing the photos taken by the wearable camera at school, with the assistance of the investigator, and generated the camera-assisted 24-h dietary recalls. Compared with camera-assisted dietary recalls, 8% (n = 160) and 1% (n = 11) of food items were underreported (i.e. not reported at all) and misreported (i.e. reported in an incorrect amount) by dietary recalls without camera-assistance, respectively. Dietary recalls without camera assistance underestimated daily energy intake by 149 ±â€¯182 kcal/d (8%) in comparison to the camera-assisted dietary recalls. Foods consumed on the snacking occasions (40%) were more likely to be underreported than those consumed at main meals (P < 0.001). Beverages (37%), fruits (30%), snacks and desserts (16%) were foods most likely to be inaccurately reported. Children were satisfied with the wearable cameras, with a median score 5.0 (IQR: 5.0-5.0) for most features. Wearable cameras hold promise for improving accuracy of dietary intake assessment in children, providing rich objective information on dietary behaviours, and received high level of satisfaction and compliance of the users. Our results suggest that the accuracy of dietary recall among Chinse school-aged children could be improved by wearable camera, especially avoiding underreporting in the snacking occasions.

Kids'Cam: An Objective Methodology to Study the World in Which Children Live.

INTRODUCTION: This paper reports on a new methodology to objectively study the world in which children live. The primary research study (Kids'Cam Food Marketing) illustrates the method; numerous ancillary studies include exploration of children's exposure to alcohol, smoking, "blue" space and gambling, and their use of "green" space, transport, and sun protection. METHODS: One hundred sixty-eight randomly selected children (aged 11-13 years) recruited from 16 randomly selected schools in Wellington, New Zealand used wearable cameras and GPS units for 4 days, recording imagery every 7 seconds and longitude/latitude locations every 5 seconds. Data were collected from July 2014 to June 2015. Analysis commenced in 2015 and is ongoing. Bespoke software was used to manually code images for variables of interest including setting, marketing media, and product category to produce variables for statistical analysis. GPS data were extracted and cleaned in ArcGIS, version 10.3 for exposure spatial analysis. RESULTS: Approximately 1.4 million images and 2.2 million GPS coordinates were generated (most were usable) from many settings including the difficult to measure aspects of exposures in the home, at school, and during leisure time. The method is ethical, legal, and acceptable to children and the wider community. CONCLUSIONS: This methodology enabled objective analysis of the world in which children live. The main arm examined the frequency and nature of children's exposure to food and beverage marketing and provided data on difficult to measure settings. The methodology will likely generate robust evidence facilitating more effective policymaking to address numerous public health concerns.

The smartphone as a platform for wearable cameras in health research.

BACKGROUND: The Microsoft SenseCam, a small camera that is worn on the chest via a lanyard, increasingly is being deployed in health research. However, the SenseCam and other wearable cameras are not yet in widespread use because of a variety of factors. It is proposed that the ubiquitous smartphones can provide a more accessible alternative to SenseCam and similar devices. PURPOSE: To perform an initial evaluation of the potential of smartphones to become an alternative to a wearable camera such as the SenseCam. METHODS: In 2012, adults were supplied with a smartphone, which they wore on a lanyard, that ran life-logging software. Participants wore the smartphone for up to 1 day and the resulting life-log data were both manually annotated and automatically analyzed for the presence of visual concepts. The results were compared to prior work using the SenseCam. RESULTS: In total, 166,000 smartphone photos were gathered from 47 individuals, along with associated sensor readings. The average time spent wearing the device across all users was 5 hours 39 minutes (SD=4 hours 11 minutes). A subset of 36,698 photos was selected for manual annotation by five researchers. Software analysis of these photos supports the automatic identification of activities to a similar level of accuracy as for SenseCam images in a previous study. CONCLUSIONS: Many aspects of the functionality of a SenseCam largely can be replicated, and in some cases enhanced, by the ubiquitous smartphone platform. This makes smartphones good candidates for a new generation of wearable sensing devices in health research, because of their widespread use across many populations. It is envisioned that smartphones will provide a compelling alternative to the dedicated SenseCam hardware for a number of users and application areas. This will be achieved by integrating new types of sensor data, leveraging the smartphone's real-time connectivity and rich user interface, and providing support for a range of relatively sophisticated applications.

Remote real-time monitoring of subsurface landfill gas migration.

The cost of monitoring greenhouse gas emissions from landfill sites is of major concern for regulatory authorities. The current monitoring procedure is recognised as labour intensive, requiring agency inspectors to physically travel to perimeter borehole wells in rough terrain and manually measure gas concentration levels with expensive hand-held instrumentation. In this article we present a cost-effective and efficient system for remotely monitoring landfill subsurface migration of methane and carbon dioxide concentration levels. Based purely on an autonomous sensing architecture, the proposed sensing platform was capable of performing complex analytical measurements in situ and successfully communicating the data remotely to a cloud database. A web tool was developed to present the sensed data to relevant stakeholders. We report our experiences in deploying such an approach in the field over a period of approximately 16 months.