Video Recording Technology Research Articles

Development and Usability of an Endoscopist Report Card Assessing ERCP Quality

Audit and feedback (A&F) for endoscopic retrograde cholangiopancreatography (ERCP) is relatively understudied despite the demonstrated effectiveness of A&F for endoscopic procedures such as colonoscopy. Endoscopist 'report cards' are one A&F tool. We aimed to develop an ERCP report card and assess its appropriateness, acceptability and feasibility through usability testing. A prototype report card was designed using a combination of published quality indicators and established predictors of adverse events (AE). Exploratory analyses from a prospective multi-center registry were performed to further identify novel and/or understudied parameters for possible inclusion. Semi-structured interviews with ERCP endoscopists were conducted and framework analysis performed. Validated post-interview usability instruments were administered. Feedback was incorporated to create a final report card. The report card included domains of technical parameters, AE rates/prevention, and patient-reported experience measures (PREMs). Qualitative feedback was positive, with respondents agreeing with inclusion of relevant content in most domains. Post-interview instruments revealed adequate appropriateness and acceptability. PREMs were felt by respondents to be poorly actionable and were replaced with appropriateness of indication and fluoroscopy usage parameters in the final report card. Concerns were raised regarding the feasibility of implementation due to reliance on difficult-to-obtain granular intraprocedural data. We designed and tested an ERCP report card that has potential to be an effective A&F intervention for endoscopists in clinical practice. Though feasibility of data capture and implementation are currently limitations, advances in video recording and artificial intelligence technologies could accelerate widespread adoption of such a tool.

The influence of anisotropy on the character of hardening in additive high-strength alloys

The purpose of this work is to establish the dependence of the coefficients of planar anisotropy on the intensity of localized deformations in various loading ranges of transverse and longitudinal sections of samples of heat-resistant powder alloy Inconel 718 manufactured using SLM technology. The role of technological anisotropy of samples characteristic of SLM technology and its effect on the hardening of Inconel 718 alloy products is evaluated. Methods. To achieve this goal, the deformation diagrams of Inconel 718 powder alloy samples manufactured using SLM technology, measured during their stretching according to GOST 11701-84, were analyzed. Flat samples with a dividing grid applied to their surface were subjected to loading. During the tests, localized deformation of the samples in different sections was determined by measuring the geometry of the images of the dividing grid. A specially developed photo and video recording technology was used to capture these images. Results. The statistical analysis of the type and parameters of the deformation diagrams made it possible to determine the nature of changes in the intensity of stresses and deformations of the samples of the studied material. The linear character of its tensile hardening in the region of small values of strain intensity and the power-law character of hardening in the range of strain intensity from 0.03 to 0.17 were established. Conclusion. A significant effect of the technological anisotropy of Inconel 718 heat-resistant powder alloy samples obtained using SLM technology on the intensity of deformations is shown. The necessity of taking this fact into account in the development of technological processes for the production of responsible products from the studied material has been revealed.

Accelerometer approach for anticipatory postural adjustments assessment during step initiation in patients with leprosy

Anticipatory postural adjustments (APAs) involve a complex coordination of sensorimotor information that can be impaired in diseases that affect nerve conduction. Assessing APAs typically requires costly video recording technology, posing a challenge to the study of postural changes. This hurdle is compounded in impoverished communities affected by diseases such as leprosy, which often receive limited government support. Recent years have seen the validation of inertial sensors in wearable devices and smartphones for APA analysis in diverse populations, including adults, the elderly and people with Parkinson’s disease. This progress offers economically efficient alternatives for the study of APA in leprosy. Do patterns of activation of anticipatory postural adjustment differ between leprosy patients and healthy controls? We also investigated the validity and replicability of APAs recorded in leprosy patients using inertial measurements and video capture recordings. Thirty healthy individuals in the control group and 30 individuals with leprosy in the leprosy group performed ten gait initiation trials. To record the APA for gait initiation, the participants stood on a 2 m platform. Each participant was informed that the experimenter would give an signal, after which the participant would initiate a two-step walk on the platform. Inertial recordings (low-cost method) and video capture recordings (gold-standard method) from center of mass displacements were used to extract the APA before gait initiation. The results show that APAs are similar between groups (control and leprosy), but leprosy patients have less consistent APAs. In addition, this study highlights the reproducibility and high correlation between the values of variables obtained from both instruments, the video recording as gold standard method and portable digital inertial sensor as a low-cost alternative method. These promising findings support the use of affordable inertial sensors to track and record APAs in underserved populations that lack easy access to gold standard methods such as video recording. This approach has the potential to improve the therapeutic care and rehabilitation of these patients. Although not currently part of official protocols for leprosy patients, this assessment method could prove particularly valuable in situations where significant sensorimotor impairments are suspected or documented.

LarvaTagger: manual and automatic tagging of Drosophila larval behaviour.

As more behavioural assays are carried out in large-scale experiments on Drosophila larvae, the definitions of the archetypal actions of a larva are regularly refined. In addition, video recording and tracking technologies constantly evolve. Consequently, automatic tagging tools for Drosophila larval behaviour must be retrained to learn new representations from new data. However, existing tools cannot transfer knowledge from large amounts of previously accumulated data. We introduce LarvaTagger, a piece of software that combines a pre-trained deep neural network, providing a continuous latent representation of larva actions for stereotypical behaviour identification, with a graphical user interface to manually tag the behaviour and train new automatic taggers with the updated ground truth. We reproduced results from an automatic tagger with high accuracy, and we demonstrated that pre-training on large databases accelerates the training of a new tagger, achieving similar prediction accuracy using less data. All the code is free and open source. Docker images are also available. See gitlab.pasteur.fr/nyx/LarvaTagger.jl.

‘Robocops’ in the Making: Reframing Police–Citizen Interactions Through the Lens of Body-Worn Cameras

Abstract This paper examines new meanings that police–citizen interactions take on when officers make sense of them through the lens of body-worn cameras (BWCs). Drawing on 30 interviews with frontline police officers in a large Canadian city, we analyse the embodied character of BWCs to show how officers reframe their role and the subtleties of their approach in dealing with the public as more robotic. First, the participants believe BWCs curb their ability to build rapport with citizens, and therefore dehumanize interactions. Second, they report a need to operate more mechanically to follow protocol for case-building and use-of-force. Still, 100 per cent of participants remain in favour of BWC use—in an era of high visibility and pressure for accountability, video recording technology offers protection.

Using virtual reality to assess gesture performance deficits in schizophrenia patients.

Gesture performance deficits are prevalent in schizophrenia patients and are strongly associated with poor social communication skills and community functioning, affecting their overall quality of life. Currently, video-recording technology is widely used in clinical settings to assess gesture production deficits in schizophrenia patients. Nevertheless, the subjective evaluation of video-recordings can encumber task assessment. The present study will aim to use virtual reality to examine its potential use as an alternative tool to objectively measure gesture performance accuracy in schizophrenia patients and healthy controls. Gesture performance in the virtual reality setting will be based on the well-established Test of Upper Limb Apraxia. Participants will be immersed in a virtual environment where they will experience themselves being embodied in a collocated virtual body seen from a first-person perspective. Motion trackers will be placed on participants' hands and elbows to track upper body movements in real-time, and to record gesture movement for later analysis. Participants will see a virtual agent sitting across from them, with a virtual table in between. The agent will perform various types of gestures and the participants' task will be to imitate those gestures as accurately as possible. Measurements from the tracking devices will be stored and analyzed to address gesture performance accuracy across groups. This study aims to provide objective measurements of gesture performance accuracy in schizophrenia patients. If successful, the results will provide new knowledge to the gesture literature and offer the potential for novel therapeutic interventions using virtual reality technologies. Such interventions can improve gesturing and thus advance social communication skills in schizophrenia patients.

SAGES video acquisition framework-analysis of available OR recording technologies by the SAGES AI task force.

Surgical video recording provides the opportunity to acquire intraoperative data that can subsequently be used for a variety of quality improvement, research, and educational applications. Various recording devices are available for standard operating room camera systems. Some allow for collateral data acquisition including activities of the OR staff, kinematic measurements (motion of surgical instruments), and recording of the endoscopic video streams. Additional analysis through computer vision (CV), which allows software to understand and perform predictive tasks on images, can allow for automatic phase segmentation, instrument tracking, and derivative performance-geared metrics. With this survey, we summarize available surgical video acquisition technologies and associated performance analysis platforms. In an effort promoted by the SAGES Artificial Intelligence Task Force, we surveyed the available video recording technology companies. Of thirteen companies approached, nine were interviewed, each over an hour-long video conference. A standard set of 17 questions was administered. Questions spanned from data acquisition capacity, quality, and synchronization of video with other data, availability of analytic tools, privacy, and access. Most platforms (89%) store video in full-HD (1080p) resolution at a frame rate of 30 fps. Most (67%) of available platforms store data in a Cloud-based databank as opposed to institutional hard drives. CV powered analysis is featured in some platforms: phase segmentation in 44% platforms, out of body blurring or tool tracking in 33%, and suture time in 11%. Kinematic data are provided by 22% and perfusion imaging in one device. Video acquisition platforms on the market allow for in depth performance analysis through manual and automated review. Most of these devices will be integrated in upcoming robotic surgical platforms. Platform analytic supplementation, including CV, may allow for more refined performance analysis to surgeons and trainees. Most current AI features are related to phase segmentation, instrument tracking, and video blurring.

Drivers of police agencies’ resistance to body-worn camera adoption

Although the use of video-recording technology in policing is on the rise in the United States, not all police agencies in the country are following this trend. Using Law Enforcement Management and Administrative Statistics Body-Worn Camera Supplement survey data collected in 2016 from a nationally representative sample of general-purpose law enforcement agencies, the present analysis identified some of the factors more likely to predict interagency differences in the intention to adopt body-worn cameras (BWCs). Findings show that resistance to the adoption of BWCs is reported by law enforcement agencies that do not think the new technology is needed, report a lack of support for BWC adoption from the agency's leadership and from patrol officers, and have privacy and cost-related concerns. Although the perceived lack of public support for the adoption of BWCs does not differentiate agencies that intend to acquire BWCs from agencies that do not, police departments that registered a higher percentage of complaints for excessive use of physical force are significantly more likely to oppose the adoption of BWCs. Support for BWC adoption is significantly higher in police departments that have acquired other types of recording equipment in the past. Even though recent state-level legislative changes related to BWCs do not have a significant impact on BWC adoption decisions at the organization level, results indicate that law enforcement agencies located in US states with strong police unions are more likely to show resistance to the adoption of BWCs in the near future.

Video Not Available:

This article examines the barriers that limit access to video art online and offers practical solutions and suggestions to aid librarians in the search for digital video art resources. Videotape is essentially an obsolete technology, a fact that dramatically slows down digitization efforts. Furthermore, in support of the protection of artist’s rights, access to video art is often controlled by third party distributors. While distributors are crucial champions of the medium, issues of copyright complicate discussions of online access. Opportunistic art lovers have taken matters into their own hands, uploading work to online platforms and creating new liminal spaces of access. This article offers an understanding of video recording technology, the historical development and dissemination of video art, and the problematic nature of many online resources that provide access to these culturally valuable works.[This article is a revision of a paper presented during the 49th annual ARLIS/NA conference held virtually May 11–13, 2021.]

An application of in-vehicle recording technologies to analyze injury severity in crashes between taxis and two-wheelers

Conventionally, the crash data used in traffic safety analysis have been collected by the police dispatched to the crash scene. Therefore, crash information inevitably includes errors that influence traffic safety analysis. Such errors can include the crash speed, crash time, crash location, and other crash characteristics. The advances in in-vehicle video recording (IVVR) technologies have recently enabled traffic safety professionals to use more accurate crash information based on crash data reconstruction methods. Although a few studies have been conducted to identify the factors affecting the crash injury severity using such detailed crash data, there was no effort to analyze the factors affecting the injury severity in crashes between taxis and two-wheelers (TWs), including bicycles and motorcycles. Therefore, this study analyzes the injury severity of TW riders in taxi-TW crashes with the accurate crash data collected by taxis equipped with IVVR devices in Incheon, Korea. Two hundred and forty-eight crash data from two years (2010–2011) were used to perform this objective. The factors affecting the injury severity to TW riders were identified based on a partial proportional odds model for these data. Seven variables were found to affect the injury severity significantly: crash speed, second collision, third collision, Delta-V, crashes that occurred with a non-helmeted motorcycle rider, crashes where the collision type was sideswipe, and crashes under rainy or snowy weather conditions. On the other hand, two variables regarding crashes, where the taxi driver behavior helped reduce visible and severe injuries, were changing lanes and the young TW riders (<18 years).

Acoustic to Electronic and Public to Private: An Introduction to Music in the Great Expansion (1700–2100 CE)

Acoustic to Electronic and Public to Private: An Introduction to Music in the Great Expansion (1700–2100 CE)

Identification of Abnormal States in Videos of Ants Undergoing Social Phase Change

Biology is both an important application area and a source of motivation for development of advanced machine learning techniques. Although much attention has been paid to large and complex data sets resulting from high-throughput sequencing, advances in high-quality video recording technology have begun to generate similarly rich data sets requiring sophisticated techniques from both computer vision and time-series analysis. Moreover, just as studying gene expression patterns in one organism can reveal general principles that apply to other organisms, the study of complex social interactions in an experimentally tractable model system, such as a laboratory ant colony, can provide general principles about the dynamics of other social groups. Here, we focus on one such example from the study of reproductive regulation in small laboratory colonies of more than 50 Harpegnathos ants. These ants can be artificially induced to begin a ~20 day process of hierarchy reformation. Although the conclusion of this process is conspicuous to a human observer, it remains unclear which behaviors during the transient period are contributing to the process. To address this issue, we explore the potential application of One-class Classification (OC) to the detection of abnormal states in ant colonies for which behavioral data is only available for the normal societal conditions during training. Specifically, we build upon the Deep Support Vector Data Description (DSVDD) and introduce the Inner-Outlier Generator (IO-GEN) that synthesizes fake “inner outlier” observations during training that are near the center of the DSVDD data description.We show that IO-GEN increases the reliability of the final OC classifier relative to other DSVDD baselines. This method can be used to screen video frames for which additional human observation is needed. Although we focus on an application with laboratory colonies of social insects, this approach may be applied to video data from other social systems to either better understand the causal factors behind social phase transitions or even to predict the onset of future transitions.

Impact of Deep Learning on Localizing and Recognizing Handwritten Text in Lecture Videos

Now-a-days, the video recording technologies have turned out to be more and more forceful and easier to utilize. Therefore, numerous universities are recording and publishing their lectures online in order to make them reachable for learners or students. These lecture videos encapsulate the handwritten text written either on a paper or blackboard or on a tablet using a stylus. On the other hand, this mechanism of recording the lecture videos consumes huge quantity of multimedia data in a faster manner. Thus, handwritten text recognition on the lecture video portals has turned out to be an incredibly significant and demanding task. Thus, this paper intends to develop a novel handwritten text detection and recognition approach on the video lecture dataset by following four major phases, viz. (a) Text Localization, (b) Segmentation (c) Pre-processing and (d) Recognition. The text localization in the lecture video frames is the initial phase and here the arbitrarily oriented text on video frames is localized using the Modified Region Growing (MRG) algorithm. Then, the localized words are subjected to segmentation via the K-means clustering, in which the words from the detected text regions are segmented out. Subsequently, the segmented words are pre-processed to avoid the blurriness artifacts as well. Finally, the pre-processed words are recognized using the Deep Convolutional Neural Network (DCNN). The performance of the proposed model is analyzed in terms of the performance measures like accuracy, precision, sensitivity and specificity to exhibit the supremacy of the text detection and recognition in lecture video. Experimental results reveal that at Learning Percentage of 70, the presented work has the highest accuracy of 89.3% for 500 count of frames.

Electronic Evidence: A Necessary Stage in Criminal Justice Development

Digitalization of criminal procedural activity is a complex process that inevitably affects the establishment of evidence procedure. One of the most controversial topics in this direction is the possibility of introducing a new type (source) of evidence: electronic evidence. The paper discusses various scientific approaches that challenge the necessity of its existence. The author expresses his point of view on the possible reasons for this trend. The position of scientists advocating the further development and implementation of electronic evidence is supported. The features of the existence of information in electronic form are described. The influence of the derived nature of the virtual space on the information obtained as a result of cognitive activity is analyzed. The problems of differentiating the information carrier and its content are stated. The specificity of the use of information in electronic form in the context of initial and derivative evidence is investigated. Attention is drawn to the need to develop criteria for electronic evidence in the direction of data authentication, as well as the mandatory involvement at certain stages of persons with special knowledge. The foreign experience of using various electronic devices in the establishment of evidence process is presented. The widespread introduction of digital audio and video recording technologies is emphasized. The concept of "digital evidence" is analyzed.

RETRACTED ARTICLE: Multi-edge optimized LSTM RNN for video summarization

Video summarization is an inevitable process in this developed communication world. The improvements in digital communication and filmless video recording technologies triggered the tremendous growth of storing and sharing variety of videos. Video summarization is used to optimize the searching and organizing process of different types of videos. Precision, Recall, F-Score and Processing time are the primary evaluation metrics of a video summarization procedure. A frequency domain multi-edge detection process and Multi-Edge optimized Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) are proposed and integrated in this work. The frequency domain Multi-Edge detection is introduced to improve the precision, recall and F-Score whereas, Multi-Edge Optimized LSTM is used to reduce the processing time of the summarization process. Discrete Wavelet Transformation based multi-edge detection algorithm is introduced and integrated with the optimized LSTM to achieve the betterment of the summarization process. The proposed method named as Multi-Edge optimized LSTM RNN for Video Summarization (MOLRVS) is indented to perform the video summarization process in real time video streaming environments to reduce a significant amount of manual interventions.

Wearable recording video technology for surgical training in living donor liver transplantation.

Backgrounds/AimsAs the development of surgical video recording technologies, educational videos have become widely utilized for trainee education. However, the current forms of surgical video are limited because they do not show all the roles of the participants. Aim of this study is to make optimal training material about living donor liver transplantation for residents and fellows using wearable recording system.MethodsThree video clips about procedure of liver transplantation were made. A head mount was used to fix the camera on the surgeon or assistant's head. Anastomosis of vessels, bench operation and trocar insertion for laparoscopic donor hepatectomy were recorded. Each video clips were edited including indicators, subtitles, and narration. The edited videos were shown to 20 General Surgery trainees (18 residents, 2 fellows) and we received feedback. The results of the questionnaire were quantitatively analyzed to show how efficient and informative it is compared to existing educational materials.ResultsSixteen of the 20 trainees (80%) responded that this video helped them improve their surgical skills. Eighteen trainees (90%) responded that they gained new knowledge through this video. Sixteen trainees (80%) responded that the action camera image material was more educational than existing text-based and video-based materials, with an average score of 8.5 and 6.5 (action camera materials vs. text-based materials, respectively).ConclusionsA head-mounted action camera video recording system is a good model for making high-quality educational video modules and can be a useful teaching tool for living donor liver transplantation.

Video recordings of Brown-headed (Molothrus ater) and Shiny (M. bonariensis) cowbirds reveal oviposition from an elevated position: Implications for host–parasite coevolution

Molothrine cowbirds are obligate brood parasites that lay eggs within 5–10 s in the minutes before sunrise. Robust analysis of their position at laying has therefore only been made possible with the development of high-resolution and low-light video recording technologies. From video recordings, we observed the moment of oviposition clearly in 8 and 31 instances of egg laying by Brown-headed (Molothrus ater) and Shiny (M. bonariensis) cowbirds, respectively. Both species laid from an elevated position such that their eggs dropped into nests from an estimated height of 4–8 cm. We propose this elevated laying position has selected for high eggshell strength in cowbirds, because stronger eggshells would be less likely to be damaged during egg laying. Stronger eggshells might also damage other eggs when dropped into the nest, thereby further reducing nestling competition from nest mates and drive selection for cowbird eggshell strength. A role for laying position in the evolution of cowbird egg strength is not mutually exclusive of the view that thickly shelled eggs have evolved as a defense to egg rejection by hosts and/or egg puncture behavior of cowbirds.

VIDEO RECORDING FOR CAPTURING INTERACTIONS BETWEEN RESIDENTS WITH DEMENTIA AND STAFF: A SYSTEMATIC REVIEW

The use of video-recording offers important advantages in observing and assessing the relationships between specific behaviors in health care settings. The purpose of this systematic review is to investigate and synthesize the methodological characteristics of studies using video-technology for measuring interactions between the older persons with dementia and staff in long-term care facilities. We searched Medline, Embase and CINHAL databases for published articles in English using a video-recording method for both staff and persons with dementia. Quantitative research design studies (e.g., descriptive studies or an experimental studies) were included. Among 5,605 searched papers, a total of 20 studies were selected for this review. Situations of video-recording were providing personal care (n=12), mealtime (n=6), and conversation (n=3). Concepts of measuring by video-recording were classified into two groups: 1) Staff [care practice by staff (n=13) and communication by staff (n=11)] and 2) residents [communication by resident (n=4), activities of daily life function of resident (n=8), and behavioral and psychological symptoms of dementia (n=10)]. This review demonstrates that video technologies are actively used to evaluate the relationship between quality of care and health outcomes of the elderly with dementia in many international nursing studies. This study provides the foundation for a future research using video-recording technologies to examine the interactions and relationship between staff and the residents in long-term care settings.

An exploratory study on pre-service teachers’ reflective reports of their video-recorded microteaching

The micro-teaching technique has been utilized for more than half a century by teacher education programs with the main aim of providing pre-service teachers with practice opportunities. The flexible nature of the technique makes it possible to adapt the implementation to the peculiarities of any specific context. In addition, the latest technological developments such as smartphones and the internet can also be integrated into the microteaching technique to increase its efficiency. In this study, the participating pre-service teachers have been asked to video-record their microteaching performances and watch their performances several times before they write a reflective report on their performance. The technique of content analysis has been applied in the analysis process of the reflective reports and their perceptions as to their instructional skills have been identified. It has also been observed that, in comparison to traditional implementation of the microteaching technique, integration of smartphone video-recording technology into the microteaching technique has yielded benefits particularly in terms of the feedback stage and improving pre-service teachers’ reflective skills.

Supporting Family Caregivers With Technology for Dementia Home Care: A Randomized Controlled Trial.

Background and ObjectivesThe number of persons living with dementia (PLWD) in the United States will reach 16 million by 2050. Behavioral and psychological symptoms of dementia challenge family caregivers and contribute to negative caregiver outcomes such as burden and depression. Available technology can support the delivery of effective interventions to families providing dementia care at home. The Supporting Family Caregivers with Technology for Dementia Home Care (FamTechCare) randomized controlled trial evaluated the effects of a telehealth intervention on caregiver outcomes.Research Design and MethodsThe FamTechCare intervention provides tailored dementia-care strategies to in-home caregivers based on video recordings caregivers submit of challenging care situations. An expert team reviews the videos and provides individualized interventions weekly for the experimental group. In the telephone-support attention control group, caregivers receive feedback from an interventionist via the telephone based on caregiver retrospective recall of care challenges. Effects of the intervention on caregiver outcomes, including burden, depression, sleep disturbance, competence, desire to institutionalize the PLWD, and caregiver reaction to behavioral symptoms were evaluated by fitting linear mixed regression models to changes in the outcomes measured at 1 and 3 months.ResultsFamTechCare caregivers (n = 42) had greater reductions in depression (p = .012) and gains in competence (p = .033) after 3 months compared to the attention control group (n = 41). Living in rural areas was associated with a reduction in depression for FamTechCare caregivers (p = .002). Higher level of education was associated with greater improvements or lesser declines in burden, competence, and reaction to behavioral symptoms for both the FamTechCare and attention control caregivers.Discussion and ImplicationsThis research demonstrated benefits of using available technology to link families to dementia care experts using video-recording technology. It provides a foundation for future research testing telehealth interventions, tailored based on rich contextual data to support families, including those in rural or remote locations.