Video-based

BACKGROUND: Real-time prediction of the remaining surgery duration (RSD) is important for optimal scheduling of resources in the operating room. METHODS: We focus on the intraoperative prediction of RSD from laparoscopic video. An extensive evaluation of seven common deep learning models, a proposed one based on the Transformer architecture (TransLocal) and four baseline approaches, is presented. The proposed pipeline includes a CNN-LSTM for feature extraction from salient regions within short video segments and a Transformer with local attention mechanisms...

Background: Women Veterans have unique health care utilization patterns; however, video-based primary care utilization among and between women and men has not been well examined. Methods: In a retrospective cohort study, we calculated gender-stratified video visit adoption (i.e., likelihood) and frequency (i.e., rate of use among users) between April 1, 2020, and March 31, 2022, by demographic and clinical characteristics known to impact health care utilization. Results: Among 5,389,139 Veterans (9.2% women), 32% of women and 18...

Recognizing the real emotion of humans is considered the most essential task for any customer feedback or medical applications. There are many methods available to recognize the type of emotion from speech signal by extracting frequency, pitch, and other dominant features. These features are used to train various models to auto-detect various human emotions. We cannot completely rely on the features of speech signals to detect the emotion, for instance, a customer is angry but still, he is speaking at a low voice (frequency components) which will eventually lead to wrong predictions...

BACKGROUND: eLearning can be an effective tool to achieve learning objectives. It facilitates asynchronous distance learning, increasing flexibility for learners and instructors. In this context, the high educational value of videos provides an invaluable primary component for longitudinal digital curricula, especially for maintaining knowledge on otherwise rarely taught subjects. Although literature concerning eLearning evaluation exists, research comprehensively describing how to design effective educational videos is lacking...

Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic echocardiograms (TTEs), which have structural information, could help identify occult AF. We created a two-stage deep learning algorithm using a video-based convolutional neural network model that (1) distinguished whether TTEs were in sinus rhythm or AF and then (2) predicted which of the TTEs in sinus rhythm were in patients who had experienced AF within 90 days. Our model, trained on 111,319 TTE videos, distinguished TTEs in AF from those in sinus rhythm with high accuracy in a held-out test cohort (AUC 0...

OBJECTIVES: The aim of this study was to investigate the mechanism of falls in male elite wheelchair basketball (WB) players and to analyse the falls characteristics considering their classification score which ranges from 1.0 to 4.5 and it is related to their functional capacity and particularly to their volume of action. DESIGN: A cross-sectional video analysis was conducted using European para championships 2023official match videos. SETTING: Players of the sample team were divided into 2 groups according to their classification point: low-point players (LPP) and high-point players (HPP)...

Video-based person re-identification (ReID) aims to exploit relevant features from spatial and temporal knowledge. Widely used methods include the part- and attention-based approaches for suppressing irrelevant spatial-temporal features. However, it is still challenging to overcome inconsistencies across video frames due to occlusion and imperfect detection. These mismatches make temporal processing ineffective and create an imbalance of crucial spatial information. To address these problems, we propose the Spatiotemporal Multi-Granularity Aggregation (ST-MGA) method, which is specifically designed to accumulate relevant features with spatiotemporally consistent cues...

Most artificial lights exhibit subtle fluctuations in intensity and frequency in response to the influence of the grid's alternating current, providing the potential to estimate the Electric Network Frequency (ENF) from conventional frame-based videos. Nevertheless, the performance of Video-based ENF (V-ENF) estimation largely relies on the imaging quality and thus may suffer from significant interference caused by non-ideal sampling, scene diversity, motion interference, and extreme lighting conditions. In this paper, we show that the ENF can be extracted without the above limitations from a new modality provided by the so-called event camera, a neuromorphic sensor that encodes the light intensity variations and asynchronously emits events with extremely high temporal resolution and high dynamic range...

BACKGROUND: With the rapid shift to telehealth, there remains a knowledge gap in how video-based care is implemented in interdisciplinary primary care (PC) settings. OBJECTIVE: The objective of this study was to gain an in-depth understanding of how video telehealth services were implemented in PC from the perspectives of patients and interdisciplinary PC team members at the Veterans Health Administration (VHA) 2 years after the onset of the COVID-19 pandemic. METHODS: We applied a positive and negative deviance approach and selected the 6% highest (n=8) and the 6% lowest (n=8) video-using PC sites in 2022 from a total of 130 VHA medical centers nationally...

Person re-identification(Re-ID) aims to retrieve pedestrians under different cameras. Compared with image-based Re-ID, video-based Re-ID extracts features from video sequences that contain both spatial features and temporal features. Existing methods usually focus on the most attractive image parts, and this will lead to redundant spatial description and insufficient temporal description. Other methods that take temporal clues into consideration usually ignore misalignment between frames and only focus on a fixed length of one given sequence...

This study explores the efficacy of various EEG complexity measures in detecting mind wandering during video-based learning. Employing a modified probe-caught method, we recorded EEG data from participants engaged in viewing educational videos and subsequently focused on the discrimination between mind wandering (MW) and non-MW states. We systematically investigated various EEG complexity metrics, including metrics that reflect a system's regularity like multiscale permutation entropy (MPE), and metrics that reflect a system's dimensionality like detrended fluctuation analysis (DFA)...

IMPORTANCE: Aortic stenosis (AS) is a major public health challenge with a growing therapeutic landscape, but current biomarkers do not inform personalized screening and follow-up. A video-based artificial intelligence (AI) biomarker (Digital AS Severity index [DASSi]) can detect severe AS using single-view long-axis echocardiography without Doppler characterization. OBJECTIVE: To deploy DASSi to patients with no AS or with mild or moderate AS at baseline to identify AS development and progression...

BACKGROUND: Approximately 80% of Deaf individuals live in low- and middle-income countries, where health systems often overlook their specific needs. This communication gap can result in misdiagnosis and inappropriate treatment, impacting their overall satisfaction with healthcare services. OBJECTIVES: This study aims to uncover barriers to healthcare access and preferences among the Deaf population in Ecuador, and the role of communication barriers in shaping satisfaction levels with healthcare services...

IMPORTANCE: As video-based care expands in many clinical settings, assessing patient experiences with this care modality will help optimize health care quality, safety, and communication. OBJECTIVE: To develop and assess the psychometric properties of the video visit user experience (VVUE) measure, a patient-reported measure of experiences with video-based technology. DESIGN, SETTING, AND PARTICIPANTS: In this survey study, veterans completed a web-based, mail, or telephone survey about their use of Veterans Healthcare Administration (VHA) virtual care between September 2021 and January 2022...

PURPOSE: In medical research, deep learning models rely on high-quality annotated data, a process often laborious and time-consuming. This is particularly true for detection tasks where bounding box annotations are required. The need to adjust two corners makes the process inherently frame-by-frame. Given the scarcity of experts' time, efficient annotation methods suitable for clinicians are needed. METHODS: We propose an on-the-fly method for live video annotation to enhance the annotation efficiency...

OBJECTIVE: In Tokyo 2020 Paralympic Games, there were the rule and goal size changes at the blind football competition. This study aimed to compare the scoring and head impact characteristics during blind football competition between the Rio 2016 and Tokyo 2020 Paralympic Games using the official videos. DESIGN: Video-based observational study. PARTICIPANTS: In total, 36 blind football (men's football 5-a-side) game videos were obtained from the official International Paralympic Committee...

BACKGROUND: Major depressive disorder is one of the leading causes of disability worldwide. Recently, the WHO has highlighted the negative impact of recent crises (COVID-19 pandemic, war in Ukraine, economic crisis). Although most international guidelines recommend psychological and psychosocial interventions as a first-line treatment for mild to moderate depression, access remains limited in France due to limited availability of trained clinicians, high costs for patients in a context of non-reimbursement and fear of stigmatisation...

INTRODUCTION: To enhance players' performance and implement effective injury prevention protocols and surveillance programs in football, it is essential to conduct epidemiological studies. Since significant disparities in injury rates across various football competitions were reported, it is important to characterize injuries in the context of the African cup of nation (AFCON) competition. AIM: To determine the incidence and factors associated with injuries among African footballers during the 2024 AFCON competition, which will be held in Ivory Coast from January 13 to February 11, 2024...

This study aimed to develop and evaluate the ARM (arm repetitive movement) algorithm using inertial measurement unit (IMU) data to assess repetitive arm motion in manual wheelchair (MWC) users in real-world settings. The algorithm was tested on community data from four MWC users with spinal cord injury and compared with video-based analysis. Additionally, the algorithm was applied to in-home and free-living environment data from two and sixteen MWC users, respectively, to assess its utility in quantifying differences across activities of daily living and between dominant and non-dominant arms...

PURPOSE: Total Knee Arthroplasty (TKA) aids in reducing pain and improving knee mobility, function, and quality of life in osteoarthritis knee (OA Knee). Techology-based rehabiliation has proved to be promising post-TKA. The objective of this systematic review was to summarize the digital technology after TKA. METHODS: The PRISMA Checklist was used for the present systematic review. Randomized and non-randomized studies were included. Joanna Briggs Critical Appraisal Checklist was used to assess risk of bias by two independent reviewers...