Video Analysis Research Articles

A comprehensive two-dimensional scoring system to assess the single-leg squat task in football players

BackgroundThe single-leg squat (SLS) is a safe and widespread functional test commonly performed in the mid-stages of rehabilitation after severe knee injuries. The use of reliable objective measures has been advocated to improve the quality of SLS assessment. The aim of this study was to describe a qualitative whole-body scoring system based on two-dimensional (2D) video analysis during SLS test and validate it against three-dimensional (3D) kinetics and kinematics. MethodsThirty-four competitive football (soccer) players performed a series of SLS tasks. 3D kinematics and kinetics were collected through infrared cameras, and 2D video analysis was performed through a scoring system with sub-scores ranging from 0/2 (non-adequate movement) to 2/2 (adequate movement) based on frontal and lateral planes objective measurements. 3D kinematics and kinetics were grouped according to the results of the 2D evaluation and compared through the analysis of variance (P < 0.05). ResultsHigher hip adduction, hip internalrotation, and knee valgus collapse were found in trials rated 0/2 or 1/2 compared with theone rated 2/2 in the limb stability score. Hip flexion and hip/knee moment ratio were lower in those scoring 0/2 comparedwith those scoring 2/2 in the movement strategy criterion. A low total score was associated with higherknee valgus collapse and lower hip/knee extensor moment ratio. Compensatory strategieswere found in frontal plane scores. ConclusionsThe 2D scoring system described was strongly associated with kinematics and kinetics from gold-standard 3D motion capture and might represent a valid tool to describe the movement quality of an SLS task.

Early Play Behaviors of Infants at Elevated Likelihood for Autism Spectrum Disorder.

Although research has examined early identification of autism spectrum disorder (ASD), few studies have found behavioral markers during midinfancy associated with later ASD diagnosis. To examine infants' play behaviors and atypical positions at age 6 mo and later outcome classification among infants at elevated likelihood (EL) and typical likelihood (TL) for ASD. Atypical positions refer to movement patterns indicative of motor delays or deviations, including atypical extension and flexion, poor weight shift and rotation, hypertonicity or hypotonicity, and the presence of primitive reflex patterns. Observational cohort longitudinal design using blinded video analysis. Fifty-eight infants (41 EL infants and 17 TL infants) 6 mo of age. Infants later diagnosed with ASD needed more support to engage in play at age 6 mo compared with infants who did not receive an ASD diagnosis (U = 130, z = -2.29, p < .05, r = .31). Atypical positions at 6 mo of age were not associated with a later diagnosis of ASD. Play behaviors may be early indicators of developmental differences for infants later diagnosed with ASD. The results of this pilot study suggest the need to observe the quality of interaction with a caregiver and objects during early play, which may serve as potential early indicators of ASD. Plain-Language Summary: Few studies have found behavioral markers during midinfancy that are associated with a later diagnosis of autism spectrum disorder (ASD). The results of this study showed that infants who were later diagnosed with ASD were found to have differences in play behaviors compared to infants who were not later diagnosed with ASD. Thus, early play behaviors may be an early indicator of developmental differences for infants who are later diagnosed with ASD.

TikTok Tracheostomy Video Analysis of Quality, Credibility, and Readability

TikTok Tracheostomy Video Analysis of Quality, Credibility, and Readability

Relationship between jump height and lower limb joint kinetics and kinematics during countermovement jump in elite male athletes

ABSTRACT This study aims to identify the relationship between jump height and the kinetic and kinematic parameters of the hip, knee, and ankle joints during countermovement jump (CMJ) in elite male athletes. Sixty-six elite male athletes from various sports (strength and power, winter downhill, combat, ball game, and aquatic) performed maximal effort CMJs with hands and arms crossed against their chests on force platforms. Jumping motion in the sagittal plane was recorded using video analysis and the peak torque, power, and angular velocity of the right hip, knee, and ankle joints were calculated during the propulsive phase. Correlations between the CMJ height and kinetic and kinematic parameters were investigated using Pearson’s product-moment coefficient (r) and Spearman’s rank correlation coefficient (ρ). CMJ height was highly correlated with peak hip power (ρ = 0.686, p < 0.001) and peak knee angular velocity (r = 0.517, p < 0.001), and moderately correlated with peak hip angular velocity (r = 0.438, p < 0.001) and peak hip torque (r = 0.398, p = 0.001). These results indicate that notable hip torque and power can contribute to increased angular velocity in both the knee and hip joints, ultimately increasing the CMJ height in elite male athletes.

Analysis of thermal videos for detection of lie during interrogation

The lie-detection tests are traditionally carried out by well-trained experts using polygraph machines. However, it is time-consuming, invasive, and, overall, a cumbersome process, not admissible by the court of law. Trained individuals can easily flaunt these tests. On the other hand, facial thermal imaging could be more effective as it is noninvasive and could be a stealth method of tracking the facial blood flow patterns, which have been proven to detect deceit. This paper presents a method based on facial thermal imaging to detect deception in human subjects. The major issue in such research is the lack of proper real-life databases which emulate the crime scenes. In this paper, first, we have developed a database based on almost real-life theft incidents with due diligence using isolated subjects over a period of time at a government hospital under the plea of free health checkup. The experiment has been conducted at Midnapore Medical College and Hospital, West Bengal, India, with proper ethical committee approval. The participants are selected at the behest of the police department with habitual crime records. Most of them have been repeatedly charged with petty crimes of pick-pocketing and stealing. They are invited individually at different instances of time under the plea of medical checkup where they have been enticed to steal cash. It is followed by a two-stage process, a friendly interaction followed by a slightly tougher interrogation. Their forehead and periorbital region skin surface temperature are recorded by a hidden thermal camera. Upon analysis, conspicuous changes in the temperature profile and blood flow pattern have been observed in the individuals who stole money and those who did not.

Are we tackle ready? Cross‐sectional video analysis of match tackle characteristics in elite women's Rugby Union

AbstractThe tackle contest is the most common and most injurious match contact event in rugby and is an indicator of performance. Tackle Ready is World Rugby's tackle technique education program. Limited research has characterized the tackle contest in women's rugby. The purpose of this study is to: (1) identify the match situational characteristics, ball‐carrier and tackler technical actions demonstrated in elite women's Rugby Union and (2) to determine the extent to which Tackle Ready recommended tackle techniques were exhibited. Technical characteristics for 1500 tackle events in the 2022–2023 Women's Six Nations Championship were visually assessed according to a predefined coding framework and the Tackle Ready program. Tackles lacked full completion (0.2%) of the 22 coded Tackle Ready techniques with 47% of the recommended techniques demonstrated in each tackle on average (range 15%–98%). A high proportion of tackles involved two defenders (48%), approaching ball‐carriers from the side (38%) or oblique angles (39%), in an upright position (30%), and with initial contact made with the arm (51%). Incorrect pre‐contact head positioning and head placement upon contact accounted for 50% and 15% of tackles, respectively, and there was a mean of 14 (95% CI 11–18) head and neck contacts to a tackler and 18 (95% CI 14–22) head and neck contacts to a ball‐carrier per game. Targeted interventions to encourage adoption of recommended techniques are needed to reduce tackle‐related injury risk in women's rugby. This study provides valuable context for future discussion across law enforcement, coach education and gender‐specific tackle coaching in the women's game.

Air Handwriting using AI and ML

Air Handwriting using AI and ML

Recognizing online video genres using ensemble deep convolutional learning for digital media service management

It's evident that streaming services increasingly seek to automate the generation of film genres, a factor profoundly shaping a film's structure and target audience. Integrating a hybrid convolutional network into service management emerges as a valuable technique for discerning various video formats. This innovative approach not only categorizes video content but also facilitates personalized recommendations, content filtering, and targeted advertising. Given the tendency of films to blend elements from multiple genres, there is a growing demand for a real-time video classification system integrated with social media networks. Leveraging deep learning, we introduce a novel architecture for identifying and categorizing video film genres. Our approach utilizes an ensemble gated recurrent unit (ensGRU) neural network, effectively analyzing motion, spatial information, and temporal relationships. Additionally,w we present a sophisticated deep neural network incorporating the recommended GRU for video genre classification. The adoption of a dual-model strategy allows the network to capture robust video representations, leading to exceptional performance in multi-class movie classification. Evaluations conducted on well-known datasets, such as the LMTD dataset, consistently demonstrate the high performance of the proposed GRU model. This integrated model effectively extracts and learns features related to motion, spatial location, and temporal dynamics. Furthermore, the effectiveness of the proposed technique is validated using an engine block assembly dataset. Following the implementation of the enhanced architecture, the movie genre categorization system exhibits substantial improvements on the LMTD dataset, outperforming advanced models while requiring less computing power. With an impressive F1 score of 0.9102 and an accuracy rate of 94.4%, the recommended model consistently delivers outstanding results. Comparative evaluations underscore the accuracy and effectiveness of our proposed model in accurately identifying and classifying video genres, effectively extracting contextual information from video descriptors. Additionally, by integrating edge processing capabilities, our system achieves optimal real-time video processing and analysis, further enhancing its performance and relevance in dynamic media environments.

Video Analyses of Sudden Unexplained Deaths in Toddlers.

Video Analyses of Sudden Unexplained Deaths in Toddlers.

3-Dimensional Biomechanics of Noncontact Anterior Cruciate Ligament Injuries in Male Professional Soccer Players.

The understanding of noncontact anterior cruciate ligament (ACL) injury causation in soccer has improved over the past decades. Bidimensional video analyses have significantly augmented our awareness, representing to date the only practical method to describe injury biomechanics. However, the extent of the problem continues to raise serious concerns. To advance our understanding of the causal pathways leading to ACL injury with a large-scale reconstruction of 3-dimensional (3D) whole-body joint kinematics of injuries that occurred to male elite soccer players, as well as to compare the joint angle time course among situational patterns. Descriptive laboratory study. A total of 33 consecutive noncontact and indirect contact ACL injuries that occurred in 6 national and 2 international professional leagues (seasons 2020-2021 to 2022-2023 until December 2022) were analyzed: (1) multiview noncoaxial television images were inspected; (2) multiple camera views were taken from 400 ms before the initial ground contact to 200 ms after the injury frame; (3) a size-matched pitch was modeled and used to calibrate cameras; (4) a 3D skeletal model was adjusted to fit the player's pose in each frame/view; and (5) poses were interpolated, and Euler joint angles were extracted. The authors reconstructed the 3D lower limb joint kinematic curves preceding and during ACL injuries in 33 cases; notably, a sudden external (up to 5°) and then internal knee rotation was observed after the initial contact and before the injury frame. The overall kinematics at injury were knee moderately flexed (45.9°± 21.7°), abducted (4.3°± 5.1°), and externally rotated (3.0°± 6.4°); trunk shallowly flexed (17.4°± 12.5°) and rotated and tilted toward the injured side; and hip flexed (32.0°± 18.7°), abducted (31.1°± 12.0°), and slightly internally rotated (6.6°± 12.2°). Variable behaviors were observed at the ankle level. Via reconstruction of the sequence of whole-body joint motion leading to injury, we confirmed the accepted gross biomechanics (dynamic valgus trend). This study significantly enriches the current knowledge on multiplanar kinematic features (transverse and coronal plane rotations). Furthermore, it was shown that ACL injuries in male professional soccer players manifest through distinct biomechanical footprints related to the concurrent game situation. Interventions aimed at reducing ACL injuries in soccer should consider that environmental features (ie, situational patterns) affect injury mechanics.

Deep seafloor hydrothermal vent communities buried by volcanic ash from the 2022 Hunga eruption

Mass mortality of marine animals due to volcanic ash deposition is present in the fossil record but has rarely been documented in real time. Here, using remotely-operated vehicle video footage and analysis of ash collected at the seafloor, we describe the devastating effect of the record-breaking 2022 Hunga submarine volcanic eruption on endangered and vulnerable snail and mussel species that previously thrived at nearby deep-sea hydrothermal vents. In contrast to grazing, scavenging, filter-feeding, and predatory vent taxa, we observed mass mortality, likely due to smothering during burial by thick ash deposits, of the foundation species, which rely on symbiotic chemosynthetic bacteria for the bulk of their nutrition. This is important for our broad understanding of the natural disturbance of marine ecosystems by volcanic eruptions and for predicting the effects of anthropogenic disturbance, like deep-sea mining, on these unique seafloor habitats.

Digital Forms for All: A Holistic Multimodal Large Language Model Agent for Health Data Entry

Digital forms help us access services and opportunities, but they are not equally accessible to everyone, such as older adults or those with sensory impairments. Large language models (LLMs) and multimodal interfaces offer a unique opportunity to increase form accessibility. Informed by prior literature and needfinding, we built a holistic multimodal LLM agent for health data entry. We describe the process of designing and building our system, and the results of a study with older adults (N =10). All participants, regardless of age or disability status, were able to complete a standard 47-question form independently using our system---one blind participant said it was "a prayer answered." Our video analysis revealed how different modalities provided alternative interaction paths in complementary ways (e.g., the buttons helped resolve transcription errors and speech helped provide more options when the pre-canned answer choices were insufficient). We highlight key design guidelines, such as designing systems that dynamically adapt to individual needs.

Unsupervised machine learning for clustering forward head posture, protraction and retraction movement patterns based on craniocervical angle data in individuals with nonspecific neck pain

ObjectivesThe traditional understanding of craniocervical alignment emphasizes specific anatomical landmarks. However, recent research has challenged the reliance on forward head posture as the primary diagnostic criterion for neck pain. An advanced relationship exists between neck pain and craniocervical alignment, which requires a deeper exploration of diverse postures and movement patterns using advanced techniques, such as clustering analysis. We aimed to explore the complex relationship between craniocervical alignment, and neck pain and to categorize alignment patterns in individuals with nonspecific neck pain using the K-means algorithm.MethodsThis study included 229 office workers with nonspecific neck pain who applied unsupervised machine learning techniques. The craniocervical angles (CCA) during rest, protraction, and retraction were measured using two-dimensional video analysis, and neck pain severity was assessed using the Northwick Park Neck Pain Questionnaire (NPQ). CCA during sitting upright in a comfortable position was assessed to evaluate the resting CCA. The average of midpoints between repeated protraction and retraction measures was considered as the midpoint CCA. The K-means algorithm helped categorize participants into alignment clusters based on age, sex and CCA data.ResultsWe found no significant correlation between NPQ scores and CCA data, challenging the traditional understanding of neck pain and alignment. We observed a significant difference in age (F = 140.14, p < 0.001), NPQ total score (F = 115.83, p < 0.001), resting CCA (F = 79.22, p < 0.001), CCA during protraction (F = 33.98, p < 0.001), CCA during retraction (F = 40.40, p < 0.001), and midpoint CCA (F = 66.92, p < 0.001) among the three clusters and healthy controls. Cluster 1 was characterized by the lowest resting and midpoint CCA, and CCA during pro- and -retraction, indicating a significant forward head posture and a pattern of retraction restriction. Cluster 2, the oldest group, showed CCA measurements similar to healthy controls, yet reported the highest NPQ scores. Cluster 3 exhibited the highest CCA during protraction and retraction, suggesting a limitation in protraction movement.DiscussionAnalyzing 229 office workers, three distinct alignment patterns were identified, each with unique postural characteristics; therefore, treatments addressing posture should be individualized and not generalized across the population.

Identification of Counterfeit Videos using Deep Learning Methodology

The rise of deep learning has ushered in a proliferation of deep fake videos, posing significant challenges to the credibility of visual content. Our research introduces a groundbreaking approach by merging Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to enhance the accuracy of deepfake prediction. This unique integration, which has not been previously implemented, significantly boosts the model's capability to discern deepfakes. The synergy of CNNs and RNNs in our methodology represents an advancement, contributing to increased accuracy in detecting synthetic content. We leverage CNNs and RNNs for an efficient solution. First, we employ a Res-Next CNN to extract distinctive features from individual video frames, effectively encoding spatial information. These features are then used in the subsequent phase, where a LSTM-RNN models temporal dynamics within the videodata.The temporal aspect is crucial in differentiating deep fake videos due to subtle inconsistencies over time. The LSTM RNN processes the feature sequence, enabling the model to identify temporal patterns unique to deep fakes. This holistic approach, combining spatial and temporal analysis, enhances the model's ability to detect even highly convincing synthetic content. Our model is trained on a comprehensive dataset with rigorous evaluations, demonstrating competitive performance through standard metrics such as accuracy, precision. Practically, our model offers real- time video analysis, automatically identifying deep fake content and mitigating potential risks. Importantly, our approach is simple and robust, suitable for deployment across diverse scenarios. In summary, our research provides an effective solution to the critical issue of deepfake detection. By synergizing CNNs and LSTM-based RNNs, we offer a practical means to uphold the integrity of visual content in an era where digital information authenticity is paramount. Keywords— Deep Learning, CNN, RNN, Deepfake, LSTM, accuracy, precision, visual content, digital information

Analysis of short videos of bovine embryos can detect presence of cryodamage

Cryopreservation of bovine embryos has transformed animal breeding strategies by allowing storage of genetic material which enables efficient recipient utilization, sale and market­ing of embryos, and shipping and transport of embryos around the world. Advancements have been made in cryopreserva­tion techniques including the introduction of direct transfer ethylene glycol media, controlled rate freezers allowing pre­cise temperature control of the freezing curve and vitrifica­tion techniques. However, little advancement has been made to evaluate embryo survival of cryopreservation which results in the transfer of embryos which have suffered cryodamage and have no chance of establishing a pregnancy. The objective of this study was to use graphic image processing (GIP) and machine-learning (ML) techniques to evaluate embryo health post-cryopreservation.

Study of the effect of electromagnetic damping force on a magnet oscillating near a non-ferromagnetic conducting plate

Abstract We have designed an experiment that involves studying the effects of a conducting plate on the motion of an oscillating disc magnet. We have employed the video analysis method by ‘Tracker’ software to investigate the variation of electromagnetic damping coefficient with distance between the plate and the magnet. This experiment can indeed serve as a valuable educational tool for undergraduate students, covering topics such as damped oscillation, electromagnetic damping, Lenz's law, and eddy currents.

Endothelial function in healthy centenarians living in the Madonie’s district (Italy)

BackgroundEndothelial function declines with age and plays a critical role in cardiovascular health. Therefore, investigating endothelial function in successful aging models, such as centenarians, is of interest. Flow-mediated dilation (FMD) of the brachial artery is the gold standard for measuring endothelial function in vivo in humans. Therefore, we investigated, for the first time, the FMD of the brachial artery in a group of healthy centenarians. MethodsSelected as part of the ABCD project (nutrition, cardiovascular wellness, and diabetes) centenarians (aged ≥100 years) living in the municipalities of Madonie (Palermo, Italy) were compared with a younger (aged <65 years) sex-matched control group from the ABCD general cohort. FMD of the brachial artery was measured in all participants using a real-time computed video analysis system for B-mode ultrasound images. Body composition (bioimpedance), carotid intima-media thickness (IMT), and ankle-brachial index (ABI) were also measured. ResultsEleven participants (males 36.4 %; age: 101 ± 1 years) out of 28 healthy centenarians successfully cooperated with the FMD test procedures, which require remaining with the upper limb immobile for approximately 10 min. This subgroup was compared with a control group of 76 healthy and younger individuals (males 36.8 %; aged: 41 ± 14 years; P < 0.001). Centenarians exhibited better endothelial function than the control group (FMD: 12.1 ± 4.3 vs 8.6 ± 5.3 %; P < 0.05). The carotid IMT was higher in the centenarian group than in the control group (0.89 ± 0.09 vs 0.56 ± 0.18 mm; P < 0.001), whereas the ABI was comparable between the two groups. ConclusionsThis small group of centenarians demonstrated an unusually favorable endothelial function, which may contribute to their unique aging profile. Further research is needed to determine whether FMD is a valid prognostic marker for successful aging.

Kinematics of 90° change of direction in young football players: Insights for ACL injury prevention from the CUTtheACLstudy on 6008 trials.

To investigate the 90° change of direction (COD) task in an extensive cohort of competitive healthy football players within the CUTtheACLstudy and to provide normative values and differences between males and females for full-body kinematics based on two-dimensional (2D) video analysis and scoring system. One-thousand-and-two competitive football (soccer) players (age 16.3 ± 2.8 years, 264 females) were prospectively enroled. Each player performed three preplanned 90° COD tasks per limb. The 2D evaluation was performed through objective measures (collected through three high-speed cameras) of frontal and sagittal plane joint kinematics at the cut initial foot contact (IC) and maximum knee flexion angle. A previously published scoring system was adopted to measure the movement quality of the COD task. The scoring system included five criteria (limb stability [LS], pelvis stability [PS], trunk stability [TS], shock absorption [SA], movement strategy [MS]) ranked from 0/2 (nonadequate) to 2/2 (adequate) with a maximum score of 10/10. Normative data were provided for all the variables; statistical differences between male and female players were investigated (p < 0.05). A total of 6008 valid attempts were included. Frontal plane knee projection angle (FPKPA) at initial contact was 24.4 ± 9.8° (95thpercentile: FPKPA > 40°). The total score was ≤4/10 in 71.2% of the trials, the lowest subscores were LS and PS. Female players showed different movement patterns with lower hip and trunk flexion both at IC and maximum knee flexion angle (p < 0.01, ES = 0.41-0.64). Female players also showed worse scores than males in SA, MSand total score (p < 0.01). Female players seem more prone to stiffer lower limb strategy and greater pelvis-trunk frontal plane instability than males. Clinicians could adopt normative data and sex-specific differences in players' movement techniques to improve ACL injury risk mitigation protocols. Level IV.

Biomechanics Analysis of Normal Jump Shot and Fade-Away Jump Shot in Basketball

Basketball players normally use jump shots to score points during a game. The player must shoot the ball depending on their own experience that requires a long period of time to train. The player can learn faster and master the shooting skills with the assistance of video and data analysis. This paper determines the scoring effectiveness, the body posture and release angle of normal and fade–away jump shots in basketball using the biomechanics analysis. Recording devices were used to record the jump shots and the results were analysed by using several software including Wondershare Filmora, KMPlayer, Openpose, MATLAB, and Logger Pro. With the aid of biomechanics formula, MATLAB and Logger Pro software, the shooting angle, acceleration, energy, force, etc data were obtained. Results showed that the average angle of release that scored for both normal and fade-away jump shots were 59.4 and 59.5 degrees respectively. Normal jump shots had been concluded as more efficient due to 15 % higher scoring than the fade-away jump shots while they required 9.5 % less power to perform. Therefore, it was found that the improvement to the Openpose software can benefit many people. In potential future application, instead of detecting human posture, detecting objects might be a breakthrough for future application around the world.

Hybrid harris hawk-arithmetic optimization with deep learning-driven object detection and classification for surveillance video analysis

Hybrid harris hawk-arithmetic optimization with deep learning-driven object detection and classification for surveillance video analysis