Overlapping phenotypic features between Early Onset Ataxia (EOA) and Developmental Coordination Disorder (DCD) can complicate the clinical distinction of these disorders. Clinical rating scales are a common way to quantify movement disorders but in children these scales also rely on the observer’s assessment and interpretation. Despite the introduction of inertial measurement units for objective and more precise evaluation, special hardware is still required, restricting their widespread application. Gait video recordings of movement disorder patients are frequently captured in routine clinical settings, but there is presently no suitable quantitative analysis method for these recordings. Owing to advancements in computer vision technology, deep learning pose estimation techniques may soon be ready for convenient and low-cost clinical usage. This study presents a framework based on 2D video recording in the coronal plane and pose estimation for the quantitative assessment of gait in movement disorders. To allow the calculation of distance-based features, seven different methods to normalize 2D skeleton keypoint data derived from pose estimation using deep neural networks applied to freehand video recording of gait were evaluated. In our experiments, 15 children  were asked to walk naturally while being videotaped by a single camera in 1280 × 720 resolution at 25 frames per second. The high likelihood of the prediction of keypoint locations  demonstrates the potential for distance-based features derived from routine video recordings to assist in the clinical evaluation of movement in EOA and DCD. By comparison of mean absolute angle error and mean variance of distance, the normalization methods using the Euclidean (2D) distance of left shoulder and right hip, or the average distance from left shoulder to right hip and from right shoulder to left hip were found to better perform for deriving distance-based features and further quantitative assessment of movement disorders. Children with Early-Onset Ataxia (EOA) and Developmental Coordination Disorder (DCD) both show features of motor incoordination, hampering clinical distinction . Gait anInertial wearable sensors can provide an objective and feasible alternative for gait assessment . The useHuman pose estimation is one of the fundamental tasks in computer vision. This task can often be subdivided into single-person and multi-person pose estimation, as well as 2D and 3D pose estimation, depending on whether the video or image dataset contains multi-person or 3D depth information. Owing to the fast development of deep learning, many convolutional neural network (CNN) based frameworks have been designed and published, such as Maskr-cnn  DeeperCuIn the daily clinical setting, neurologists routinely record patients’ movements for further evaluation. The ubiquity of video cameras in outpatient clinics and recent advances in video-based pose estimation have motivated us to design a 2D skeleton-based method for quantitative analysis of movement disorders using video images taken in the coronal plane. In a clinical setting, sagittal plane video recordings are typically not available, due to space limitations. Through pose estimation, the joint coordinates of the patient in single camera video recordings can be obtained in a convenient and low-cost way. The use of 2D video-based motion capture for gait analysis dates back to the last century . It has Here, we propose and compare seven different normalization methods that enable the calculation of distance-based features derived from pose estimation results. The normalization method needs to address two issues: (1) the skeleton size varies depending on the distance from the camera in every frame, (2) the skeleton position in each frame might change due to camera instabilities. These problems induce nonphysiological frame-to-frame variability, hindering calculation and comparison of distance-based features. We here initially apply the AlphaPose deep learning model and PoseFlow framework to obtain skeleton keypoint data from ataxia, DCD and the controls. We anticipate that the best normalization method will maintain the constancy of certain distances in the coronal plane, such as the distance between the two shoulders when walking, while maintaining the variability of other distances, such as the distance between the two wrists.The entire pipeline for quantitative assessment of gait from freehand 2D camera recordings is summarized in The data for this study were collected at the University Medical Center Groningen , in accordance with local research and integrity codes. Fifteen children, including five with EOA , five with DCD , and five healthy controls  participated in the experiment. All included children older than 12 years of age and all parents of the children included provided informed consent before study enrollment. Children younger than 12 years of age also provided informed assent. EOA patients had radiologic (MRI), metabolic, and laboratory and genetic testing at the department of (pediatric) neurology at the University Medical Center Groningen as part of their diagnostic evaluation. DCD patients were also evaluated at the pediatric neurology outpatient clinic. When applicable, these evaluations included MRI, electromyography, muscle ultrasound, and/or laboratory and sometimes also genetic testing to exclude other underlying neurologic disorders.Children were asked to walk freely and repeatedly in a straight line while an experimenter stood at the end of the corridor holding a single 2D video camera  facing the subjects for recording. They were asked to walk at their own pace in a corridor of approximately 15 m, make a 180 degree turn and return to the starting position, in accordance with the SARA regular gait task guidelines. EOA was clinically confirmed in accordance with its definition . For furAfter cleaning the video data, we used AlphaPose, a deep neural network model, to estimate the 2D locations of skeleton keypoints. Here, we utilized the Yolo-v3 detector , pretraiN continuous skeletons , where skeleton Si of the i-th frame (i = 1… N) is composed of 17 pairs of coordinates (in pixels) representing all 17 keypoints.We proposed and analyzed different normalization methods. Here, the original keypoint data of each video segment were presented as a sequence of It should be noted that movement inside the coronal plane (such as up-and-down or side-to-side movement of a limb) has no effect on distance computation, but movement outside the plane  does. For this reason, we consider both the Euclidean distance between two joints and the distance between two points in the horizontal and vertical directions, respectively, for the different normalization methods. We consider two-step solutions, that include position shifting and size scaling.Position shifting. This method achieves the result that the mid- shoulder point becomes the origin  in each frame, by shifting all coordinates according to:Step 1: Here , (2) and (4) together can be written as follows:To illustrate the effect of the different normalization steps on skeleton size and position, we show several frames of an EOA patient walking towards the camera at each step of the normalization process in Performance was assessed by calculating the mean value of the absolute error of the angle (mean absolute angle error) and the mean variance of the distance between certain keypoints. It is important to note that we cannot obtain any true physical distance measurements because we lost depth dimension information from the start by using a 2D camera. Therefore, our evaluation metrics are inspired by our clinical task, with the expectation that in the ideal case (1) there should be no changes in angles between vectors in the coronal plane before and after normalization, (2) normalization should maintain the variability of the distance between the two wrists and the two ankles, and (3) the constancy of the distances between the two shoulders and between the two hips is maintained . We selected four relative angles (angles between vectors): the angles between the left- and right-wrist–elbow vector and the elbow–shoulder vector, and the angles between the hip–knee vector and the knee–ankle vector. We also selected eight absolute angles  related to the left- and right-wrist–elbow, elbow–shoulder, hip–knee, and knee–ankle vectors. For comparison of the mean variance of distance, we selected the distance between the two shoulder, wrist, hip, and ankle keypoints, expecting that after normalization the variance of the distance between the two shoulder and between the two hip keypoints should be close to 0 , but the variance of the distance between the two wrist and two ankle keypoints should be as large as possible (expecting most variability in movement from these keypoints).t-test was conducted to compare the likelihood of prediction of keypoint locations before data cleaning and after data cleaning. After noisy frames and the standing and turning around segments were removed, there was a significant increase of the probability  = 3.36, p < 0.05).The results for the mean absolute angle error are provided in p = 0.16; wrist: U = 62, p = 0.29; hip: U = 57, p = 0.20; ankle: U = 68, p = 0.41; Mann–Whitney U-tests). Although the shoulder and hip variances of the ASH method obtained the lowest variances  among all normalization methods, there was no significant difference between the MS/MH-d and ASH methods either . However, this method balanced using the distance between the left shoulder and right hip and the right shoulder and left hip to achieve a more stable performance.p = 0.048; ASH: U = 42, p = 0.045). As the goal of these tests was only to identify the best performing method(s), we did not correct for multiple comparisons. To conclude, both the LS/RH-d, and ASH normalization methods performed reasonably well and similarly in our task.We subsequently plotted the distance variance for EOA, DCD, and the controls separately in To better understand what our normalization is accomplishing, we plotted the distribution of the 17 keypoints before and after LS/RH-d normalization for one segment of a DCD child walking towards/away from the camera See . The cooIn this study, we present a framework based on 2D video pose estimation and proposed different normalization methods for skeleton data to enable the quantitative assessment of movement disorders. We found that AlphaPose and PoseTrack based keypoint localization can achieve relatively high confidence in coronal plane 2D recordings, and normalization methods in this framework could be helpful for the calculation of distance- based features.The high likelihood after cleaning in our dataset from AlphaPose and PoseTrack with pretraining in the MSCOCO dataset supports the potential for quantitative analysis of routine video recordings for assistance in diagnosis and daily monitoring. Our video data, which included 15 children walking freely in a corridor, was captured with a single camera at a resolution of only 1280 × 720 pixels and a frame rate of 25 frames per second. The major reason the confidence cannot achieve values higher than 0.9 after cleaning is that keypoints on the face, such as the nose, eyes, and ears, cannot be seen or have low spatial resolution as people walk away from the camera. Yet, the likelihood findings show that even at low video resolution, the pose estimation model has a high level of reliability, and thus provides a solid platform for further study and demonstrates that it is promising for clinical application.Assessing movement disorders objectively and accurately is notoriously difficult. Even though machine learning models have been used to predict gait characteristics , currentThis study has some limitations. First, the children with EOA were slightly older than the DCD and the control children. However, as healthy and DCD children grow up, the variability in coordinative movements declines ,48, and Our normalization framework applied to 2D freehand single camera video recording data demonstrated a promising application for the quantitative assessment of movement disorders in a convenient and objective manner. For future further evaluation of the proposed normalization methods, after inclusion of a calibration step in prospectively collected video recordings, 3D optical systems employing reflective markers could be utilized to establish ground truth. As such, this study is a preliminary step towards quantitative analysis of clinically observed gait using single camera freehand video recording. In addition, if more data is collected, machine learning algorithms could be developed to help differentiate between different movement disorders.


Aim: To investigate the reliability and educational value of YouTube videos of minimally invasive complete mesocolic excision with right hemicolectomy procedures.Materials and methods: We searched YouTube with the terms “Laparoscopic and Robotic Complete Mesocolic Excision with Right Hemicolectomy” on January 12, 2021. To assess the reliability of the videos, we evaluated nine steps in each video and scored the videos based on the key steps they contained. The videos were divided into three groups according to the source of the upload. The total number of views, length, time since upload, and the number of likes, dislikes, and comments were recorded for each video. Narration, the use of descriptive subtitles, and the upload status by an expert surgeon were also examined.Results: Sixty-eight videos were included in the study. A positive significant correlation was identified between the comprehensiveness score (CS) and the number of views (p=0.025). The CSs of the videos accessed from academic channels, as well as those accessed from journals, congress, and association channels, recorded higher CSs than those obtained from the personal channels of consultants (p=0.003). It was also found that CSs were higher in the videos of expert surgeons (p<0.001) and narrated videos (p<0.001).Conclusion: Not all YouTube videos on this subject have reliability and educational value. Surgical videos on YouTube may be evaluated by a video review commission formed by academic institutions, surgical associations, or expert surgeons, and videos suitable for education could be brought together and published via a free channel. Colorectal cancer is the third most common type of cancer in both men and women. According to Global Cancer Observatory (GLOBOCAN) data, there are approximately two million new cases per year worldwide . The effThe COVID-19 pandemic has had a severe impact on the quantity and quality of surgical training. A study conducted by Purdy et al. reported that there had been a 33.5% reduction in the total number of major operations performed by 1,358 general surgery residents during the pandemic period when compared to the pre-pandemic period . YouTubeA search on YouTube was conducted using the search terms “Laparoscopic Complete Mesocolic Excision with Right Hemicolectomy” and “Robotic Complete Mesocolic Excision with Right Hemicolectomy’’ on January 12, 2021, and the search results were sorted using the filter “Sort by View Count.” It was assumed that filters such as “medical student” and “surgical trainee,” and videos with a high number of views and interactions, would be of higher quality for medical education and the visualization of surgical techniques. The videos were saved in a playlist as the search results on YouTube can change from day to day, after which duplicate videos (n=6) and videos without audio narration in English (n=3) were removed. Videos in multiple parts were treated as a single video (n=1). As a result of the search, 68 videos were obtained, 46 of which were of laparoscopic procedures, and 24 were of robotic complete mesocolic excisions. To assess the reliability of the videos, we evaluated nine steps in each video, based on the steps detailed in an article published by Strey et al. with some modifications . The vidThe videos were divided into three groups based on the source of the upload. Source 1: Academia-based channels . Source 2: Educational videos uploaded by specialized  surgical associations, colorectal surgery congress videos, and YouTube video channels of Colorectal Journals. Source 3: Consultant videos .The total number of views, length, and time since upload, as well as the numbers of likes, dislikes, and comments, were recorded for each video. Viewers' interactions with the videos were calculated in terms of “views per day” .The videos were also examined for narration, descriptive subtitle presence, and upload status by an expert surgeon. The criterion according to which the surgeons were classified as experts was having at least five publications on minimally invasive colorectal surgery listed in PubMed within the last two years.Statistical methodThe consistency of coverage score to normal distribution was examined with the Shapiro-Wilk test. The scope score was reported as a symptom statistically with the median, interquartile range, minimum and maximum values. In comparing the coverage score, Mann-Whitney U and Kruskal Wallis tests were used, and the subgroup analyses were made using the Dunn Bonferroni test after the Kruskal Wallis test. The relationships between the scope score and other discrete and continuous variables in the study were examined by correlation analysis, and the Spearman correlation coefficient was calculated. Statistical analyses were performed using Statistical Package for Social Sciences (SPSS) version 23 . A type I error rate of 5% was considered statistically significant for all statistical comparisons.Of the 68 videos watched, 46 were laparoscopic and 23 were robotic complete mesocolic excision videos. The distribution of responses to the items used in the comprehensiveness calculation is presented in Table A comparison of the comprehensiveness scores obtained for each of the 68 videos based on the source of the video, the expertise of the surgeon in the video, the narration in the video, and the presence of a descriptive subtitle in the video is presented in Table It was determined that the comprehensiveness scores differed based on whether the surgeon in the video was an expert or not (p<0.001). The comprehensiveness scores of the videos featuring an expert surgeon (14( [minimum-maximum: 7 to 18]) were higher than those of videos that did not feature an expert surgeon (10 [min-max: 2 to 18]) (p<0.001).Similarly, the comprehensiveness scores were found to be higher for narrated videos (15 [min-max: 7 to 18]) than for non-narrated videos (10 [min-max: 2 to 16]) (p<0.001).It was noted, however, that the comprehensiveness score was unaffected by the presence or absence of descriptive subtitles in the video (p=0.210). The median comprehensiveness score of videos supported by descriptive subtitles was 14 (min-max: 7 to 18) and 11.50 (min-max: 2 to 18) for those not supported by subtitles.Table The median number of views of the videos included in the study was 638.50 , and a significant positive correlation was found between the comprehensiveness score and the number of views . The comprehensiveness score of the videos can be expected to increase with an increase in the number of views. The median video length value of the videos included in the study was 9.08 minutes (min-max: 3.43 to 75.08), and there was no correlation between the comprehensiveness score and video duration (p=0.954). The time since the upload date of the videos included in the study was calculated as 933 (min-max: 13 to 2310) days. It was determined that the upload date of the video did not affect the comprehensiveness score (p=0.826). The median number of views of the videos was determined as 0.84 (min-max: 0.02 to 28.74).It was observed that the comprehensiveness score was unaffected by the number of dislikes of the videos (p=0.202). The median comprehensiveness score of the videos with dislikes was 14 (min-max: 9 to 18) and the comprehensiveness score of the videos with no dislikes was 12 (min-max: 2 to 18).Similarly, the comprehensiveness score was unaffected by video comments (p=0.844). The median comprehensiveness score of the videos with comments was 14 (min-max: 9 to 18) and the comprehensiveness score of the videos with no comments was 14 (min-max: 2 to 18).YouTube is a giant Internet video broadcasting platform that attracts more than one billion video views per day and more than 500 hours of video uploaded per minute . Some ofThe working hours of surgical residents are limited to 80 hours a week in the United States and 48 hours a week in Europe, and consequently, those in Europe perform fewer surgeries during surgical training . ResidenIn operations that require a more specific and more effective learning process, such as oncological surgery, there has been a growing preference for learning techniques that can reduce the disadvantages associated with the pandemic. These include virtual online lectures and didactics, video and teleconferencing, interactive online surgical platforms and VR-simulators, live interactive virtual rounds, laparoscopic box training, homemade surgical simulation models, and video-based online platforms  .It is thought that e-learning will make important contributions to the field by compensating for the deficiencies in theoretical and practical training. Jayakumar et al. listed the advantages of e-learning as easy access, learning flexibility, easy updating, multimedia presentation, and personalized learning, while the disadvantages were stated as dependence on internet speed, high initial cost, and the need for programming expertise . SurgicaIn the study conducted by Yee et al., it was stated that the factors affecting the quality of a video presentation can be divided into three groups. The first group includes factors related to the surgeon , the second group includes factors related to the procedure , and the third group includes factors related to the purpose of the video  . We beliStudy limitationsThis study has several limitations. Only English videos were included. The videos were filtered according to view count. As is known, video count is a dynamic process and can change every moment. The videos included only laparoscopic or robotic surgeries. Watching the videos together might have caused some bias, but this was eliminated with the consensus of the three surgeons.The results of this study indicate that the reliability and quality of health-related videos on YouTube are insufficient. In the future, surgical videos on YouTube may be evaluated by a video review commission formed by academic institutions, surgical associations, or expert surgeons, and videos suitable for education could be brought together and published via a free channel. Furthermore, financial support may be provided to encourage content creators to make more useful videos. In addition, new policies and strategies should be developed to audit health-related content uploaded to YouTube before it can be published.


The prevalence and role of malnutrition in periprosthetic joint infection (PJI) remain unclear. This study aimed to use measurable nutritional screening tools to assess the prevalence of malnutrition in PJI patients during two-stage exchange arthroplasty and to explore the association between malnutrition and treatment failure. Our study retrospectively included 183 PJI cases who underwent 1st stage exchange arthroplasty and had available nutritional parameters, of which 167 proceeded with 2nd stage reimplantation. The recently proposed Musculoskeletal Infection Society (MSIS) Outcome Reporting Tool was used to determine clinical outcomes. The Controlling Nutritional Status (CONUT), Nutritional Risk Index (NRI), and Naples Prognostic Score (NPS) were used to identify malnutrition at 1st and 2nd stage exchange, respectively. Multivariate logistic regression analyses were performed to determine the association between malnutrition and treatment failure. Restricted cubic spline models were further used to explore the dose–response association. Additionally, risk factors for moderate-to-severe malnutrition were evaluated. Malnourished patients identified by CONUT, NPS, and NRI accounted for 48.1% (88/183), 98.9% (181/183), and 55.7% (102/183) of patients at 1st stage, and 9.0% (15/167), 41.9% (70/167), and 43.1% (72/167) at 2nd stage, indicating a significant improvement in nutritional status. We found that poorer nutritional status was a predictor of treatment failure, with CONUT performing best as a predictive tool. Moderate-to-severe malnutrition at 1st stage identified by CONUT was significantly related to treatment failure directly caused by PJI (odds ratio [OR] = 5.86), while the OR was raised to 12.15 at 2nd stage (OR = 12.15). The linear dose–response associations between them were also confirmed (P for nonlinearity at both 1st and 2nd stage > 0.05). As for total treatment failure, moderate-to-severe malnutrition as determined by CONUT was associated with a 1.96-fold and 8.99-fold elevated risk at the 1st and 2nd stages, respectively. Age ≥ 68 years (OR = 5.35) and an increased number of previous surgeries (OR = 2.04) may be risk factors for moderate-to-severe malnutrition. Overall, the prevalence of malnutrition in PJI patients is very high. Given the strong association between moderate-to-severe malnutrition identified by CONUT and PJI treatment failure, COUNT could be a promising tool to evaluate the nutritional status of PJI patients to optimize treatment outcomes. Periprosthetic joint infection (PJI) is the most devastating complication after total joint arthroplasty (TJA). The number of PJIs is estimated to grow exponentially in the next decade due to the aging population and the dramatic increase of TJA ,2,3. TheMalnutrition generally implies undernutrition and refers to deviations from adequate and optimal nutritional status . As a moExtensive studies have reported a synergistic relationship between malnutrition and infection. The main reason for the increased susceptibility to infection in malnourished hosts may be the extensive compromise of immune function, with potential mechanisms including impaired mucosal and skin barrier function, reduced macrophage numbers and phagocytosis, decreased natural killer cell activity, and defects in the adaptive immune system, represented by T cells . The immMore critically, in clinical settings, pathological conditions such as chronic infections and cancer have been documented to induce a higher prevalence of malnutrition, resulting in worse clinical outcomes ,25,26,27Previous nutritional assessments in arthroplasty were primarily based on individual blood parameters ,18,30. NTherefore, this study aimed to determine the prevalence of malnutrition identified by INSTs in PJI patients and to explore the association between malnutrition and treatment outcomes. Meanwhile, it could provide further clinical insights into malnutrition in infectious diseases. After Institutional Review Board approval, we retrospectively reviewed 195 suspected PJI cases who received 1st stage exchange arthroplasty at our institution and had available nutritional parameters between January 2009 and January 2020. The required nutritional laboratory tests included routine blood and biochemical tests. We excluded 12 patients, including 8 patients who did not meet the International Consensus Meeting (ICM) 2018 criteria  and 4 paTwo-stage exchange arthroplasty is the standard regimen for chronic PJI at our institution. Institution-based surgical techniques performed by high-volume surgeons were used for all patients. Briefly, the 1st stage exchange consists of removal of the infected component, thorough debridement, and placement of an antibiotic-impregnated spacer. Multiple microbiological cultures guide the systematic administration of antibiotics. After 6–12 weeks of antibiotic therapy, patients are evaluated comprehensively for the timing of 2nd stage reimplantation, including laboratory tests and clinical signs. If the infection is considered to be eradicated, a redebridement is performed and a new prosthesis is reinserted. In our study, 167 patients proceeded with 2nd stage reimplantation. Interstage attrition occurred in 16 patients. Of them, five patients were assessed as medically unfit for reimplantation, six died, three were reluctant to proceed with reimplantation, and two underwent salvage surgery . Two investigators independently reviewed the patients’ medical records of 1st and 2nd stage exchange. Nutrition-related parameters were extracted, including laboratory values of serum albumin, lymphocytes, neutrophils, monocytes, and total cholesterol. Based on the availability of the parameters and their essential value in the diagnosis and treatment of PJI, c-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were also obtained to reflect the systemic inflammatory response ,40. In aThe CONUT, NPS, and NRI were used to assess the nutritional status of PJI patients. The CONUT score was calculated from total cholesterol, lymphocytes, and serum albumin, with 0–1, 2–4, and >5 representing normal, mild, and moderate-to-severe malnutrition, respectively . The NPSThe mean follow-up time was 7.56  years after resection. The recently proposed Musculoskeletal Infection Society (MSIS) Outcome Reporting Tool was used to determine clinical outcomes . This tot-tests. Categorical variables were compared using chi-square tests and Fisher exact tests. Venn diagrams depicted the relationship between malnourished patients identified by various INSTs. We also performed Pearson correlation analyses to explore the correlation of nutritional scores with indicators of systemic inflammation or other nutritional scores. Values were presented as mean ± SD or number of subjects (percentage). Differences in continuous variables between groups were compared using independent-samples p < 0.3 in univariate analysis. All logistic regression analyses reported adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Additionally, after adjusting baseline characteristics, we used restricted cubic splines (RCS) with three knots to evaluate the dose–response relationship of CONUT score with treatment failure directly related to PJI. After adjusting baseline characteristics such as age, gender, Body Mass Index (BMI), pathogens, previous surgeries, knee or hip joints, primary diagnosis, smoking, and comorbidities, the associations between malnutrition at the 1st or 2nd stage exchange and failures directly related to PJI were assessed using logistic regression analysis. We investigated the impact of mild or moderate-to-severe malnutrition on outcomes, respectively, with normal nutritional status identified by different INSTs as the reference category. Another logistic regression analysis was performed to identify risk factors of moderate-to-severe malnutrition identified by CONUT at 1st stage. The receiver operating characteristic (ROC) curve determined the optimal cutoff value of age. Multivariate analysis was performed for variables with p < 0.05 was considered to indicate statistical significance. All statistical analyses were performed by SPSS version 20  and R software version 3.8.1 . 2. The most common causative organism and primary diagnoses were coagulase-negative staphylococci (28.4%) and osteoarthritis (28.4%). The study included 183 PJI patients who underwent 1st stage exchange, and their baseline characteristics are presented in p < 0.001) compared to those at the 1st stage (As shown in st stage . p< 0.001). In addition, correlation analysis of the three INSTs and ESR or CRP revealed a close association between poorer nutritional status and stronger inflammatory response (response . p = 0.016). At the 2nd stage, the relative risk of failure in patients with moderate-to-severe malnutrition identified by CONUT or NPS increased to 12.15  or 14.39 , respectively. Although statistically insignificant, moderate-to-severe malnutrition determined by NRI also tended to be associated with treatment failure directly related to PJI . Given the good predictive value of moderate-to-severe malnutrition as determined by CONUT, we further explored its association with total treatment failure. It was associated with a 1.96-fold and 8.99-fold elevated risk at the 1st and 2nd stage, respectively (As shown in ectively . p = 0.031) and increased number of previous surgeries  as independent risk factors. Compared with osteoarthritis, a primary diagnosis of osteonecrosis of the femoral head  may be a protective factor. We further evaluated the predictors of moderate-to-severe malnutrition identified by CONUT. Univariate logistic regression analysis identified age, gender, number of previous surgeries, and primary diagnosis as potential risk factors. The ROC curve indicated that an optimal cut-off value of age was 68 years. Malnutrition has been extensively documented in the orthopedic literature to be closely associated with adverse clinical outcomes ,14,15,16Malnutrition is becoming a widely recognized comorbidity in preventing and treating musculoskeletal disorders . HoweverThe association between nutritional status and clinical outcomes has been confirmed in the orthopedic literature. Three meta-analyses have shown that malnutrition increases the risk of surgical site infection after TJA ,48,49. AGiven that malnutrition is common in patients with PJI and is associated with treatment failure, the question remains as to which tool is more appropriate for clinicians to use to identify malnourished PJI patients. Our results suggested that CONUT may have a better potential predictive value, although there was a positive correlation between CONUT, NPS, and NRI. In addition, NPS and NRI showed a stronger relationship with ESR. This might be explained by the fact that different tools contain different parameters or different thresholds for the same parameter. Only albumin was common among the parameters included in the three screening tools. However, in the NPS and CONUT scoring systems, the diagnostic threshold for malnutrition is 40 g/L and 35 g/L, respectively, while it is used as a continuous variable in the NRI. As we have seen, the three screening tools showed poor concordance in identifying malnutrition, with prevalence rates ranging from 48.1% to 98.9%, revealing that they are not interchangeable. The above phenomenon has also been demonstrated in studies from other fields ,37,53. MAnother significant implication of this research is that it could help identify patients at risk for moderate-to-severe malnutrition. The current consensus is that older adults are susceptible to nutritional problems and eventually to malnutrition through various mechanisms . Our resPrevious studies have confirmed that malnutrition plays a detrimental role in different populations ,63,64. HSeveral limitations were considered in our study. First, the study design was retrospective, with a limited number of patients enrolled, and certain biases were inherent. We may be able to conduct larger sample size studies in the future and allow for stratified analyses to improve the robustness of the results and explore the impact of different factors on the results. Second, despite the execution of standard institutional treatment guidelines, patient management variation persists over 10 years. Third, only nutritional status at baseline was available, and no indicators were dynamically observed during follow-up. Due to the lack of knowledge about the patient’s diet, there are unknowns related to the effects of macro- and micronutrients as well as dietary patterns on the progression and treatment of PJI. Additionally, the identification of malnutrition was based on definitions, and the exploration of thresholds for each INST score may further strengthen our conclusions. Although ESR and CRP are the most commonly used indicators in PJI diagnosis and reimplantation studies, future exploration of additional inflammatory indicators may provide more information on the nutritional and systemic inflammatory status. Finally, the identification of malnutrition is exclusively dependent on blood parameters and does not allow for the assessment of other conditions that may lead to immune compromise, such as overnutrition. Direct measurement of body composition or scoring questionnaire-based screening, such as the Nutritional Risk Screening 2002 and Malnutrition Universal Screening Tool, may provide new insights into this issue. Overall, the significance of the present study is to report the alarming prevalence of malnutrition in patients with PJI and to explore the significant association of malnutrition with their treatment failure for the first time, which means that we have a great scope to improve their prognosis. Given the dramatic increase in the incidence of PJI, we strongly recommend routine nutritional assessment for patients with PJI. Additionally, we highlighted the need for further research to develop targeted interventions and improve clinical outcomes in this vulnerable population. Overall, the prevalence of malnutrition in PJI patients is very high, even exceeding that in some common cancers. Moderate-to-severe malnutrition identified by CONUT at either stage is associated with treatment failure. In addition, advanced age and increased number of previous surgery increase the risk of moderate-to-severe malnutrition. We strongly recommend routine nutritional screening and improving malnutrition in PJI patients, especially those at high risk.


The COVID-19 pandemic is the first pandemic where social media platforms relayed information on a large scale, enabling an “infodemic” of conflicting information which undermined the global response to the pandemic. Understanding how the information circulated and evolved on social media platforms is essential for planning future public health campaigns. This study investigated what types of themes about COVID-19 were most viewed on YouTube during the first 8 months of the pandemic, and how COVID-19 themes progressed over this period.We analyzed top-viewed YouTube COVID-19-related videos in English from December 1, 2019 to August 16, 2020 with an open inductive content analysis. We coded 536 videos associated with 1.1 billion views across the study period. East Asian countries were the first to report the virus, while most of the top-viewed videos in English were from the US. Videos from straight news outlets dominated the top-viewed videos throughout the outbreak, and public health authorities contributed the fewest. Although straight news was the dominant COVID-19 video source with various types of themes, its viewership per video was similar to that for entertainment news and YouTubers after March.We found, first, that collective public attention to the COVID-19 pandemic on YouTube peaked around March 2020, before the outbreak peaked, and flattened afterwards despite a spike in worldwide cases. Second, more videos focused on prevention early on, but videos with political themes increased through time. Third, regarding prevention and control measures, masking received much less attention than lockdown and social distancing in the study period.Our study suggests that a transition of focus from science to politics on social media intensified the COVID-19 infodemic and may have weakened mitigation measures during the first waves of the COVID-19 pandemic. It is recommended that authorities should consider co-operating with reputable social media influencers to promote health campaigns and improve health literacy. In addition, given high levels of globalization of social platforms and polarization of users, tailoring communication towards different digital communities is likely to be essential.The online version contains supplementary material available at 10.1186/s12889-022-13151-7. The coronavirus SARS-CoV-2 spread coronavirus disease COVID-19) around the world in early 2020 9 around . It brouAs the leading online social platform in the United States  and the While there have been investigations of themes, sources, and/or engagement on YouTube , 28 or oOn social media, all users , media outlets, and governments) can be both content generators and consumers, and they all compete for public attention to their messages . This competition can affect public awareness and the ability of health organizations to promote their presumably helpful messages , 36. HerData were collected on August 25, 2020, using the YouTube API v3 in Python. We found the top up-to-50 most viewed videos released each week from December 1, 2019 to August 16, 2020 by searching for the keywords “coronavirus,” “COVID” and “Wuhan.” In addition, “SARS” was used as a keyword before February 2020 to include videos about the SARS-like disease before it was known to be caused specifically by SARS-CoV-2. The start date was chosen such that it would slightly predate the pandemic, while the end date was chosen to be close to the date of collection, while ensuring that each video would have at least one week of time to accumulate views before the date of collection.Each week, videos were selected if they were identified (as previously described), as being in the top 20 most viewed videos of our original keyword search, or if they received over half a million views and were in the top 20 after exclusions. The 1/2 million views was arbitrarily decided as a practical cutoff point for a relatively popular video; we did not alter this cutoff based on the geographic origin of each video because most videos can accrue views from anywhere in the world. The following were excluded: live videos, non-English videos without English subtitles, and videos found by the search but unrelated  to COVID-19. Some of the early weeks had only a few qualifying videos. Google search interest for the topic ``Coronavirus disease 2019’’ from the weekly Google Trend data was collected from December 1, 2019 to August 16 for comparison with YouTube videos view interests. The search interest data of India, the United Kingdom, the United States and the world were selected for comparison , both of whom had participated in the creation of the coding book, as well as having multiple rounds of coding practices. Consensus was achieved by discussion between coders and the first author (CS). Each video was assigned a code by one of the coders. Both coders also coded 5 percent of the videos assigned to the other to assess inter-coder reliability.We evaluated the clarity  of obserCohen’s Kappa statistic for inter-coder reliability was 0.76, which is considered acceptable for content analysis . OverallCollectively, the 536 coded videos were viewed over 1.1 billion times in total, as of August 25, 2020. The earliest videos selected for coding under our criteria were from Singapore on January 3rd, 2020 (see “Chinese authorities working to identify virus behind pneumonia outbreak in Wuhan” in Table Korea on the 10th of January “New type of coronavirus found for pneumonia outbreak in China: WHO” (video number 11 in Table Thailand on the 13th “Thailand reports first case of Wuhan coronavirus outside China” (video number 12),UK on the 18th “Could this coronavirus be Disease X? Everything you need to know about the mystery virus in China” (video number 13),USA on the 19th “See where officials believe the coronavirus started” (video number 14),China on the 23rd “Coronavirus patient in Wuhan expected to leave hospital after ECMO support” (video number 15), andCanada on the 25th “Coronavirus Q&A: Separating fact from fiction” (video number 16).East Asian countries were the first to report the virus, but the United States became the leading country by view counts afterwards. After Hong Kong and Singapore, source countries in January 2020 . 27/225 (12.0%) videos published before April 8, 2020 had themes of politics and blame, compared to 83/331 (26.7%) videos published on or after April 8, 2020  when a video devotes more time to that theme than to others.Additional file 2: Table2. Codedvideocountsbytheme. Thenumber(n)ofvideoswitheachtheme. The median (interquartile range) of views, likes, dislikes, and comments for videos with each theme. M denotes millions, while k denotes thousands.Additional file 3: Table 3. Examples of Videos Viewed Meeting the Criteria for Inclusion from January to August 2020.Additional file 4: Table 4. All types of sources identified and coded.Additional file 5: Table 5. Coded video counts by source. The number (n) of videos with each source type . The median (interquartile range) of views, likes, dislikes, and comments for videos published by each source type. M denotes millions, while k denotes thousands.Additional file 6: Table 6. Aggregate characteristics of all coded videos.


Dialogue sentiment analysis is a hot topic in the field of artificial intelligence in recent years, in which the construction of multimodal corpus is the key part of dialogue sentiment analysis. With the rapid development of the Internet of Things (IoT), it provides a new means to collect the multiparty dialogues to construct a multimodal corpus. The rapid development of Mobile Edge Computing (MEC) provides a new platform for the construction of multimodal corpus. In this paper, we construct a multimodal corpus on MEC servers to make full use of the storage space distributed at the edge of the network according to the procedure of constructing a multimodal corpus that we propose. At the same time, we build a deep learning model  and use the constructed corpus to train the deep learning model for sentiment on MEC servers to make full use of the computing power distributed at the edge of the network. We carry out experiments based on real-world dataset collected by IoT devices, and the results validate the effectiveness of our sentiment analysis model. With the rapid development of the Internet of Things (IoT), the number of connected things is continuously increasing as well as their interactions –4. At thThe traditional centralized network cannot meet the needs of mobile users due to low storage capacity, high energy consumption, low bandwidth, and high latency , 10. MobWhile emotional analysis has been successful for text, it is a question that has not been fully studied for data, which contain two or three modes of text, audio, and vision simultaneously. The biggest setbacks for studies in this direction are lack of a proper dataset and methodology , 21. HowThe construction of the different corpora has similarities in many aspects such as the data used, annotation process, and annotation specification, which has certain reference value for us to use the IoT devices to collect data for construction of corpus. At the same time, the construction of the different corpora can provide some guidance and reference for the data collected by IoT devices from daily life or from situation comedies. At present, English corpora are considered the most abundant resource. Therefore, this paper, starting from English multimodal corpora, introduces the related subtasks and corresponding corpora as well as the latest research work on the corpora through sorting out different multimodal sentimental analysis subtasks.In 2016, Niu's team introduced a multiview sentiment analysis dataset (MVSA) including a set of image-text pairs with manual annotations collected from Twitter, which is annotated with positive, neutral, and negative sentimental labels . The MVSIn 2008, Busso's team described a new corpus named the interactive emotional dyadic motion capture database (IEMOCAP) which contains approximately 12 hours of multimodal data to facilitate the investigations of understanding expressive human communication . In totaIn 2016, Zadeh's team introduced the first opinion-level annotated corpus of sentiment and subjectivity analysis in online videos called Multimodal Opinionlevel Sentiment Intensity dataset (MOSI) . The senIn 2018, Bagher Zadeh's team introduced CMU Multimodal Opinion Sentiment and Emotion Intensity (CMU-MOSEI), the largest dataset of sentiment analysis and emotion recognition at that time . The datFriends. This dataset is a multimodal dataset encompassing audio, visual, and textual modalities, which contains about 13,000 utterances from 1,433 dialogues. Each utterance in the snippet of conversation is annotated with one of seven emotional labels, including anger, disgust, sadness, happiness, neutral, surprise, and fear. At the same time, each utterance is annotated with one of the three sentimental labels, including positive, negative, and neutral.In 2018, Soujanya's team proposed the Multimodal EmotionLines Dataset (MELD) to solve the gap that there is no large-scale multimodal multiparty emotional conversational database containing more than two speakers . The MELIn 2020, Yu's team proposed the Chinese single and multimodal sentiment analysis dataset (CH-SIMS) which is a fine-grained annotated Chinese multimodal emotion analysis dataset . CH-SIMSIn 2021, Tang's team proposed a multimodal sentiment analysis dataset named baiDu Video Sentiment dataset (DuVideoSenti), which consists of 5,630 videos displayed on Baidu . In thisIn 2022, Liang's team proposed a Multimodal Sentiment Chat Translation Dataset (MSCTD) containing 142,871 English-Chinese utterance pairs in 14,762 bilingual dialogues and 30,370 English-German utterance pairs in 3,079 bilingual dialogues . Each utIn this section, we introduce a procedure for constructing multimodal corpus based on multiparty dialogues collected by IoT devices to provide an idea and method for researchers to construct multimodal corpus from multiple perspectives.The picture quality of the video should be as clear as possible.The characters in the whole video should be as few as possible, and especially when the speaker speaks, the background characters in a video fragment should be as few as possible.In a video fragment, when the speaker speaks, noise such as background music should be avoided as much as possible.A fundamental requirement of video fragments for constructing multimodal corpus is that the speaker's face and voice must appear in the same video fragment at the same time and it can remain for a certain period of time. In order to get the video fragments containing multiparty dialogues as raw data sources for our multimodal corpus construction as close to life as possible, we can use IoT devices to collect dialogue fragments from daily life or situation comedies as video fragments we need. At the same time, in order to effectively obtain the corresponding video fragments from the multiparty dialogues collected by IoT devices, there are also specific requirements for the collected target fragments:The corresponding video fragments obtained from the dialogue fragments collected by IoT devices that meet the above requirements are conducive to the annotators to determine the sentiment and emotion of the speaker appearing in the video, so as to improve the accuracy of annotation and the accuracy of the extracted features for all modalities including text, audio, and vision. In the procedure of corpus construction, in addition to ensuring the quality of video fragments to be annotated, the annotation scheme is also an indispensable part. As a result, it is necessary to develop an annotation scheme to ensure the smooth construction of multimodal corpus to meet the quality requirement of multimodal corpus and facilitate annotators to annotate.Only one speaker is allowed to speak in the same video fragment to be annotated and the emotion will not change greatly as appropriate during the speech.The video fragment to be annotated should not be too short or too long by the same speaker.The short sentences of the same speaker with the same emotion should be combined as appropriate, and the longer sentences should be properly segmented according to the principle of semantic integrity and consistency principle.The video fragment to be annotated must meet the requirement that the people appearing on the screen must include the speaker.The annotation unit of corpus is a speech of a speaker in a dialogue. The principle of consistency should be followed when annotating each video fragment:If the video fragment does not conform to the above principle of consistency, the video fragment will be filtered immediately. In short, the combination and segmentation of annotation units should follow the principle of not combining the speeches of different speakers or scenarios, so that it is convenient for the annotators to annotate.The annotation template designed in this paper includes the information of season, episode, dialogue, utterance number, speaker, utterance, emotion, and sentiment. If it is a video fragment obtained from the dialogue fragments collected by IoT devices from daily life, the information of season and episode may not be required. If it is a video fragment obtained from the dialogue fragments collected by IoT devices from situation comedies, the information of season indicates the season which a video fragment belongs to and the information of episode indicates the episode which a video fragment belongs to. The information of dialogue indicates the scene which a video fragment belongs to. The information of utterance number indicates the position of a video fragment in one dialogue. The speaker indicates the person who is talking in a video fragment. The information of utterance indicates the content text described by the current speaker. The information of emotion represents the external emotion of the person who is talking in a video fragment. The information of sentiment represents the internal feeling of the person who is talking in a video fragment, which needs to be judged by the context of the dialogue.Sentimental information and emotional information are the focus of the whole annotation scheme. The division of sentimental categories and emotional categories is the cornerstone for the construction of the whole corpus. The standard of classification is to take into account the coverage of sentimental categories and emotional categories in the whole video. In order to reasonably organize the classification of sentiment and the classification of emotion, this paper refers to several multimodal corpora and summarizes the methods of their sentimental classification and emotional classification listed in It can be seen from Considering the above factors and referring to the six basic emotion types proposed by Ekman , this paIn real life, people do not necessarily show the corresponding emotions when expressing their internal feelings. Sometimes emotions conflict with people's internal feelings. At this time, it needs to be judged in many aspects to determine the character's real feelings. Therefore, when annotating sentimental information, it needs logical reasoning combined with the dialogue-context to accurately annotate the speaker's sentimental information. The annotation of emotional information only needs to be based on the external emotional expression presented by the speaker.Multiparty dialogues collected by IoT devices can be uploaded to MEC servers through network transmission to make full use of the amount of idle storage space distributed at the edge of the network. The procedure of data preprocessing is to use the video editing tool Adobe Premiere Pro on MEC servers to cut the target fragments at the frame level according to the consistency principle specified in the annotation unit section, which will be very time-consuming but accurate enough to obtain the video fragments that meet the requirements of multimodal corpus construction. If the video fragments collected by IoT devices are from daily life, the edited video fragment should be classified according to the scene to which the video fragment belongs. If the video fragments collected by IoT devices are from situation comedies, the edited video fragment should be classified according to the season attached, the episode attached, and the scene to which the video fragment belongs.Annotation specification includes two parts: annotation principle and annotation process, which are used to control the whole procedure of multimodal corpus construction.When annotating sentiments and emotions, the annotated sentiments and emotions are the sentiments and emotions of the characters speaking in a video fragment, not the sentiments and emotions of the annotator watching this video fragment. At the same time, in a scene, the speaker's sentiment is easily affected by other characters in the scene, and the speaker's sentiment usually has a certain continuity in a scene. The speaker's sentiment in the preceding utterance and the sentiment in the latter utterance are likely to be the same or similar. Therefore, when annotating the sentiment of each speaker, the sentiment of the speaker should not be annotated according to the facial expression and the intonation of voice of the speaker but should be comprehensively judged according to the dialogue-context.Group the preprocessed data according to the scene and then give each group of data to two persons, respectively, who annotate each group of data on the MEC servers according to the information contained in the annotation template. If the preprocessed data are collected by IoT devices from daily life, the information that should be included in the annotation template is dialogue, utterance number, speaker, utterance, emotion, and sentiment. If the preprocessed data are collected by IoT devices from situation comedies, the information that should be included in the annotation template is season, episode, dialogue, utterance number, speaker, utterance, emotion, and sentiment. The part with inconsistent sentimental and emotional information in the annotated content is handed over to the third person for judgment and decision. The process of annotation is shown in The consistency of annotation is the key index to evaluate the construction of corpus. We can evaluate the quality of corpus by comparing the consistency of sentimental and emotional annotation between two annotators.For our deep learning model, the overall deployment framework is shown in We run our sentimental analysis model (SAM) and other strong algorithm models on a public dataset named IEMOCAP. According to the comparison results shown in (1) Textual Feature. Because the structure of the previous pretraining model is limited by the unidirectional language model (left-to-right language model pretraining or right-to-left language model pretraining), it also limits the representation ability of the model, so that it can only obtain unidirectional context information. BERT uses MLM for pretraining and uses deep bidirectional transformer components to build the whole model, so it finally generates deep bidirectional language representation that can integrate the left and the right context information, which is the reason why we use pretraining language model BERT to extract textual features [features . Firstly(2) Audio Feature. OpenSMILE which is widely applied in automatic sentiment recognition in affective computing is an open-source toolkit for audio feature extraction and classification of speech and music signals, which is the reason why we use OpenSMILE to extract audio features. Firstly, we used the OpenSMILE tookit to obtain 384 dimensional sentiment features of audio, including prosodic feature and spectral feature, and then the audio features are normalized by the standard normalization (Z-score) method. The dimension of audio features is reduced by full connection to obtain 300-dimensional sentiment features of audio.(3) Visual Feature. CNN with 3D convolutional kernels, which outperforms 2D CNNs through the use of large-scale video datasets, is intuitively effective because such 3D convolution can be used to directly extract spatiotemporal features from raw videos [w videos . FirstlyDialogueRNN is a neural network that keeps track of the individual party states throughout the conversation and uses this information for sentimental classification, which is capable of handling multiparty conversation . The DiaAfter extracting the vectors of textual features, audio features, and visual features, we can splice vectors of two or three modes together to obtain the multimodal feature vectors of the current utterance on MEC server. The multimodal feature vectors are used as the input data of the sentiment encoder to obtain the representation of the sentimental feature integrating the context features. Finally, the output sentimental features are directly used as the input data of the full connection layer + softmax layer (sentiment classifier) to obtain the sentimental label of the current utterance.For the tens of thousands of dialogue fragments collected by IoT devices such as IP cameras from daily life, which can collect video and audio information at the same time, process the collected video and audio information to a certain extent, and transfer video and audio information to MEC servers over network, we need to select the dialogue fragments according to the specific requirements of the collected target fragments introduced in Section 3.1 to pick out the dialogue fragments that can be used to construct the multimodal corpus, which may take a lot of time and effort. However, we need to recognize the reality that although IoT devices can collect tens of thousands of dialogue fragments, most of these dialogue fragments can only ensure clear image quality but cannot ensure that there are as few characters as possible in the dialogue fragments and also cannot ensure that noise such as background music can be avoided as much as possible when the speaker speaks. These situations may lead us to pick out fewer useful fragments from the collected dialogue fragments that can be used to build a multimodal corpus. Even if these situations exist, the number of dialogue fragments collected by IoT devices that can be used to construct the multimodal corpus far exceeds the number of dialogue fragments collected by other means. At the same time, we can also use IoT devices to selectively collect the dialogue fragments we need from situation comedies, so that the collected dialogue fragments can have clear picture quality, and can ensure that there are fewer characters and less background noise in the dialogue than those directly collected from daily life.Biography of the Naive WuLin, which premiered in 2019, as the data source to construct the multimodal corpus. Compared with traditional Chinese situation comedies, this situation comedy has clearer picture quality, more obvious emotional characteristics, and less background noise, and few other characters speak at the same time when one character speaks. According to the information specified in the annotation template, some data of the constructed corpus are shown in Biography of the Naive WuLin are mainly Xiangyu Tong, Zhantang Bai, Furong Guo, Xiucai Lv, Dazui Li, Constable Xing, and Xiaobei Mo. Other supporting roles account for a small proportion.Since it takes too much time and energy to collect dialogue fragments for constructing the multimodal corpus using IoT devices from daily life, we can also collect dialogue fragments for constructing the multimodal corpus through IoT devices from situation comedies. Most situation comedies start with creating opposites and contradictions and end with solving contradictions and reaching reconciliation. Following the procedure of constructing a corpus introduced in This constructed multimodal corpus contains 5541 utterances, 330 dialogues, and 25 speakers. Figures Due to the limitation of space, this paper uses the constructed corpus to train the deep learning model for sentiment and analyzes the experimental results.Biography of the Naive WuLin, the speakers do not use Mandarin when speaking but use dialects from all over China. This is what we neglect when constructing the corpus. Due to the particularity of dialect pronunciation, there will be a certain conflict between the features of audio mode and text mode. Through the above experimental results, we should note that when collecting multiparty dialogues by IoT devices for constructing multimodal corpus, we should choose the multiparty dialogues in which the speaker speaks with standard accent.The above prediction results show that the accuracy of prediction results will decline after the features of audio mode and text mode are fused, which reflects that the features of audio mode and text mode have a certain conflict. Through the analysis, we find out the reasons for the above results: in the dialogue fragments collected by IoT devices from situation comedy Our sentiment analysis model can be applied to the surveillance systems and can improve the effect of surveillance systems. The types of the surveillance system include but are not limited to empty nesters companion system and security system based on sentiment analysis. The surveillance system uses the camera and other IoT devices to obtain the video in real time and transmits the video to MEC servers. The servers analyze the sentiments of the characters in the video and take corresponding actions according to the analysis results.The system can collect and obtain the sentiments of empty nesters through IoT devices such as camera equipment, sensors, and artificial intelligence technologies such as our sentiment analysis model, extract and classify the sentimental features, and transmit it to MEC servers for sentimental analysis. Then, computers give feedback according to the analysis results. The feedback forms include but are not limited to voice, image, or action. The system can use robots as the carrier to make empty nesters interact well with the system, reduce their loneliness, and increase their happiness in daily life.In stations and airports, the security system based on sentiment analysis can collect the sentimental information of every tourist who passes through the security gate in real time. The system can automatically check out the people with high possibility of crime by analyzing his sentiment in a short period of time, so as to prevent criminal violations.In this paper, we propose a procedure of constructing a multimodal corpus for multiparty dialogues collected by IoT devices. We construct a multimodal corpus on MEC servers according to the procedure using the multiparty dialogues collected by IoT devices. At the same time, we build a sentiment analysis model and train the model for sentiment on MEC server using the constructed multimodal corpus. According to the experimental results, we find that when collecting the multiparty dialogues by IoT devices used to construct the multimodal corpus, the speakers in the collected multiparty dialogues should preferably use the standard accent when speaking, which can improve the effectiveness of the constructed multimodal corpus. In future, we will try to use IoT devices to collect multiparty dialogue from daily life to build a multimodal corpus and continue to improve the details of the sentiment analysis model.


The purpose of this study was to identify the career paths of transnational migrating female elite handball players. Fourteen Slovenian and Suisse national team players were monitored over a 7-year period by means of semi-structured interviews and official handball records. At the end of the examination period, six still-active players were interviewed again. Qualitative thematic analysis was employed to develop a contextualized understanding of participants’ careers paths and life trajectories in relation to their athletic migration and dual career. In relation to the limited opportunities offered by small countries with middle-ranking national handball teams, participants highlighted that sport migration coupled with dual career opportunities represented a strategic decision for a successful career development through several key factors: (1) a clear intention towards a professional handball career; (2) the actual fulfilment of professional handball career aspirations; (3) dual career goals as part of the migration process; (4) high personal ambition and emotional connection to handball; (5) the implementation of a successful dual career path; (6) a positive migration experience; and (7) feeling supported and valued during relocation. Sport federations and elite clubs should consider the implementation of a multidimensional approach encompassing dual career paths to facilitate athletes’ transnational relocation and career transitions. Globalization is a process encompassing the causes, the course, and the consequences of transnational and transcultural integration, consolidating the world into a whole space for individual progress in many sectors of the society at large, including sport ,2,3. In In recent decades, a growing number of athletes and sports professionals engaged in transnational sport migration and/or relocation within their native country to foster their athletic development, to expand their professional networks, and/or to strengthen their dual career paths  ,4,5,6,7.A sports career is a dynamic, multidimensional, multilevel, and multifactorial process, in which the athletes’ efforts, dual career obligations, and socio-cultural and life aspects affect the transition from youth talent to the mastery elite level, and post-athletic career retirement ,14,15,16According to the literature ,3,29,30,Research on athletic labor migration has investigated athletes’ motivations and reasons for sport migration ,40,41,42In general, a sport career might span over 15 years from the talent development to the elite senior levels; sport migration might occur at a different career stage and/or athlete’s age, with specific national and sport-specific aspects playing a modulating role . FurtherIn athletic migration, one important modulating factor concerns the gender of the athletes ,52. In rIn handball, differences in cross-national relevance of this team sport may influence the career trajectories of sportspersons . PlayersFor the present study, a 7-year (from 2012 to 2019) longitudinal qualitative approach was applied to investigate migration experiences of elite female handball players members of the Slovenian (SLO) and Switzerland (SUI) National teams, which held a middle-rank European position during the examination period . In particular, the following inclusion criteria have been adopted for both the cross-sectional analysis at the beginning of the study and the longitudinal analysis: (i) being an elite athlete and active member of the handball national team in the native country; (ii) being a sport migrant; and (iii) being enrolled in a dual career path at the beginning of the experimental period. Thus, quitting the sport career, and/or lowering the competition level, and/or losing the “sport migrant” status during the experimental period were considered as exclusion criteria for the longitudinal analysis.Qualitative thematic analysis has been applied to develop a contextualized understanding of the career and life trajectories of female handball players during their migration experience, including the management of their dual career. In this framework, the present study intended to integrate and expand previous research findings regarding cross-national mobility in elite athletes ,3,5,9 wiAccording to the literature ,57, semin = 8, aged 23.2 ± 6.5 years) and SUI  national teams presenting the “elite migrating dual career athlete” status volunteered for the present study. The sample represented the most successful female handball national team players in both countries, having played more than 50 national team matches.Fourteen female handball players from SLO  was for the recruitment of the SLO and SUI women handball athletes during a national team preparation camp, based on inclusion criteria. Athletes were informed about the aim and procedures of the study, the confidential nature of the data collection, and the possibility to drop the research at any time with no explanation. To voluntarily enroll in the study, all the players provided their written informed consent and general demographic information. Thus, data were coded to guarantee the anonymity of the participants.The second phase (in 2012) was for the administration of the first semi-structured interviews (“Interview 1”) to the research sample. At this research stage, an emphasis was placed on the athletes’ perceptions regarding their current sport and academic status, and the reasons for sport migration. Interviews were arranged at a time and in a place convenient to the athletes and conducted in-person by a research team member.The third phase (from 2012 to 2019) consisted of a 7-year monitoring period of the athletes’ career development, characteristics of their migration process , sport-specific information , and dual career paths. Contextual data were collected both through individual contacts with the involved players, and from the SLO and SUI National and European Handball Federation on-line platforms.The fourth phase (in 2019) consisted of a second semi-structured interview (“Interview 2”) administered only to the participants still presenting the “elite handball migrating athlete” status. Conversely, athletes not meeting the inclusion criteria have been excluded from this research stage. To check the quality of the collected responses at the Interview 1, to verify the accuracy of the information retrieved in the monitoring phase , and to stimulate further reflection on major career events occurred during their migration experience, “Interview 2” started with athletes cross checking the previous research material. In this phase, an emphasis was given to the shifting discourses regarding athletes’ insights and personal evaluation regarding their career and life journeys, as a result of their migration choices. Interviews were conducted both face-to-face and online during the season 2019/2020.The longitudinal research design of the present study was characterized by a four-phase data collection:The interview duration ranged from 50 to 105 min for each athlete. By considering the different nationalities of the participants in the present study, in order to allow athletes to freely express themselves and to encourage them to provide comprehensive perceptions regarding their career development and migration features, the semi-structured interviews were conducted in their native language . To refine the accuracy and quality of the collected athletes’ responses, interviews have been recorded and transcribed. Subsequently, the final text of each interview was translated into English and reviewed for language correctness by a native speaker  before data processing and analysis.To identify major participants’ career development patterns, Regarding the domestic relocation prior to transnational migration, with respect to SLO athletes SUI players tended to have a more static national sport career  due to the lack of perceived opportunities and prospective athletic growth resulting from relocation within the national handball context. In fact, domestic mobility was limited by the general amateur organization of SUI sport clubs, which was perceived as lacking potential opportunities for handball career progression. Conversely, national athletic relocation emerged as a common practice in Slovenia, where athletes tend to play for different clubs to ameliorate their athletic status. Finally, both SUI and SLO players reported 2–8 years of national senior elite experience before engaging in transnational athletic migration, which was deemed a necessary step for further career development. In fact, amateur and semi-professional athletes decided to migrate to pursue a professional sport career, with SLO athletes presenting a longer international experience at the beginning of this study with respect to their SUI counterparts.The first interview in 2012 highlighted a lack of opportunities for a handball career development in the native country as the major reason for sports migration, which was perceived as a strategic choice to attain better sport conditions , dual career opportunities, and to increase competencies and life skills to prepare for post-athletic career retirement . Family and peers were perceived as influencing both the athletes’ sport and personal development in their home country and their decision to migrate. In particular, transnational mobility was perceived as one of the most important stages in the athletes’ sport career development. Furthermore, relocation was associated with prospective athletic success, and improved quality of life and financial condition. Whilst sport migration represented the first opportunity for SUI athletes to be paid for playing handball, increased salary opportunities became a contributing and relevant factor for the migration decision for SLO players. In fact, SUI athletes valued the potential improvement of their handball skills during migration, which could contribute to ameliorate their engagement with the national team. Conversely, a perceived prospective enhancement of the social status emerged as a crucial factor for the transnational migration of SLO athletes. Additionally, access to dual career opportunities during relocation was reported a migration pre-requisite for the majority of the athletes.In particular, the players highlighted:“My parents recognized very soon that I was more motivated for school when I was also doing well at handball. Although they had different plans for my future (a career in business), they supported me during my handball career”.(SUI player)“My mother was repeating to me, ‘You should go abroad. There everything is better than here: clubs are more structured and better organized, and salaries are better. If you invest so much time in all the stages of your sport career, why not getting economic benefits from handball? In addition, you will have better opportunities abroad. I would like to have you at home, but I wish you a better life; better than I have’”.(SLO player)“What really mattered for me and my parents was to be recognized in prominent foreign handball clubs; and, even more, to find a job abroad. The career goals were included in my sport and life plans from the beginning, being clear that I would migrate one day to change my life prospects”.(SLO player)“I was thinking about leaving the previous club in my home country for a while. I felt that my home club was not the right environment, at the same time I was not happy at home. My father was putting additional pressure on me with his permanent presence in my handball and in my life in general. I simply wanted to move”.(SLO player)“For me a key point was to migrate. My position in the family and my social status had turned drastically after migration. When I was playing at home, for my family I was “just another female handball player”; after I migrated, my social status was much higher—I was “someone”, the successful person, the family member to be proud of”.(SLO player)Regarding the organization of the transnational migration, all the players reported that they prepared physically and mentally to cope with relocation challenges. Only three elite athletes with outstanding handball skills were directly contacted by foreign clubs, whereas difficulties in finding a good foreign club emerged for the rest of the players. However, the majority of the athletes stressed that being a national team member played a crucial role in their opportunities to migrate, since they “became visible” at the national team tournaments.n = 10; SUI: n = 3; SLO: n = 7) competed at an elite level throughout the examination period, whereas the remaining 29% athletes  ended their sport career before 2019. Regarding migration, only 43% athletes  showed an “elite sport migrant” status in 2019, which was retained till Interview 2. Conversely, in 2019, five athletes were still active but relocated in their native country. Only 36% of the sample  maintained transnational migration during the 7-year study, whereas intermittent mobility was observed in five players, who experienced a period of relocation to their native country. At the end of the study, only one SUI athlete was still a top-level migrant player, whereas two athletes relocated to Switzerland and three retired at around 30 years of age, transitioning into the labor market and starting their family. Regarding SLO players, in 2019, only two athletes were top professional players participating in the Handball Champions League, and scored among the top players in Europe. Conversely, the other active SLO players moved in national and international semi-professional leagues and only one athlete retired before the end of the study.n = 8; SUI: n = 5; SLO: n = 3), followed by Spain  and France . In particular, migration dynamics was more stable in the SUI sample with respect to the SLO one. In fact, the majority of the SUI athletes (n = 7) mostly played in the German league, probably due to the same native language. Conversely, SLO players presented a higher variety of destinations and reported a total of 20 between-country and 28 between-club sporting transfers.Regarding the countries of migration, Germany was the most frequent destination for athletes Individual coping strategies with multiple challenges derived by an international sporting career have been emphasized as a key factor in determining career transitions outcomes. Having moved abroad, some athletes reported a variety of feelings, ranging from big expectations to substantial doubts regarding their life choices. Some experienced homesickness and wish to return home, especially when the sport and living conditions in the foreign country did not meet their pre-migration expectations. In this framework, perceived social support from parents, peers, teammates, and coaches played a crucial role in athletes’ adaptation to the new socio-cultural environment. Whilst many athletes reported a strong social support from family members during the whole migration period, other declared that their partners were mostly unwilling to adjust their lives to the athletes’ careers. Finally, language barriers affected the life and career management of migrating players who needed to learn a foreign language.“When I decided to move, I was really excited… but being abroad alone wasn’t so much fun in the beginning. I felt loneliness”.(SUI player)“In the beginning, it was very difficult to communicate with the coach or teammates, who were speaking French. Some of them helped me with translation in English, during practicing and playing matches; however, it was hectic with this communication. When I mastered the French language, I felt very happy and this had led to a better communication in handball”.(SLO player)Regarding dual careers, the majority of the athletes enrolled in distance academic courses and graduated during their migration period. In particular, six athletes graduated in sport-related studies: one in social sciences, two in economics, and three became teachers. While abroad, after graduation six SLO athletes reported that they were combining their handball and vocational commitments.Although financial aspects were not considered a key priority for migrating, especially SUI players appreciated the economic benefits deriving from their international athletic mobility.“It is not a lot of money, but I’m happy with that. I’m realistic. I know that I am not a world—class player or a handball star, so it is about what I can get. The experience counts more than [the] money I earn”.(SUI player)n = 1; SLO: n = 5) maintained the eligibility criteria for the longitudinal analysis and were interviewed in 2019. In fact, in 2019 they reported an overall average international experience of around 9 years, having started their international mobility before the beginning of this study. After such a long migration period, in the second interview athletes reflected upon the effects of the whole relocation process on their sport, personal, and vocational development. In general, all players believed that migration had strongly improved their sport career opportunities, being a springboard towards handball professionalization. Furthermore, a consensus emerged in relation to the relevant visibility of being national team players in creating migration opportunities and a direct recruitment from a foreign sport club.As displayed in “At the beginning of my career, I decided I would do everything to succeed. I would not return home as a loser. I wanted to be a winner. Not because of my father but because of myself”.(SLO player)“Wer es nicht probiert, hat schon verloren. [Who hasn’t tried has already lost]”.(SUI player)All participants reported that they considered dual career an essential aspect of their migration choice, being part of their plans from the very beginning of this experience. In particular, all the athletes mentioned that their families demanded them to complete their education while pursuing their international athletic goals. To note, one SLO player declared that her athletic migration experience gave her dual career a special push. Interestingly, the majority of the athletes showed an interest in working in either sports management or some other sport-related business after finishing their handball careers.“Switzerland was not “big enough” for my sport career dreams. In pursuing my goal to play my sport professionally, I wanted also to check how the other European countries were organizing sport in combination with academic studies. I decided to study sport in Denmark, the “heart of women’s handball”. I was ambitious in both sport and in my other career”.(SUI player)“My family was repeating me that ‘It is very nice that you are enjoying handball, but school comes first!’”(SUI player)“When I was at home, I expected my mother to remind me about school. Now I know that I somehow considered my school as my mother’s business, and not mine. When I moved abroad, I finally realized that everything in my life is my responsibility, including my education”.(SLO player)All the participants believed that transnational mobility contributed to their personal growth, offering them the possibility to develop life competencies and skills . Furthermore, the participants mentioned also the benefits deriving from athletic migration for acquiring vocational skills, learning foreign languages, expanding their social networks, and ameliorating their general lifestyle through different sociocultural perspectives.“The biggest lesson was to have the self-confidence to arrive as a Swiss player into a very big handball nation and show them that we are able to play handball as well. A positive mind-set and psychology, combined with self-confidence, were very important in the first three years. In the last two years, I got used to it and I played better and better because I felt secure and confident. I also learnt that without self-confidence I would never have been a good player. I believed in my strength and made my own way. This was a lesson for life”.(SUI player)“Germans are different, so structured and disciplined. Conversely, Slovenians are part of the Balkans, more creative and passionate, and looking for better life prospects”.(SLO player)“I currently work for the Handball Federation. The job is very interesting and also nice for me because I know more or less how everything works from my experience as a player. My time playing in other countries also helped. I speak fluent English and I had chance to gain experience regarding other handball cultures, such as Danish, Slovenian and German. People I work with maybe still know me and accept me as a foreign professional player”.(SUI player)“French (language) would be an important competence in my post-handball career”.(SLO player)All the athletes admitted having experienced some difficulties during the pre-transition and acute cultural adaptation phases. Indeed, SLO players described their first migration as a big, difficult, and stressful step in their careers, but also as the best decision of their life. After having adapted to the new socio-cultural environment, they perceived they had higher sport results and an overall enriched life experience with respect to other not-migrating athletes. Whilst the SLO players reported that their migration experience was meant to build potential future life and occupational prospects in the relocation countries, the SUI player expressed no doubts about returning to Switzerland in the future.“Going abroad was the best decision in my life. I enjoy playing handball, I’ve got a good job and I found love—I got married here”.(SLO player)“I knew from the beginning of my migration experience that my future would be in Switzerland. After my handball career, I intended to return to Switzerland, and I had a clear future plan to return to Switzerland to work. Occupational and opportunities in life are too excellent in Switzerland to stay elsewhere”.(SUI player)Overall, in considering the conceptual categorization of student-athlete migration the thematic analysis identified four main-level constructs : (1) ambConsidering that previous scientific studies on dual career migration mainly focused on male athletes with a final destination in several countries worldwide , the lonIn examining the push factors of dual career migration of SLO and SUI female players, it is relevant to consider that some European countries attract athletes wishing to experience higher sports achievements in countries having a high international role in women’s handball ranking . In the Differently from the literature, no mercenary profile emerged in this study, probably because the financial revenues provided to the female handball players were not sufficient to capitalize for future years ,5,50. DeThe ambitious category could not be considered a separate category when overlapping with other push factors of the athlete’s personal life ,41. In aDespite the fact that players considered migration experience valuable at a personal level, they also reported difficulties in developing a sense of belonging at the beginning of their migration process. In the literature, some athletes complained about the complexity of their cross-cultural experiences, inequality in opportunities, and the difficulty of developing a sense of belonging ,9,27,34.In general, the players considered their careers successful, being satisfied with their migration decision, especially when comparing their careers with those of non-migrating counterparts. At the end of their handball career, the majority of players tended to return to their native country, substantiating the returnee category of migrating athletes ,50. The The present study generated new evidence for more structured and effective career development paths in women’s elite handball. In particular, sport migration from geographically small countries presenting limited sport opportunities could be considered as a key career determinant. In fact, all the participants of this study highlighted the benefits derived from sport relocation for their career success, especially in considering the limited sport opportunities available in their native countries. Furthermore, the development of their life and vocational skills and competencies has been identified as a crucial determinant when considering athletic relocation. In exploring the role of migration in the sport career, the characteristics of the athletic relocation, the athletes’ reasons and/or goals for migration, the dual career strategies, the coping process with career and migration barriers/challenges, and the competence/skill development during the migration process, the present findings could provide some suggestions and recommendations to promote a holistic development for migrant female handball athletes: (1) the possession of excellent handball skills and a clear intention towards building a professional handball career; (2) the actual fulfilment of professional handball career aspirations; (3) the planning of clear dual career goals at the beginning of the migration process; (4) high personal ambition and emotional connection to handball; (5) the implementation of a successful dual career path; (6) a positive migration experience; and (7) feeling supported and valued in the new team and community environments.Thus, the career trajectory of women elite athletes migrating in order to accomplish higher sport goals should encompass multidimensional developmental factors  to promote a holistic development of the athlete as an individual and to facilitate career transitions and post-athletic career adjustments. In this framework, dual career opportunities  are a crucial determinant to provide the athletes with additional relocation benefits and to equip them with necessary skills and competencies to prepare for post-sport retirement. This aspect is important for sportspeople at large, independently from the athletic domain. However, in minor sports and for athletes migrating from countries with limited athletic growth possibilities, the enrichment of their relocation experience  becomes even more important for both their personal and professional growth. Indeed, many former migrant players used their international experience to enroll in the sporting job market, contribute to women’s handball development as managers or team officials within handball national teams/federations, and/or to professionally relocate outside the sport environment, turning into vocational migrants. Therefore, sport federations and elite sport clubs recruiting migrating athletes should be sensitized towards successfully addressing these issues to facilitate the transnational relocation of elite female athletes. In particular, providing athletes with necessary support and opportunities may contribute to both enrich their migrating experience, to increase their sport performances, and to ameliorate their socio-cultural integration. Although some factors might be generalized, it is important to emphasize that each migration story is unique.The limited number of athletes accomplishing the whole duration of the research and the involvement of athletes from two countries could be considered limitations of this study. To further explore career trajectories and choices of migrating female athletes, future studies should envision the involvement of a higher number of participants from different countries, representing a variety of sport disciplines. This approach would help to identify significant and specific socio-cultural and personal characteristics/determinants/predictors to facilitate successful transnational migration and dual career development of elite athletes. Despite the high reputation of the research team members on dual career of sportspersons and international handball, the lack of an external piloting phase including external experts could represent a further limitation of the study.