Investigation of the dependence of joint contact forces on musculotendon parameters using a codified workflow for image-based modelling

The generation of subject-specific musculoskeletal models of the lower limb has become a feasible taskthanks to improvements in medical imaging technology and musculoskeletal modelling software.Nevertheless, clinical use of these models in paediatric applications is still limited for what concernsthe estimation of muscle and joint contact forces. Aiming to improve the current state of the art, amethodology to generate highly personalized subject-specific musculoskeletal models of the lower limbbased on magnetic resonance imaging (MRI) scans was codified as a step-by-step procedure and appliedto data from eight juvenile individuals. The generated musculoskeletal models were used to simulate 107gait trials using stereophotogrammetric and force platform data as input. To ensure completeness of themodelling procedure, muscles’ architecture needs to be estimated. Four methods to estimate muscles’maximum isometric force and two methods to estimate musculotendon parameters (optimal fiber lengthand tendon slack length) were assessed and compared, in order to quantify their influence on the models’output. Reported results represent the first comprehensive subject-specific model-based characterizationof juvenile gait biomechanics, including profiles of joint kinematics and kinetics, muscle forces and jointcontact forces. Our findings suggest that, when musculotendon parameters were linearly scaled from areference model and the muscle force-length-velocity relationship was accounted for in the simulations,realistic knee contact forces could be estimated and these forces were not sensitive the method used tocompute muscle maximum isometric force

Commentary on the Integration of Model Sharing and Reproducibility Analysis to Scholarly Publishing Workflow in Computational Biomechanics

© 1964-2012 IEEE.Objective: The overall goal of this paper is to demonstrate that dissemination of models and analyses for assessing the reproducibility of simulation results can be incorporated in the scientific review process in biomechanics. Methods: As part of a special issue on model sharing and reproducibility in the IEEE Transactions on Biomedical Engineering, two manuscripts on computational biomechanics were submitted: Rajagopal et al., IEEE Trans. Biomed. Eng., 2016 and Schmitz and Piovesan, IEEE Trans. Biomed. Eng., 2016. Models used in these studies were shared with the scientific reviewers and the public. In addition to the standard review of the manuscripts, the reviewers downloaded the models and performed simulations that reproduced results reported in the studies. Results: There was general agreement between simulation results of the authors and those of the reviewers. Discrepancies were resolved during the necessary revisions. The manuscripts and instructions for download and simulation were updated in response to the reviewers' feedback; changes that may otherwise have been missed if explicit model sharing and simulation reproducibility analysis was not conducted in the review process. Increased burden on the authors and the reviewers, to facilitate model sharing and to repeat simulations, were noted. Conclusion: When the authors of computational biomechanics studies provide access to models and data, the scientific reviewers can download and thoroughly explore the model, perform simulations, and evaluate simulation reproducibility beyond the traditional manuscript-only review process. Significance: Model sharing and reproducibility analysis in scholarly publishing will result in a more rigorous review process, which will enhance the quality of modeling and simulation studies and inform future users of computational models

Reference standardization and triglyceride interference of a new homogeneous HDL-cholesterol assay compared with a former chemical precipitation assay

A homogeneous HDL-c assay (HDL-H), which uses polyethylene glycol-modified enzymes and sulfated alpha-cyclodextrin, was assessed for precision, accuracy, and cholesterol and triglyceride interference. In addition, its analytical performance was compared with that of a phosphotungstic acid (PTA)/MgCl2 precipitation method (HDL-P). Within-run CVs were < or = 1.87%; total CVs were < or = 3.08%. Accuracy was evaluated in fresh normotriglyceridemic sera using the Designated Comparison Method (HDL-H = 1.037 Designated Comparison Method + 4 mg/L; n = 63) and in moderately hypertriglyceridemic sera by using the Reference Method (HDL-H = 1.068 Reference Method - 17 mg/L; n = 41). Mean biases were 4.5% and 2.2%, respectively. In hypertriglyceridemic sera (n = 85), HDL-H concentrations were increasingly positively biased with increasing triglyceride concentrations. The method comparison between HDL-H and HDL-P yielded the following equation: HDL-H = 1.037 HDL-P + 15 mg/L; n = 478. We conclude that HDL-H amply meets the 1998 NCEP recommendations for total error; its precision is superior compared with that of HDL-P, and its average bias remains below +/-5% as long as triglyceride concentrations are < or = 10 g/L and in case of moderate hypercholesterolemia

Generative deep learning applied to biomechanics: creating an infinite number of realistic walking data for modelling and data augmentation purposes

Our work using generative deep learning models to generate synthetic human movement data to augment existing datasets was presented at the 9th World Congress of Biomechanics

Evaluation of an Online Course Promoting Health and Wellbeing for University Students and Employees.

Published studies dealing with health promotion activities, such as the improvement of physical activity and healthy eating, for workers and students prove the effectiveness of these preventive interventions. The consequent benefits include better prevention of cardiovascular risk and an improvement in quality of life. Considering this, an intervention aimed at promoting healthy eating and non-sedentary lifestyles has been implemented within an Italian university: the aim of the present research is to evaluate its effectiveness. The intervention consisted of a targeted asynchronous e-learning two-hour course on healthy eating and non-sedentary lifestyles. The attendants were 2004 university students and employees. We conducted two surveys before and after the training intervention, and, through the responses obtained, we evaluated the effectiveness of the intervention. We applied different statistical methods, including unpaired t-tests and nonparametric tests, principal components and cluster analysis. Our results indicate that the post-training knowledge has been significantly improved, compared to that pre-training (7.3 vs. 8.7, p &lt; 0.001). Moreover, the whole sample showed an improved awareness of the importance of healthy behaviors, and perception of the University as an institution promoting a healthy lifestyle. Through the principal components analysis, we identified a unidimensional latent factor named “health and behaviors”. The cluster analysis highlighted that the sub-group reporting the lowest scores at the survey before the training was the one with the highest improvement after the intervention. To the best of our knowledge, this is the first Italian study testing, before and after a health promotion intervention, the knowledge and the attitudes and behaviors towards healthy lifestyles of a group of students and workers. Moreover, we also evaluated the pre- and post-intervention perceived health status, as well as the level of engagement of the attendants, with respect to their colleagues and management in an educational institution promoting wellbeing. The conclusions of our study support the need for further adoption of health promotion training interventions, similar to the one we performed, in order to improve healthy eating and non-sedentary behaviors among workers and students

Generative adversarial networks to create synthetic motion capture datasets including subject and gait characteristics

\ua9 2024 The AuthorsResource-intensive motion capture (mocap) systems challenge predictive deep learning applications, requiring large and diverse datasets. We tackled this by modifying generative adversarial networks (GANs) into conditional GANs (cGANs) that can generate diverse mocap data, including 15 marker trajectories, lower limb joint angles, and 3D ground reaction forces (GRFs), based on specified subject and gait characteristics. The cGAN comprised 1) an encoder compressing mocap data to a latent vector, 2) a decoder reconstructing the mocap data from the latent vector with specific conditions and 3) a discriminator distinguishing random vectors with conditions from encoded latent vectors with conditions. Single-conditional models were trained separately for age, sex, leg length, mass, and walking speed, while an additional model (Multi-cGAN) combined all conditions simultaneously to generate synthetic data. All models closely replicated the training dataset (&lt;8.1 % of the gait cycle different between experimental and synthetic kinematics and GRFs), while a subset with narrow condition ranges was best replicated by the Multi-cGAN, producing similar kinematics (&lt;1\ub0) and GRFs (&lt;0.02 body-weight) averaged by walking speeds. Multi-cGAN also generated synthetic datasets and results for three previous studies using reported mean and standard deviation of subject and gait characteristics. Additionally, unseen test data was best predicted by the walking speed-conditional, showcasing synthetic data diversity. The same model also matched the dynamical consistency of the experimental data (32 % average difference throughout the gait cycle), meaning that transforming the gait cycle data to the original time domain yielded accurate derivative calculations. Importantly, synthetic data poses no privacy concerns, potentially facilitating data sharing

Sun protection habits and behaviors of a group of outdoor workers and students from the agricultural and construction sectors in north-Italy

Background: Despite the relevant frequency of ultraviolet induced adverse health effects in workers, solar ultraviolet radiation (UVR) exposure is an occupational risk not adequately minimized in Italy. Objective: To assess the characteristics and prevalence of sun exposure habits and behaviors in a group of students and outdoor workers (OW) from the agricultural and construction sectors of a north-Italian region. Methods: Based on a previously developed standardized questionnaire, we collected full information on individual sun exposure habits at work and during leisure activities. Results: In 2018, 380 high school students and OW from the agricultural and construction sectors participated in a sun-safety campaign. More than a third (39.0%) of OW reported never using sunglasses, 52.8% never applied sunscreens at work, and a quarter never wear a UV protective hat. Considering leisure-time, students reported more frequent sunburns compared to OW: 25.0% vs. 13.8%; half (51.6%) of students and a third (36.4%) of OW reported never wearing a UV protective hat. A third (30.1%) of students and 37.2% of OW never or only seldom applied sunscreens on holidays. Discussion: The majority of OW in our study reported poor protective solar exposure habits. Young students of the construction and agricultural sectors indicated even worse sun-protective behaviors, both during apprenticeship and leisure activities. Our study highlights the low health literacy related to solar UVR in OW and apprentices. Further educational initiatives are required in Italy to improve the adoption of protective behaviors during outdoor activities

History of occupational accidents and near misses and sleepiness in Italian professional drivers: a cross-sectional study

Background: Sleep difficulties among professional drivers are a major concern for health and safety as they can be associated with increased tiredness while driving and can be related to an increased risk of accidents. Several lifestyle-related risk factors can have an important impact on sleep. This study aims to investigate whether a history of work accidents or near misses is associated with abnormal sleepiness among a sample of Italian professional drivers, considering individual and occupational factors that may influence this relationship. Methods: From 2018 to 2022, we conducted a cross-sectional study recruiting professional drivers attending mandatory health and safety training courses in accordance with Italian legislation. Participants completed a six-section questionnaire including personal information, sleep-related difficulties, occupational data, habits, history of accidents and near misses, and the Epworth Sleepiness Scale (ESS). We used multiple logistic regression models to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for abnormal sleepiness. Results: The sample comprised 884 workers, predominantly male (99%), with mean age 49.4 years. Our study showed associations between several risk factors and excessive sleepiness. Consuming alcohol showed an increased probability of higher ESS scores. Similarly, snoring and having a history of occupational accidents or near misses showed increased probability of abnormal sleepiness. Conclusion: This study suggests a potential association between a history of near misses and abnormal sleepiness among professional drivers. The observed relationship underscores the need to address underlying sleep disorders, such as undiagnosed sleep apnea, which may contribute to excessive sleepiness and compromised safety. Drivers with a history of work accidents or near misses should be considered for screening programs targeting abnormal sleepiness, as these events may serve as early warning signs. Educational interventions to raise awareness and promote better sleep hygiene among this at-risk group could play a crucial role in improving both occupational health and road safety. Despite limitations inherent to self-reported data, our findings offer valuable insights for targeted prevention strategies

Diagnostic nerve block in prediction of outcome of botulinum toxin treatment for spastic equinovarus foot after stroke: A retrospective observational study

Objective: To evaluate the role of diagnostic nerve block in predicting the outcome of subsequent botulinum toxin type A treatment for spastic equinovarus foot due to chronic stroke. Design: Retrospective observational study. Patients: Fifty chronic stroke patients with spastic equinovarus foot. Methods: Each patient was given diagnostic tibial nerve block (lidocaine 2% perineural injection) assessment followed by botulinum toxin type A inoculation into the same muscles as had been targeted by the nerve block. All patients were evaluated before diagnostic nerve block, after the nerve block, and 4 weeks after botulinum toxin injection. Outcomes were ankle dorsiflexion passive range of motion of the affected side, and calf muscle spasticity, measured with the modified Ashworth scale and the Tardieu Scale. Results: Significant improvements were measured after diagnostic nerve block and botulinum toxin injection compared with the baseline condition. Diagnostic nerve block led to significantly greater improvements in all outcomes than botulinum toxin injection. Conclusion: This study confirmed diagnostic nerve block as a valuable screening tool in deciding whether to treat spastic equinovarus with botulinum toxin. However, the results support the evidence that diagnostic nerve block results in a greater reduction in muscle overactivity than does botulinum toxin type A in patients with spastic equinovarus due to stroke

Psychological treatments and psychotherapies in the neurorehabilitation of pain. Evidences and recommendations from the italian consensus conference on pain in neurorehabilitation

BACKGROUND: It is increasingly recognized that treating pain is crucial for effective care within neurological rehabilitation in the setting of the neurological rehabilitation. The Italian Consensus Conference on Pain in Neurorehabilitation was constituted with the purpose identifying best practices for us in this context. Along with drug therapies and physical interventions, psychological treatments have been proven to be some of the most valuable tools that can be used within a multidisciplinary approach for fostering a reduction in pain intensity. However, there is a need to elucidate what forms of psychotherapy could be effectively matched with the specific pathologies that are typically addressed by neurorehabilitation teams. OBJECTIVES: To extensively assess the available evidence which supports the use of psychological therapies for pain reduction in neurological diseases. METHODS: A systematic review of the studies evaluating the effect of psychotherapies on pain intensity in neurological disorders was performed through an electronic search using PUBMED, EMBASE, and the Cochrane Database of Systematic Reviews. Based on the level of evidence of the included studies, recommendations were outlined separately for the different conditions. RESULTS: The literature search yielded 2352 results and the final database included 400 articles. The overall strength of the recommendations was medium/low. The different forms of psychological interventions, including Cognitive-Behavioral Therapy, cognitive or behavioral techniques, Mindfulness, hypnosis, Acceptance and Commitment Therapy (ACT), Brief Interpersonal Therapy, virtual reality interventions, various forms of biofeedback and mirror therapy were found to be effective for pain reduction in pathologies such as musculoskeletal pain, fibromyalgia, Complex Regional Pain Syndrome, Central Post-Stroke pain, Phantom Limb Pain, pain secondary to Spinal Cord Injury, multiple sclerosis and other debilitating syndromes, diabetic neuropathy, Medically Unexplained Symptoms, migraine and headache. CONCLUSIONS: Psychological interventions and psychotherapies are safe and effective treatments that can be used within an integrated approach for patients undergoing neurological rehabilitation for pain. The different interventions can be specifically selected depending on the disease being treated. A table of evidence and recommendations from the Italian Consensus Conference on Pain in Neurorehabilitation is also provided in the final part of the pape