Physical Tasks Research Articles

Adverse Childhood Experiences and Chronic Low Back Pain in Adulthood: The Role of Emotion Regulation

Chronic low back pain (cLBP) is characterized by biopsychosocial determinants that collectively result in a substantial burden at the individual, community, and health care system levels. A growing body of literature suggests that childhood adversity is longitudinally associated with the development and maintenance of various chronic pain conditions in adulthood. Little research has investigated the psychological processes that might underlie the association between adverse childhood experiences (ACEs) and cLBP. Emotion regulation comprises a substantive part of the subjective experience of pain and may be a potential mechanism through which ACEs contribute to cLBP etiology and maintenance. Thus, the current study examined the extent to which emotion dysregulation mediated the relationship between ACEs and pain severity (pain at rest and movement-evoked pain) in adults with cLBP. Participants included 183 adults (53.0% female, 62.5% non-Hispanic Black) between the ages of 18 and 85 with cLBP. Participants self-reported on ACEs, pain, difficulties in emotion regulation (DER), depression, and completed brief physical function tasks. In data analytic models, sociodemographic variables were included as covariates. Analyses revealed that emotion regulation mediated the relationship between ACEs and cLBP severity at rest (indirect effect = .15 [95% CI {.06–.25}]) and with movement (indirect effect = 1.50 [95% CI {.69–2.57}]). Findings suggest ACEs are linked to cLBP severity in adulthood through DER. This aligns with research demonstrating that childhood maltreatment can lead to DER, which perpetuate over the lifespan to impact adult health outcomes. PerspectiveThis study presents emotion dysregulation as a psychological pathway through which childhood adversity may contribute to cLBP in adulthood. This work may bolster our understanding of social experiences as risk factors for chronic pain, while identifying targets for clinical intervention. Trial RegistrationThis study utilized baseline data collected as part of a parent trial titled “Examining Racial and SocioEconomic Disparities in Chronic Low Back Pain” (ClinicalTrials.gov ID: NCT03338192).

Passive Model-Predictive Impedance Control for Safe Physical Human–Robot Interaction

Various cognitive systems have been designed to model the position and stiffness profiles of human behavior and then to drive robots by mimicking the human’s behavior to accomplish physical human-robot interaction tasks through a properly designed impedance controller. However, some studies have shown that variable stiffness parameters of the impedance controller can cause the violation of the passivity constraint of the robot states, and make the robot’s stored energy exceed the external energy injected from the human user, thus leading to the unsafe human-robot interaction. To solve this problem, this paper proposes a novel passive model predictive impedance control method including two control loops. In the bottom-loop of the proposed controller, the robot is driven by a variable impedance controller to achieve the desired compliant interaction behavior. In the top-loop of the proposed controller, the model predictive control (MPC) is used to ensure that the robot states satisfy the passivity constraint by calculating a complementary torque to limit the stored energy of the robot. The passivity of the closed-loop robot system and the feasibility of MPC are guaranteed by theoretical analysis, ensuring the safety of the robotic movement in the human-robot interaction. The effectiveness of the proposed method is demonstrated by the simulation and experiment on the Franka Emika Panda robot.

Neural Reactivity to Haptics: Virtual Tasks Versus Physical Tasks

Neural Reactivity to Haptics: Virtual Tasks Versus Physical Tasks

Решение физических задач как инструмент формирования профессиональных компетенций врача и провизора

Solving physical problems can be considered as a goal and method of teaching. Insufficient fundamental knowledge of medical university students will not allow them to meet modern requirements of medical science. The choice of physics tasks, the content of which is focused on the future profession, contributes to the formation of professional and general cultural competencies of a doctor and a pharmacist. It is reasonable to use such tasks in different types of classes: seminars, laboratory workshops, colloquiums. Motivation is increased by selecting tasks taking into account the future medical specialty and identifying interdisciplinary connections. The article provides examples of tasks in accordance with the goals set during the lesson.

Neural Physical Simulation with Multi-Resolution Hash Grid Encoding

We explore the generalization of the implicit representation in the physical simulation task. Traditional time-dependent partial differential equations (PDEs) solvers for physical simulation often adopt the grid or mesh for spatial discretization, which is memory-consuming for high resolution and lack of adaptivity. Many implicit representations like local extreme machine or Siren are proposed but they are still too compact to suffer from limited accuracy in handling local details and a long time of convergence. We contribute a neural simulation framework based on multi-resolution hash grid representation to introduce hierarchical consideration of global and local information, simultaneously. Furthermore, we propose two key strategies: 1) a numerical gradient method for computing high-order derivatives with boundary conditions; 2) a range analysis sample method for fast neural geometry boundary sampling with dynamic topologies. Our method shows much higher accuracy and strong flexibility for various simulation problems: e.g., large elastic deformations, complex fluid dynamics, and multi-scale phenomena which remain challenging for existing neural physical solvers.

Assessment of an arm-support exoskeleton on physical demands, task performance, and usability during simulated agricultural tasks

This laboratory-based study aimed to determine whether an arm-support exoskeleton (ASE) would be an effective intervention to reduce the physical strain associated with manual agricultural work. Twenty-four (gender-balanced) participants performed pruning and harvesting tasks (at four different heights: knee, elbow, shoulder, and overhead), lifting/lowering, and Timed Up & Go (TUG) tasks with and without an ASE. During these tasks, muscle activity (in the upper trapezius, anterior deltoid, biceps brachii, and erector spinae), task completion time, perceived exertion, and usability were assessed. The results indicated a significant reduction (31.7%–60.2%) in muscle activity, particularly in the upper trapezius and anterior deltoid, when using the ASE during tasks at shoulder work height or above. However, there was an observed increase in muscle strain in the erector spinae, suggesting potential risk to the lower back. Given these findings, a more rigorous evaluation of ASEs in agricultural tasks should be pursued before implementing exoskeletons in agricultural tasks to avoid unintended health hazards. Relevance to industryA relatively new application of exoskeleton technology, extensively studied in fields like rehabilitation, manufacturing, and the military, is its use in agriculture. This study details the physical requirements of specific tasks to offer insights into the challenges that exoskeleton technologies for agriculture may encounter.

Dysphagia and Functional Limitations Among Adults in the United States: Findings from the 2022 National Health Interview Survey.

Dysphagia or swallowing dysfunction is associated with reduced quality of life and poor long term outcomes. While standard dysphagia treatment focuses on improving swallowing function, it is not clear if people with dysphagia also have difficulties performing daily tasks. This study aimed to determine if individuals with dysphagia had difficulties with participating in daily tasks requiring physical function, as compared to those with no dysphagia. We conducted a secondary data analysis using the responses of 24,107 adults aged 18years or older who completed the 2022 National Health Interview Survey. The independent variable was report of swallowing problem during the past 12months, and the dependent variables were report of difficulty in physical function tasks (e.g., self-care, mobility, working, social participation). We utilized propensity score methods to balance demographic and clinical variables between groups, and examined if individuals with dysphagia had more difficulties with the physical function tasks. The propensity score methods balanced the demographic and clinical variables (absolute standardized differences < 0.1). People with dysphagia had significantly higher odds ratios (ranged from 1.23 to 1.70, all p < 0.05) of having difficulties in physical function tasks than those without dysphagia. The findings revealed an association between experiencing dysphagia and encountering difficulties in self-care, mobility, working, and social participation in the general adult population in the US. Results of our study indicate that during the course of rehabilitation, healthcare professionals should consider the potential impact of dysphagia symptoms on clients' ability to partake in independent activities in their community settings.

The impact of boxing on the physical health of young athletes at the initial training stage

Modern socio-economic and political problems in Ukraine, associated with martial law, place high demands on the physical health, performance and active physical condition of schoolchildren. Boxing is currently very popular among many youth sports. The purpose of the study is to experimentally test the effect of boxing on the physical health of young athletes at the stage of initial training. Methodology. To solve the problems, the following research methods were used: analysis of scientific and methodological literature; sociological methods (survey, conversations, questionnaires); pedagogical methods (pedagogical observation, pedagogical experiment); physiometric and index methods; methods of mathematical statistics. The scientific novelty of the study lies in the improvement of the methodology for using boxing tools to improve the health level of young athletes at the stage of initial training. Results. The formation of the experimental methodology was based on the following pedagogical provisions: an integrated approach to the development of physical qualities; health-improving orientation of boxing classes, which was ensured by regular physical activity, compliance with general didactic principles of accessibility, gradualism and age-appropriate technical and physical tasks, as well as by conducting the vast majority of classes in the fresh air. Conclusions. The final assessment of the level of physical health of the test subjects in the experimental group corresponds to above the average level of health, while for the young boxers in the control group it corresponds to below the average level of health. This fact indicates the effectiveness of the introduced boxing training methodology at the initial training stage.

Computing multi-eigenpairs of high-dimensional eigenvalue problems using tensor neural networks

In this paper, we propose a type of tensor-neural-network-based machine learning method to compute multi-eigenpairs of high dimensional eigenvalue problems without Monte-Carlo procedure. Solving multi-eigenvalues and their corresponding eigenfunctions is one of the basic tasks in mathematical and computational physics. With the help of tensor neural network, the high dimensional integrations included in the loss functions of the machine learning process can be computed with high accuracy. The high accuracy of high dimensional integrations can improve the accuracy of the machine learning method for computing multi-eigenpairs of high dimensional eigenvalue problems. Here, we introduce the tensor neural network and design the machine learning method for computing multi-eigenpairs of the high dimensional eigenvalue problems. The proposed numerical method is validated with plenty of numerical examples.

The impact of task (un)certainty on repeated grip force production

Many studies found that in physical tasks, reducing certainty regarding their endpoints hinders performance. However, the impact of reducing certainty regarding other aspects of physical tasks is unknown. Here we manipulated the certainty of the required effort on an unrelated, parallel task (i.e., off-task uncertainty) and examined how it impacts force production in two within-subject experiments (N = 79). In two sessions, subjects completed 20 repetitions composed of maximal forces using a gripper with their dominant hand. Between repetitions, participants applied either submaximal constant or varied grip forces, with their non-dominant arm, matched for total forces across repetitions. While we observed trivial differences in total forces between conditions, under the varied condition, participants produced a steeper decrease in forces, suggesting that off-task uncertainty impacted their effort allocation strategy. We speculate that this pattern can be attributed to cognitive overload and/or changes in motivation stemming from the imposed uncertainty.

Interactive boxing–cycling on frailty and activity limitations in frail and prefrail older adults: A randomized controlled trial

BackgroundFrailty is common among older adults, often associated with activity limitations during physical and walking tasks. The interactive boxing-cycling combination has the potential to be an innovative and efficient training method, and our hypothesis was that interactive boxing-cycling would be superior to stationary cycling in improving frailty and activity limitations in frail and prefrail older adults. ObjectiveTo examine the impact of interactive boxing-cycling on frailty and activity limitations in frail and prefrail older adults compared to stationary cycling. Materials and methodsA single-blinded randomized controlled trial. Forty-five participants who met at least one frailty phenotype criteria were randomly assigned to receive either interactive boxing-cycling (n = 23) or stationary-cycling (n = 22) for 36 sessions over 12 weeks. The interactive boxing-cycling was performed on a cycle boxer bike with an interactive boxing panel fixed in front of the bike. The primary outcomes were frailty status, including score and phenotypes. Secondary outcomes included activity limitations during physical and walking tasks. The pre- and post-intervention data of both groups were analyzed using a repeated measures two-way ANOVA. ResultsBoth types of cycling significantly improved frailty scores (p<0.001). Interactive boxing-cycling was more effective than stationary cycling in reversing the frailty phenotype of muscle weakness (p = 0.03, odds ratio 9.19) and demonstrated greater improvements than stationary cycling in arm curl (p = 0.002, η2=0.20), functional reach (p = 0.001, η2=0.22), and grip strength (p = 0.02, η2=0.12) tests. Additionally, interactive boxing-cycling exhibited a greater effect on gait speed (p = 0.02, η2=0.13) and gait variability (p = 0.01, η2=0.14) during dual-task walking. ConclusionIn frail and prefrail older adults, interactive boxing-cycling effectively improves frailty but is not superior to stationary cycling. However, it is more effective at improving certain activity limitations. Registration numberTCTR20220328001

Risk of unfavorable pain prognosis impacts walking physiomechanical parameters and psychophysiological workload in sufferers of chronic low back pain

BackgroundTolerating physical tasks depends not only on task-specific characteristics but also on an individual's psychophysiological capacity to respond to the imposed load. People suffering from chronic low back pain (CLBP) may experience reduced psychophysiological capacity and are at risk for poor pain prognosis, which could lead to an increased walking workload. AimTo investigate how the risk of unfavorable pain prognosis in CLBP can impact walking physiomechanical parameters and psychophysiological workload. MethodsA cross-sectional observational study. The study classified 74 volunteers into four groups based on their prognosis for pain: pain-free control (CG/n = 20), low (LrG/n = 21), medium (MrG/n = 22), and high (HrG/n = 11) risk of poor prognosis for CLBP. The ground assessments identified the self-selected (SSW) and optimal (OWS) walking speeds, as well as the locomotor rehabilitation index (LRI). Treadmill assessments were conducted at two different speeds (0.83 and 1.11 m s−1, SSW and OWS) to record physiomechanical parameters. Psychophysiological workloads during walking were measured via workload impulse for the session (TRIMP), determined by variations in heart rate. ResultsCLBP groups exhibited slower SSW and lower LRI compared to the CG. The TRIMP was lower in the LrG. However, both MrG and HrG exhibited a comparable overload to the CG, even while walking at a lower intensity with a psychophysical demand. SSW and OWS displayed an increased TRIMP compared to fixed speeds. ConclusionPsychosocial factors may affect SSW in people with CLBP but not among the risk strata. An unfavorable prognosis for pain could jeopardize the psychophysiological capacity to withstand walking demands.

Feature selection with distance correlation

Choosing which properties of the data to use as input to multivariate decision algorithms—also known as feature selection—is an important step in solving any problem with machine learning. While there is a clear trend towards training sophisticated deep networks on large numbers of relatively unprocessed inputs (so-called automated feature engineering), for many tasks in physics, sets of theoretically well-motivated and well-understood features already exist. Working with such features can bring many benefits, including greater interpretability, reduced training and run time, and enhanced stability and robustness. We develop a new feature selection method based on distance correlation, and demonstrate its effectiveness on the tasks of boosted top- and W-tagging. Using our method to select features from a set of over 7,000 energy flow polynomials, we show that we can match the performance of much deeper architectures, by using only ten features and two orders-of-magnitude fewer model parameters. Published by the American Physical Society 2024

Association between match-related physical activity profiles and playing positions in different tasks: A data driven approach

ABSTRACT Assessing the intensity characteristics of specific soccer drills (matches, small-side game, and match-based exercises) could help practitioners to plan training sessions by providing the optimal stimulus for every player. In this paper, we propose a data analytics framework to assess the neuromuscular or metabolic characteristics of a soccer-specific exercise in relation with the expected match intensity. GPS data describing the physical tasks’ external intensity during an entire season of twenty-eight semi-professional soccer players competing at the fourth Italian division were used in this study. A supervised machine-learning approach was tested in order to detect difference in playing positions in different sport-specific drills. Moreover, a non-supervised machine-learning model was used to profile the match neuromuscular and metabolic characteristics. Players’ playing positions during matches and match-based exercises are characterised by specific metabolic and neuromuscular characteristics related to tactical demands, while in the small-side game these differences are not detected. Additionally, our framework permits to evaluate if the match performance request is mirrored during training drills. Practitioners could evaluate the type of stimulus performed by a player in a specific training drill in order to assess if they reflect the matches characteristics of their specific playing position.

Efektivitas Program Pendaftaran Tanah Sistematis Lengkap (PTSL) di Kantor Pertanahan Kabupaten Aceh Tengah

This study aims to find out and analyze how the PTSL program at the Central Aceh District Land Office is running. The research method used a qualitative research method with a descriptive approach. Data collection techniques were carried out by interviews, observation, documentation and literature study. Informants came from the PTSL program implementation team, namely the physical and juridical task force, village committee and the community who participated in program implementation. The results of the study show that there are two problems in implementing the PTSL program in Central Aceh District, namely; first, the slow process of distributing certificates to the public. Second, the community complained about being quoted the cost of preparing for the implementation of the program as an operation in the village. The long implementation of the program was due to a lack of communication and coordination that existed between the implementing committee, namely the village and the Central Aceh District Land Office committee. Meanwhile, the preparation costs quoted from the community were in accordance with applicable regulations, namely a maximum quotation of Rp. 250,000 per plot of land and an additional Rp. 50,000 if there is no basis for land right. There are no other citations outside of the regulations, so there is no indication of extortion in the implementation of the program caused by the leadership of the Head of the Land Office who gave a firm warning to both the office implementing committee and the committee in the village implementing the program.

A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks

Machine learning algorithms are heavily relied on to understand the vast amounts of data from high-energy particle collisions at the CERN Large Hadron Collider (LHC). The data from such collision events can naturally be represented with graph structures. Therefore, deep geometric methods, such as graph neural networks (GNNs), have been leveraged for various data analysis tasks in high-energy physics. One typical task is jet tagging, where jets are viewed as point clouds with distinct features and edge connections between their constituent particles. The increasing size and complexity of the LHC particle datasets, as well as the computational models used for their analysis, have greatly motivated the development of alternative fast and efficient computational paradigms such as quantum computation. In addition, to enhance the validity and robustness of deep networks, we can leverage the fundamental symmetries present in the data through the use of invariant inputs and equivariant layers. In this paper, we provide a fair and comprehensive comparison of classical graph neural networks (GNNs) and equivariant graph neural networks (EGNNs) and their quantum counterparts: quantum graph neural networks (QGNNs) and equivariant quantum graph neural networks (EQGNN). The four architectures were benchmarked on a binary classification task to classify the parton-level particle initiating the jet. Based on their area under the curve (AUC) scores, the quantum networks were found to outperform the classical networks. However, seeing the computational advantage of quantum networks in practice may have to wait for the further development of quantum technology and its associated application programming interfaces (APIs).

Research and application of multimedia compression technology in online physical education teaching task

Research and application of multimedia compression technology in online physical education teaching task

Effect of Grip strength on Work Efficiency in Hand Tools Tasks

The overarching goal of ergonomics is to enhance performance and ensure workplace safety during physical tasks, simultaneously minimizing musculoskeletal disorders and energy expenditure. Recently, concerns have arisen about body measurements contributing not only to musculoskeletal issues but also to a potential decline in energy and work efficiency. Hence, this study aimed to explore the impact of maximum grip strength (MGS) on activity energy expenditure (AEE) and work efficiency. AEE measurements, conducted using the Actiheart, were carried out with 10 subjects performing a drilling task in 12 coordinated postures involving the shoulder, trunk, and leg. Analysis through independent samples t-test and mean differences revealed that AEE decreased as subject's MGS increased. Individuals with higher MGS exhibited lower in AEE, suggesting greater efficiency in their performance.

Household Sustainability Labour and the Gendering of Responsibility for Low Waste Living

This article explores the nature of domestic labour involved in sustainability transitions at the household level, with waste reduction as an exemplar. We draw on national survey data (N = 2717) from Australia, and qualitative data from a participatory action project working with 34 householders on experiments in low waste living. We found low waste living was challenging work mentally, physically and interpersonally and required information, skills and the resources of time and money. Waste reduction in households also required relational labour inside and outside the household. On the basis of existing literature and our findings we theorise that sustainability labour is comprised of five overlapping elements: physical, cognitive, relational, economic and political tasks. We argue that reducing waste is an example of sustainability labour that is led largely by women, as they work to change household practices and the systems in which these are embedded, towards a more sustainable future.

Benefits and risk of using crossfit training to the process of physical training of military specialists

The physical preparation of military personnel remains a pertinent focus of scientific inquiry in the development of a contemporary army. This necessitates the exploration of effective fitness training approaches that contribute to crafting an efficient methodology for the physical readiness of military specialists. CrossFit emerges as a popular and effective direction capable of addressing this challenge. Analysis has permitted the synthesis of information about the essence of CrossFit as a high-intensity method of physical training, highlighting its advantages in enhancing the physical fitness and functional readiness of military personnel. Despite the potential benefits and accessibility of CrossFit, caution is warranted regarding its integration into the military’s physical training system due to the heightened risk of injuries, which could impact the quality of their professional duties. Therefore, a meticulous examination of CrossFit training specifics is imperative, taking into account the unique demands and fitness requirements of military personnel. The availability of CrossFit exercises enables the creation of flexible training programs using block planning within a macrocycle duration. This facilitates the al ternating focus of training and the comprehensive execution of military physical training tasks. Implementing CrossFit in military physical training should consider the peculiarities of the profession and the contextual conditions, adhering to safety protocols during exercise execution. This necessitates careful attention to mastering the rational technique of exercises. The selection of training modes should align with the training objectives and the current functional status and fitness level of military personnel. Overall, CrossFit proves to be an effective tool for physical training, with successful integration possible if methodological adherence is maintained, thereby unlocking its advantages for addressing the physical training needs of the army.