An Ergonomics Analysis of Archers through Motion Tracking to Prevent Injuries and Improve Performance.

Archery ranks among the sports with a high incidence of upper extremity injuries, particularly affecting the drawing shoulder and elbow, as well as inducing stress on the lower back. This study seeks to bridge the gap by integrating real-time human motion with biomechanical software to enhance the ergonomics of archers. Thirteen participants were involved in four tasks, using different bows with varied draw weights and shooting distances. Through the application of advanced integrative technology, this study highlights the distinct postures adopted by both males and females, which indicate the biomechanical differences between genders. Additionally, an analysis of the correlation between exposed spinal forces and these adopted postures provides insights into injury risk assessment during the key archery movements. The findings of this study have the potential to significantly enhance the application of training methodologies and the design of assistive devices. These improvements are geared towards mitigating injury risks and enhancing the overall performance of archers.

The Effect of Key Anthropometric and Biomechanics Variables Affecting the Lower Back Forces of Healthcare Workers.

Wearable devices are becoming ubiquitous and can be used to better estimate postures and movements to reduce the risk of injuries. Thirty-three participants were recruited in this study to perform two daily repetitive patient transfer tasks while the full body movements were acquired using a set of magneto-inertial wearable devices. The use of wearable devices allowed for the estimation of the forces provoked on the lower back during the entire task performance. In postures where the forces exceeded the warning threshold found in the literature, healthcare workers were considered to have a greater risk of injury. Additionally, the maximum force exerted by each hand to avoid injury to the spinal column was also estimated. Knowing the key anthropometric variables associated with musculoskeletal disorders (MSDs) will enable engineers and researchers to design better assistive devices and injury prevention programs in diverse workplaces.

Using Digital Human Modelling to Evaluate the Risk of Musculoskeletal Injury for Workers in the Healthcare Industry.

BACKGROUND: Hospital nurses and caregivers are reported to have the highest number of workplace injuries every year, which directly leads to missed days of work, a large amount of compensation costs, and staff shortage issues in the healthcare industry. Hence, this research study provides a new technique to evaluate the risk of injuries for healthcare workers using a combination of unobtrusive wearable devices and digital human technology. The seamless integration of JACK Siemens software and the Xsens motion tracking system was used to determine awkward postures adopted for patient transfer tasks. This technique allows for continuous monitoring of the healthcare worker's movement which can be obtained in the field. METHODS: Thirty-three participants underwent two common tasks: moving a patient manikin from a lying position to a sitting position in bed and transferring the manikin from a bed to a wheelchair. By identifying, in these daily repetitive patient-transfer tasks, potential inappropriate postures that can be conducive to excessive load on the lumbar spine, a real-time monitoring process can be devised to adjust them, accounting for the effect of fatigue. Experimental Result: From the results, we identified a significant difference in spinal forces exerted on the lower back between genders at different operational heights. Additionally, we revealed the main anthropometric variables (e.g., trunk and hip motions) that are having a large impact on potential lower back injury. CONCLUSIONS: These results will lead to implementation of training techniques and improvements in working environment design to effectively reduce the number of healthcare workers experiencing lower back pain, which can be conducive to fewer workers leaving the healthcare industry, better patient satisfaction and reduction of healthcare costs.

Depth-Dependent Control in Vision-Sensor Space for Reconfigurable Parallel Manipulators.

In this paper, a control approach for reconfigurable parallel robots is designed. Based on it, controls in the vision-sensor, 3D and joint spaces are designed and implemented in target tracking tasks in a novel reconfigurable delta-type parallel robot. No a priori information about the target trajectory is required. Robot reconfiguration can be used to overcome some of the limitations of parallel robots like small relative workspace or multiple singularities, at the cost of increasing the complexity of the manipulator, making its control design even more challenging. No general control methodology exists for reconfigurable parallel robots. Tracking objects with unknown trajectories is a challenging task required in many applications. Sensor-based robot control has been actively used for this type of task. However, it cannot be straightforwardly extended to reconfigurable parallel manipulators. The developed vision-sensor space control is inspired by, and can be seen as an extension of, the Velocity Linear Camera Model-Camera Space Manipulation (VLCM-CSM) methodology. Several experiments were carried out on a reconfigurable delta-type parallel robot. An average positioning error of 0.6 mm was obtained for static objectives. Tracking errors of 2.5 mm, 3.9 mm and 11.5 mm were obtained for targets moving along a linear trajectory at speeds of 6.5, 9.3 and 12.7 cm/s, respectively. The control cycle time was 16 ms. These results validate the proposed approach and improve upon previous works for non-reconfigurable robots.

A Novel Velocity-Based Control in a Sensor Space for Parallel Manipulators.

It is a challenging task to track objects moving along an unknown trajectory. Conventional model-based controllers require detailed knowledge of a robot's kinematics and the target's trajectory. Tracking precision heavily relies on kinematics to infer the trajectory. Control implementation in parallel robots is especially difficult due to their complex kinematics. Vision-based controllers are robust to uncertainties of a robot's kinematic model since they can correct end-point trajectories as error estimates become available. Robustness is guaranteed by taking the vision sensor's model into account when designing the control law. All camera space manipulation (CSM) models in the literature are position-based, where the mapping between the end effector position in the Cartesian space and sensor space is established. Such models are not appropriate for tracking moving targets because the relationship between the target and the end effector is a fixed point. The present work builds upon the literature by presenting a novel CSM velocity-based control that establishes a relationship between a movable trajectory and the end effector position. Its efficacy is shown on a Delta-type parallel robot. Three types of experiments were performed: (a) static tracking (average error of 1.09 mm); (b) constant speed linear trajectory tracking-speeds of 7, 9.5, and 12 cm/s-(tracking errors of 8.89, 11.76, and 18.65 mm, respectively); (c) freehand trajectory tracking (max tracking errors of 11.79 mm during motion and max static positioning errors of 1.44 mm once the object stopped). The resulting control cycle time was 48 ms. The results obtained show a reduction in the tracking errors for this robot with respect to previously published control strategies.

Modeling the neuro-mechanics of human balance when recovering from a fall: a continuous-time approach.

BACKGROUND: Balance control deteriorates with age and nearly 30% of the elderly population in the United States reports stability problems. Postural stability is an integral task to daily living reliant upon the control of the ankle and hip. To this end, the estimation of joint parameters can be a useful tool when analyzing compensatory actions aimed at maintaining postural stability. METHODS: Using an analytical approach, this study expands on previous work and analyzes a two degrees of freedom human model. The first two modes of vibration of the system are represented by the neuro-mechanical parameters of a second-order, time-varying Kelvin-Voigt model actuated at the ankle and hip. The model is tested using a custom double inverted pendulum and healthy volunteers who were subjected to a positional step-like perturbation during quiet standing. An in silico sensitivity analysis of the influence of inertial parameters was also performed. RESULTS: The proposed method is able to correctly identify the time-varying visco-elastic parameters of of a double inverted pendulum. We show that that the parameter estimation method can be applied to standing humans. These results appear to identify a subject-independent strategy to control quiet standing that combines both the modulation of stiffness, and the use of an intermittent control. CONCLUSIONS: This paper presents the analysis of the non-linear system of differential equations representing the control of lumped muscle-tendon units. It utilizes motion capture measurements to obtain the estimates of the system's control parameters by constructing a simple time-dependent regressor for estimating the time-varying parameters of the control with a single perturbation. This work is a step forward into the understanding of the neuro-mechanical control parameters of human recovering from a fall. In previous literature, the analysis is either restricted to the first vibrational mode of an inverted-pendulum model or assumed to be time-invariant. The proposed method allows for the analysis of hip related movement for stability control and highlights the importance of core training.

Towards a Simplified Estimation of Muscle Activation Pattern from MRI and EMG Using Electrical Network and Graph Theory.

Muscle functional MRI (mfMRI) is an imaging technique that assess muscles' activity, exploiting a shift in the T2-relaxation time between resting and active state on muscles. It is accompanied by the use of electromyography (EMG) to have a better understanding of the muscle electrophysiology; however, a technique merging MRI and EMG information has not been defined yet. In this paper, we present an anatomical and quantitative evaluation of the method our group introduced in to quantify its validity in terms of muscle pattern estimation for four subjects during four isometric tasks. Muscle activation pattern are estimated using a resistive network to model the morphology in the MRI. An inverse problem is solved from sEMG data to assess muscle activation. The results have been validated with a comparison with physiological information and with the fitting on the electrodes space. On average, over 90% of the input sEMG information was able to be explained with the estimated muscle patterns. There is a match with anatomical information, even if a strong subjectivity is observed among subjects. With this paper we want to proof the method's validity showing its potential in diagnostic and rehabilitation fields.

A Computational Index to Describe Slacking During Robot Therapy.

Movement facilitation has a fundamental role in the rehabilitation treatment of stroke survivors. However, its action mechanisms are still poorly understood. An open question is to identify the effect of the level of assistance on the recovery process. To address this topic, new insight on voluntary control and movement strategies during rehabilitation must be gained. Robot-assisted arm movements were examined in a task where subjects had to reach distal targets in the presence of assistive forces. As the training proceeded, subjects improved their performance and exercised with both the initial force level of the first session and with progressively decreasing levels of assistive force. We found that when stroke survivors became to execute voluntary movements with lower forces levels they decreased their voluntary control in the presence of higher forces, following a minimum effort trajectory. These findings provide a new important insight for the rehabilitation of stroke survivors, suggesting that passive mobilization and exercise with constant force, although useful for muscular reinforcement, may have a detrimental effect on voluntary control and movements planning.

Synthesis of Poly-Lactic Acid by Ring Open Polymerization from Beer Spent Grain for Drug Delivery.

Poly-lactic acid (PLA) is a synthetic polymer that has gained popularity as a scaffold due to well-established manufacturing processes, predictable biomaterial properties, and sustained therapeutic release rates. However, its drawbacks include weak mechanical parameters and reduced medicinal delivery efficacy after PLA degradation. The development of synthetic polymers that can release antibiotics and other medicines remains a top research priority. This study proposes a novel approach to produce PLA by converting Brewer's spent grain (BSG) into lactic acid by bacterial fermentation followed by lactide ring polymerization with a metal catalyst. The elution properties of the PLA polymer are evaluated using modified Kirby-Bauer assays involving the antimicrobial chemotherapeutical, trimethoprim (TMP). Molded PLA polymer disks are impregnated with a known killing concentration of TMP, and the PLA is evaluated as a drug vehicle against TMP-sensitive Escherichia coli. This approach provides a practical means of assessing the polymer's ability to release antimicrobials, which could be beneficial in exploring new drug-eluting synthetic polymer strategies. Overall, this study highlights the potential of using BSG waste materials to produce valuable biomaterials of medical value with the promise of expanded versatility of synthetic PLA polymers in the field of drug-impregnated tissue grafts.

Experimental measure of arm stiffness during single reaching movements with a time-frequency analysis.

We tested an innovative method to estimate joint stiffness and damping during multijoint unfettered arm movements. The technique employs impulsive perturbations and a time-frequency analysis to estimate the arm's mechanical properties along a reaching trajectory. Each single impulsive perturbation provides a continuous estimation on a single-reach basis, making our method ideal to investigate motor adaptation in the presence of force fields and to study the control of movement in impaired individuals with limited kinematic repeatability. In contrast with previous dynamic stiffness studies, we found that stiffness varies during movement, achieving levels higher than during static postural control. High stiffness was associated with elevated reflexive activity. We observed a decrease in stiffness and a marked reduction in long-latency reflexes around the reaching movement velocity peak. This pattern could partly explain the difference between the high stiffness reported in postural studies and the low stiffness measured in dynamic estimation studies, where perturbations are typically applied near the peak velocity point.

Critical damping conditions for third order muscle models: implications for force control.

Experimental results presented in the literature suggest that humans use a position control strategy to indirectly control force rather than direct force control. Modeling the muscle-tendon system as a third-order linear model, we provide an explanation of why an indirect force control strategy is preferred. We analyzed a third-order muscle system and verified that it is required for a faithful representation of muscle-tendon mechanics, especially when investigating critical damping conditions. We provided numerical examples using biomechanical properties of muscles and tendons reported in the literature. We demonstrated that at maximum isotonic contraction, for muscle and tendon stiffness within physiologically compatible ranges, a third-order muscle-tendon system can be under-damped. Over-damping occurs for values of the damping coefficient included within a finite interval defined by two separate critical limits (such interval is a semi-infinite region in second-order models). An increase in damping beyond the larger critical value would lead the system to mechanical instability. We proved the existence of a theoretical threshold for the ratio between tendon and muscle stiffness above which critical damping can never be achieved; thus resulting in an oscillatory free response of the system, independently of the value of the damping. Under such condition, combined with high muscle activation, oscillation of the system can be compensated only by active control.

Preparation of Nanopaper for Colorimetric Food Spoilage Indication.

In this study, we are reporting the fabrication of a nanocellulose (NFC) paper-based food indicator for chicken breast spoilage detection by both visual color change observation and smartphone image analysis. The indicator consists of a nanocellulose paper (nanopaper) substrate and a pH-responsive dye, bromocresol green (BCG), that adsorbs on the nanopaper. The nanopaper is prepared through vacuum filtration and high-pressure compression. The nanopaper exhibits good optical transparency and strong mechanical strength. The color change from yellow to blue in the nanopaper indicator corresponding to an increase in the solution pH and chicken breast meat storage data were observed and analyzed, respectively. Further, we were able to use color differences determined by the RGB values from smartphone images to analyze the results, which indicates a simple, sensitive, and readily deployable approach toward the development of future smartphone-based food spoilage tests.

Comparative analysis of methods for estimating arm segment parameters and joint torques from inverse dynamics.

A common problem in the analyses of upper limb unfettered reaching movements is the estimation of joint torques using inverse dynamics. The inaccuracy in the estimation of joint torques can be caused by the inaccuracy in the acquisition of kinematic variables, body segment parameters (BSPs), and approximation in the biomechanical models. The effect of uncertainty in the estimation of body segment parameters can be especially important in the analysis of movements with high acceleration. A sensitivity analysis was performed to assess the relevance of different sources of inaccuracy in inverse dynamics analysis of a planar arm movement. Eight regression models and one water immersion method for the estimation of BSPs were used to quantify the influence of inertial models on the calculation of joint torques during numerical analysis of unfettered forward arm reaching movements. Thirteen subjects performed 72 forward planar reaches between two targets located on the horizontal plane and aligned with the median plane. Using a planar, double link model for the arm with a floating shoulder, we calculated the normalized joint torque peak and a normalized root mean square (rms) of torque at the shoulder and elbow joints. Statistical analyses quantified the influence of different BSP models on the kinetic variable variance for given uncertainty on the estimation of joint kinematics and biomechanical modeling errors. Our analysis revealed that the choice of BSP estimation method had a particular influence on the normalized rms of joint torques. Moreover, the normalization of kinetic variables to BSPs for a comparison among subjects showed that the interaction between the BSP estimation method and the subject specific somatotype and movement kinematics was a significant source of variance in the kinetic variables. The normalized joint torque peak and the normalized root mean square of joint torque represented valuable parameters to compare the effect of BSP estimation methods on the variance in the population of kinetic variables calculated across a group of subjects with different body types. We found that the variance of the arm segment parameter estimation had more influence on the calculated joint torques than the variance of the kinematics variables. This is due to the low moments of inertia of the upper limb, especially when compared with the leg. Therefore, the results of the inverse dynamics of arm movements are influenced by the choice of BSP estimation method to a greater extent than the results of gait analysis.

The Kapitza's Pendulum as a Concurrent Strategy for Maintaining Upright Posture.

A Kapitza's pendulum shows that it is possible to stabilize an inverted pendulum by making its base oscillate vertically. This action seems to introduce an inertial effect which will produce an attractor about the upright vertical position. This work shows that the upright posture of the trunk achieved while walking can be explained using a combination of a vertical oscillation and an angular stiffness regulation at the pelvis. This is shown with an estimated oscillation and stiffness obtained from video recordings of an unimpaired and a Parkinsoninan gaits. By simulating the dynamic model of the pendulum for a range of parameters, a series of stability conditions are found. They show that the introduction of the vertical oscillation results in a fast stabilization of the trunk and point to control strategies which rely on the system's dynamics.

The Effect of Crank Resistance on Arm Configuration and Muscle Activation Variances in Arm Cycling Movements.

Arm cycling on an ergometer is common in sports training and rehabilitation protocols. The hand movement is constrained along a circular path, and the user is working against a resistance, maintaining a cadence. Even if the desired hand trajectory is given, there is the flexibility to choose patterns of joint coordination and muscle activation, given the kinematic redundancy of the upper limb. With changing external load, motor noise and changing joint stiffness may affect the pose of the arm even though the endpoint trajectory is unchanged. The objective of this study was to examine how the crank resistance influences the variances of joint configuration and muscle activation. Fifteen healthy participants performed arm cranking on an arm-cycle ergometer both unimanually and bimanually with a cadence of 60 rpm against three crank resistances. Joint configuration was represented in a 3-dimensional joint space defined by inter-segmental joint angles, while muscle activation in a 4-dimensional "muscle activation space" defined by EMGs of 4 arm muscles. Joint configuration variance in the course of arm cranking was not affected by crank resistance, whereas muscle activation variance was proportional to the square of muscle activation. The shape of the variance time profiles for both joint configuration and muscle activation was not affected by crank resistance. Contrary to the prevailing assumption that an increased motor noise would affect the variance of auxiliary movements, the influence of noise doesn't appear at the joint configuration level even when the system is redundant. Our results suggest the separation of kinematic- and force-control, via mechanisms that are compensating for dynamic nonlinearities. Arm cranking may be suitable when the aim is to perform training under different load conditions, preserving stable and secure control of joint movements and muscle activations.

Taxonomy of Two Dimensional Bio-Inspired Locomotion Systems.

This paper introduces a new approach to characterize the locomotion of self-assembling modular systems. By establishing the necessary components for a locomotive modules and a hierarchy of locomotive systems, further research can be done into each category. The systems are broken into three primary groups: limbed, limbless, and rolling. The majority of the variations exist within the legged domain, and hence the largest area of study rests there. This study contributes to the literature inasmuch as creating a hierarchical framework that can be used for the creation of algorithms for self-assembling micro and nano robots for drug delivery and surgery.

Experimental Estimation of a Second Order, Double Inverted Pendulum Parameters for the study of Human Balancing.

Balance control deteriorates naturally with age and is reliant upon the control of the ankle and hip joints. To this end, the estimation of ankle and hip parameters in quiet standing can be a useful tool when analyzing compensatory actions aimed at maintaining postural stability. This work presents an experimental study of a theoretical approach built upon previous results where the physiological parameters a second-order time-varying Kelvin-Voigt model are estimated for the actuation of the ankle and hip. These estimates are obtained using a double inverted pendulum based model subject to a step-like perturbation. Making use of RGB camera data to obtain the estimates of the system's visco-elastic parameters, the approach employed is capable of estimating the time-varying values for the body's control parameters. This work presents the first results of the method demonstrating the viability of a low-cost technique for regular testing of subjects with a high fall risk.

The Concurrent Control of Motion and Contact Force in the Presence of Predictable Disturbances.

The simultaneous control of force and motion is important in everyday activities when humans interact with objects. While many studies have analyzed the control of movement within a perturbing force field, few have investigated its dual aspects of controlling a contact force in nonisometric conditions. The mechanism by which the central nervous system controls forces during movements is still unclear, and it can be elucidated by estimating the mechanical properties of the arm during tasks with concurrent motion and contact force goals. We investigate how arm mechanics change when a force control task is accomplished during low-frequency positional perturbations of the arm. Contrary to many force regulation algorithms implemented in robotics, where contact impedance is decreased to reduce force fluctuations in response to position disturbances, we observed a steady increase of arm endpoint stiffness as the task progressed. Based on this evidence, we propose a theoretical framework suggesting that an internal model of the perturbing trajectory is formed. We observed that force regulation in the presence of predictable positional disturbances is implemented using a position control strategy together with the modulation of the endpoint stiffness magnitude, where the direction of the endpoint stiffness ellipse's major axis is oriented toward the desired force.

Jerk Decomposition during Bimanual Independent Arm Cranking.

The relationship between the smoothness of the upper limb endpoint movement and multi joint angular motion is a function of the individual joint angular velocities, accelerations, and jerks as well as the instantaneous arm configuration and its rate of change during movement execution. We compared the contribution of jerk components to the total endpoint jerk in able bodied participants who performed arm cranking movements on an arm cranking device where the two arms could crank independently. The results of this investigation suggest that the most dominant components of the end effector jerk are related to both the angular jerks and to the change of arm configuration pose. This jerk partitioning is much stronger as it was found previously for both reaching arm movements and single hand cranking. This shows the task specificity of the decomposition of endpoint jerk and the effect that bi-manual tasks can have on the smoothness of movements. The proposed decomposition may give useful information in why certain bi-manual rehabilitation processes are more useful than others.

A framework for closing the loop between human experts and computational algorithms for the assessment of movement disorders.

Clinical assessment of abnormal neuromechanics is typically performed by manipulation of the affected limbs; a process with low inter- and intra-rater reliability. This paper aims at formalizing a framework that closes the loop between a clinician's expertise and computational algorithms, to enhance the clinician's diagnostic capabilities during physical manipulation. The framework's premise is that the dynamics that can be measured by manipulation of a limb are distinct between movement disorders. An a priori database contains measurements encoded in a space called the information map. Based on this map, a computational algorithm identifies which probing motions are more likely to yield distinguishing information about a patient's movement disorder. The clinician executes this movement and the resulting dynamics, combined with clinician input, is used by the algorithm to estimate which of the movement disorders in the database are most probable. This is recursively repeated until a diagnosis can be confidently made. The main contributions of this paper are the formalization of the framework and the addition of the information map to select informative movements. The establishment of the framework provides a foundation for a standardized assessment of movement disorders and future work will aim at testing the framework's efficacy.