Disorientation effects, circulating small ribonucleic acid, and genetic susceptibility on static postural stability.

Background: Motion Sickness increases risk of performance deficits and safety of flight concerns. The etiology of motion sickness is poorly understood. Here, we attempted to quantify the physiological effects of motion sickness on static balance and determine the genetic predictors associated with these effects. Methods: 16 subjects underwent a disorientation stimulus to induce motion sickness. Motion sickness susceptibility was identified using the Motion Sickness Susceptibility Questionnaire. Postural balance outcomes were measured using two tasks, and small ribonucleic acid profiles were assessed with blood draws before motion sickness stimulus. Differences in postural sway before and after the stimulus as well as effect modification of susceptibility were assessed. A random forest followed by regression tree analysis was constructed for each postural sway variable to determine top genetic and covariate predictors. Findings: Significant differences existed in mean postural balance responses between before and after stimulus. Individuals with longer stimulus survival experienced a greater (but insignificant) perception of sway, even if not displaying increased sway for all conditions. Circulation small ribonucleic acids were differentially expressed between individuals with long and short stimulus survival, many of these microRNA have purported targets in genes related to vestibular disorders. Interpretation: We found motion sickness produces transient motor dysfunction in a healthy military population. Small ribonucleic acids were differentially expressed between subjects with long and short stimulus survival times.

Motion sickness decreases low back function and changes gene expression in military aircrew.

BACKGROUND: Motion sickness and low back disorders are prevalent and debilitating conditions that affect the health, performance, and operational effectiveness of military aircrews. This study explored the effects of a motion sickness stimulus on biomechanical and genetic factors that could potentially be involved in the causal pathways for both disorders. METHODS: Subjects recruited from a military population were exposed to either a mild (n = 12) or aggressive (n = 16) motion sickness stimulus in a Neuro-Otologic Test Center. The independent variable of interest was the motion sickness stimulus exposure (before vs. after), though differences between mild and aggressive stimuli were also assessed. Dependent measures for the study included motion sickness exposure duration, biomechanical variables (postural stability, gait function, low back function, lumbar spine loading), and gene expression. FINDINGS: Seven of twelve subjects experiencing the mild motion sickness stimulus endured the full 30 min in the NOTC, whereas subjects lasted an average of 13.2 (SD 5.0) minutes in the NOTC with the aggressive motion sickness stimulus. Mild motion sickness exposure led to a significant decrease in the postural stability measure of sway area, though the aggressive motion sickness exposure led to a statistically significant increase in sway area. Both stimuli led to decreases in low back function, though the decrease was only statistically significant for the mild protocol. Both stimuli also led to significant changes in gene expression. INTERPRETATION: Motion sickness may alter standing balance, decrease low back function, and lead to changes in the expression of genes with roles in osteogenesis, myogenesis, development of brain lymphatics, inflammation, neuropathic pain, and more. These results may provide preliminary evidence for a link between motion sickness and low back disorders.

Differences in lumbar spine measures as a function of MRI posture in low back pain patients and its clinical implications.

STUDY DESIGN: Observational Study. OBJECTIVE: The primary objective was to determine if there were differences in spine structure measures between experimental postures and standard supine posture MRIs. METHODS: Thirty-four low back pain patients were included. MRI was taken in 6 experimental postures. The dependent measures includes sagittal view anterior (ADH), middle and posterior disc heights, thecal sac width, left/right foraminal height (FH). In the axial view: disc width, left and right foraminal height. Measures were done L3/L4, L4/L5 and L5/S1. Each subject served as their own control. Spine measurements in the experimental posture were compared to the same measures in the standard supine posture. RESULTS: 94% inter-observer reliability was seen. In the sagittal and axial view, 55 of the 108 and 11 of the 18 measures were significantly different. In sagittal view: a) ADH was significantly smaller in the sitting flexed posture by 2.50 mm ± 0.63 compared to the supine posture; b) ADH in sitting neutral posture was significantly smaller than the standard posture by 1.97 mm ± 0.86; c) sitting flexed posture showed that bilateral FH measures were significantly different; d) Bilateral FH was larger in the sitting neutral posture compared to the standard supine posture by 0.87 mm ± 0.17. CONCLUSIONS: This research quantifies the differences in spine structure measures that occur in various experimental postures. The additional information gathered from an upright MRI may correlate with symptoms leading to an accurate diagnosis and assist in future spine research.

Dynamic Joint Motions in Occupational Environments as Indicators of Potential Musculoskeletal Injury Risk.

The objective of this study was to test the feasibility of using a pair of wearable inertial measurement unit (IMU) sensors to accurately capture dynamic joint motion data during simulated occupational conditions. Eleven subjects (5 males and 6 females) performed repetitive neck, low-back, and shoulder motions simulating low- and high-difficulty occupational tasks in a laboratory setting. Kinematics for each of the 3 joints were measured via IMU sensors in addition to a "gold standard" passive marker optical motion capture system. The IMU accuracy was benchmarked relative to the optical motion capture system, and IMU sensitivity to low- and high-difficulty tasks was evaluated. The accuracy of the IMU sensors was found to be very good on average, but significant positional drift was observed in some trials. In addition, IMU measurements were shown to be sensitive to differences in task difficulty in all 3 joints (P < .05). These results demonstrate the feasibility for using wearable IMU sensors to capture kinematic exposures as potential indicators of occupational injury risk. Velocities and accelerations demonstrate the most potential for developing risk metrics since they are sensitive to task difficulty and less sensitive to drift than rotational position measurements.

An electromyography-assisted biomechanical cervical spine model: Model development and validation.

BACKGROUND: In spite of the prevalence of occupational neck disorders as a result of work force fluctuating from industry to sedentary office work, most cervical spine computational models are not capable of simulating occupational and daily living activities whereas majority of cervical spine models specialized to simulate crash and impact scenarios. Therefore, estimating spine tissue loads accurately to quantify the risk of neck disorders in occupational environments within those models is not possible due to the lack of muscle models, dynamic simulation and passive spine structures. METHODS: In this effort the structure, logic, and validation process of an electromyography-assisted cervical biomechanical model that is capable of estimating neck loading under three-dimensional complex motions is described. The developed model was designed to simulate complex dynamic motions similar to work place exposure. Curved muscle geometry, personalized muscle force parameters, and separate passive and (electromyography-driven) active muscle force components are implemented in this model. FINDINGS: Calibration algorithms were able to reverse-engineer personalized muscle properties to calculate active and passive muscle forces of each individual. INTERPRETATION: This electromyography-assisted cervical spine model with curved muscle model is capable to accurately predict spinal tissue loads during isometric and dynamic head and neck activities. Personalized active and passive muscle force algorithms will help to more robustly investigate person-specific muscle forces and spinal tissue loads.

One versus two-handed lifting and lowering: lumbar spine loads and recommended one-handed limits protecting the lower back.

The objectives of this study were to quantify loads imposed upon the lumbar spine while lifting/lowering with one versus two hands and to create guidelines for one-handed lifting/lowering that are protective of the lower back. Thirty subjects (15 male, 15 female) performed one- and two-handed exertions in a laboratory, lifting from/lowering to 18 lift origins/destinations using medicine balls of varying masses. An electromyography-assisted model predicted peak spinal loads, which were related to tissue tolerance limits to create recommended weight limits. Compared to two-handed exertions, one-handed exertions resulted in decreased spinal compression and A/P shear loading (p < 0.001) but increased lateral shear (p < 0.001). Effects were likely driven by altered moment exposures attributable to altered torso kinematics. Differences between spinal loads for one- versus two-handed exertions were influenced by asymmetry (p < 0.001) and amplified at lower lift origin/destination heights, lower object masses and larger horizontal distances between the body and the load (p < 0.001). Practitioner summary: A biomechanical model was utilised to compare spinal loading for one versus two-handed lifting/lowering. Spinal loads in compression and A/P shear were reduced for one-handed relative to two-handed exertions. As current lifting guidelines cannot appropriately be applied to one-handed scenarios, one-handed weight limits protecting the lower back are presented herein. Abbreviations: LBD: low back disorder, EMG: electromyography, A/P: anterior/posterior, MVC: maximum voluntary contraction.

Spinal loading and lift style in confined vertical space.

The objective of this study was to investigate biomechanical loads on the lumbar spine as a function of working in a confined vertical space, consistent with baggage handling inside the baggage compartment of an airplane. Ten male subjects performed baggage handling tasks using confined (kneeling, sitting) and unconfined (stooping) lifting styles. Dependent measures of torso flexion and three-dimensional spinal loads were assessed with an electromyography-driven biomechanical model. Lifting exertions typical to airline baggage handling posed significant risk to the lumbar spine, regardless of lifting style. Statistically significant differences attributable to lift style (stooping, kneeling, sitting) were not observed for peak compressive, lateral shear, or resultant spinal loads, but lifting while kneeling decreased anterior/posterior (A/P) shear spinal loads relative to stooping (p = 0.02). Collectively, kneeling offers the greatest benefit when lifting in confined spaces because of the ability to keep the torso upright, subsequently reducing shear forces on the lumbar spine.

Impact of two postural assist exoskeletons on biomechanical loading of the lumbar spine.

This study evaluated loading on the low back while wearing two commercially available postural assist exoskeletons. Ten male subjects lifted a box from multiple lift origins (combinations of vertical height and asymmetry) to a common destination using a squatting lifting technique with and without the use of either exoskeleton. Dependent measures included subject kinematics, moment arms between the torso or weight being lifted and the lumbar spine, and spinal loads as predicted by an electromyography-driven spine model. One of the exoskeletons tested (StrongArm Technologies™ FLx) reduced peak torso flexion at the shin lift origin, but differences in moment arms or spinal loads attributable to either of the interventions were not observed. Thus, industrial exoskeletons designed to control posture may not be beneficial in reducing biomechanical loads on the lumbar spine. Interventions altering the external manual materials handling environment (lift origin, load weight) may be more appropriate when implementation is fesible.

Effectiveness of a vacuum lifting system in reducing spinal load during airline baggage handling.

Information on spinal loading for using lift assist systems for airport baggage handling is lacking. We conducted a laboratory study to evaluate a vacuum lift system for reducing lumbar spinal loads during baggage loading/unloading tasks. Ten subjects performed the tasks using the industry average baggage weight of 14.5 kg on a typical two-shelved baggage cart with or without using the lift system (i.e. lifting technique). Repeated measures analysis of variance (2 tasks × 2 shelf heights x 2 techniques) was used. Spinal loads were estimated by an electromyography-driven biomechanical model. On average, the vacuum lift system reduced spinal compressive forces on the lumbar spine by 39% and below the 3400 N damage threshold. The system also resulted in a 25% reduction in the anterior-posterior shear force at the L5/S1 inferior endplate level. This study provides evidence for the potential to reduce spinal loads when using a vacuum lift system.

Biomechanically determined hand force limits protecting the low back during occupational pushing and pulling tasks.

Though biomechanically determined guidelines exist for lifting, existing recommendations for pushing and pulling were developed using a psychophysical approach. The current study aimed to establish objective hand force limits based on the results of a biomechanical assessment of the forces on the lumbar spine during occupational pushing and pulling activities. Sixty-two subjects performed pushing and pulling tasks in a laboratory setting. An electromyography-assisted biomechanical model estimated spinal loads, while hand force and turning torque were measured via hand transducers. Mixed modelling techniques correlated spinal load with hand force or torque throughout a wide range of exposures in order to develop biomechanically determined hand force and torque limits. Exertion type, exertion direction, handle height and their interactions significantly influenced dependent measures of spinal load, hand force and turning torque. The biomechanically determined guidelines presented herein are up to 30% lower than comparable psychophysically derived limits and particularly more protective for straight pushing. Practitioner Summary: This study utilises a biomechanical model to develop objective biomechanically determined push/pull risk limits assessed via hand forces and turning torque. These limits can be up to 30% lower than existing psychophysically determined pushing and pulling recommendations. Practitioners should consider implementing these guidelines in both risk assessment and workplace design moving forward.

Development and testing of a moment-based coactivation index to assess complex dynamic tasks for the lumbar spine.

BACKGROUND: Many methods exist to describe coactivation between muscles. However, most methods have limited capability in the assessment of coactivation during complex dynamic tasks for multi-muscle systems such as the lumbar spine. The ability to assess coactivation is important for the understanding of neuromuscular inefficiency. In the context of this manuscript, inefficiency is defined as the effort or level of coactivation beyond what may be necessary to accomplish a task (e.g., muscle guarding during postural stabilization). The objectives of this study were to describe the development of an index to assess coactivity for the lumbar spine and test its ability to differentiate between various complex dynamic tasks. METHODS: The development of the coactivation index involved the continuous agonist/antagonist classification of moment contributions for the power-producing muscles of the torso. Different tasks were employed to test the range of the index including lifting, pushing, and Valsalva. FINDINGS: The index appeared to be sensitive to conditions where higher coactivation would be expected. These conditions of higher coactivation included tasks involving higher degrees of control. Precision placement tasks required about 20% more coactivation than tasks not requiring precision, lifting at chest height required approximately twice the coactivation as mid-thigh height, and pushing fast speeds with turning also required at least twice the level of coactivity as slow or preferred speeds. INTERPRETATION: Overall, this novel coactivation index could be utilized to describe the neuromuscular effort in the lumbar spine for tasks requiring different degrees of postural control.

Accuracy map of an optical motion capture system with 42 or 21 cameras in a large measurement volume.

Optical motion capture is commonly used in biomechanics to measure human kinematics. However, no studies have yet examined the accuracy of optical motion capture in a large capture volume (>100m3), or how accuracy varies from the center to the extreme edges of the capture volume. This study measured the dynamic 3D errors of an optical motion capture system composed of 42 OptiTrack Prime 41 cameras (capture volume of 135m3) by comparing the motion of a single marker to the motion reported by a ThorLabs linear motion stage. After spline interpolating the data, it was found that 97% of the capture area had error below 200µm. When the same analysis was performed using only half (21) of the cameras, 91% of the capture area was below 200µm of error. The only locations that exceeded this threshold were at the extreme edges of the capture area, and no location had a mean error exceeding 1mm. When measuring human kinematics with skin-mounted markers, uncertainty of marker placement relative to underlying skeletal features and soft tissue artifact produce errors that are orders of magnitude larger than the errors attributed to the camera system itself. Therefore, the accuracy of this OptiTrack optical motion capture system was found to be more than sufficient for measuring full-body human kinematics with skin-mounted markers in a large capture volume (>100m3).

Validation of a personalized curved muscle model of the lumbar spine during complex dynamic exertions.

Previous curved muscle models have typically examined their robustness only under simple, single-plane static exertions. In addition, the empirical validation of curved muscle models through an entire lumbar spine has not been fully realized. The objective of this study was to empirically validate a personalized biologically-assisted curved muscle model during complex dynamic exertions. Twelve subjects performed a variety of complex lifting tasks as a function of load weight, load origin, and load height. Both a personalized curved muscle model as well as a straight-line muscle model were used to evaluate the model's fidelity and prediction of three-dimensional spine tissue loads under different lifting conditions. The curved muscle model showed better model performance and different spinal loading patterns through an entire lumbar spine compared to the straight-line muscle model. The curved muscle model generally showed good fidelity regardless of lifting condition. The majority of the 600 lifting tasks resulted in a coefficient of determination (R2) greater than 0.8 with an average of 0.83, and the average absolute error less than 15% between measured and predicted dynamic spinal moments. As expected, increased load and asymmetry were generally found to significantly increase spinal loads, demonstrating the ability of the model to differentiate between experimental conditions. A curved muscle model would be useful to estimate precise spine tissue loads under realistic circumstances. This precise assessment tool could aid in understanding biomechanical causal pathways for low back pain.

Curved muscles in biomechanical models of the spine: a systematic literature review.

Early biomechanical spine models represented the trunk muscles as straight-line approximations. Later models have endeavoured to accurately represent muscle curvature around the torso. However, only a few studies have systematically examined various techniques and the logic underlying curved muscle models. The objective of this review was to systematically categorise curved muscle representation techniques and compare the underlying logic in biomechanical models of the spine. Thirty-five studies met our selection criteria. The most common technique of curved muscle path was the 'via-point' method. Curved muscle geometry was commonly developed from MRI/CT database and cadaveric dissections, and optimisation/inverse dynamics models were typically used to estimate muscle forces. Several models have attempted to validate their results by comparing their approach with previous studies, but it could not validate of specific tasks. For future needs, personalised muscle geometry, and person- or task-specific validation of curved muscle models would be necessary to improve model fidelity. Practitioner Summary: The logic underlying the curved muscle representations in spine models is still poorly understood. This literature review systematically categorised different approaches and evaluated their underlying logic. The findings could direct future development of curved muscle models to have a better understanding of the biomechanical causal pathways of spine disorders.

A biologically-assisted curved muscle model of the lumbar spine: Model validation.

BACKGROUND: Biomechanical models have been developed to predict spinal loads in vivo to assess potential risk of injury in workplaces. Most models represent trunk muscles with straight-lines. Even though straight-line muscles behave reasonably well in simple exertions, they could be less reliable during complex dynamic exertions. A curved muscle representation was developed to overcome this issue. However, most curved muscle models have not been validated during dynamic exertions. Thus, the objective of this study was to investigate the fidelity of a curved muscle model during complex dynamic lifting tasks, and to investigate the changes in spine tissue loads. METHODS: Twelve subjects (7 males and 5 females) participated in this study. Subjects performed lifting tasks as a function of load weight, load origin, and load height to simulate complex exertions. Moment matching measures were recorded to evaluate how well the model predicted spinal moments compared to measured spinal moments from T12/L1 to L5/S1 levels. FINDINGS: The biologically-assisted curved muscle model demonstrated better model performance than the straight-line muscle model between various experimental conditions. In general, the curved muscle model predicted at least 80% of the variability in spinal moments, and less than 15% of average absolute error across levels. The model predicted that the compression and anterior-posterior shear load significantly increased as trunk flexion increased, whereas the lateral shear load significantly increased as trunk twisted more asymmetric during lifting tasks. INTERPRETATION: A curved muscle representation in a biologically-assisted model is an empirically reasonable approach to accurately predict spinal moments and spinal tissue loads of the lumbar spine.

A biologically-assisted curved muscle model of the lumbar spine: Model structure.

BACKGROUND: Biomechanical models have been developed to assess the spine tissue loads of individuals. However, most models have assumed trunk muscle lines of action as straight-lines, which might be less reliable during occupational tasks that require complex lumbar motions. The objective of this study was to describe the model structure and underlying logic of a biologically-assisted curved muscle model of the lumbar spine. METHODS: The developed model structure including curved muscle geometry, separation of active and passive muscle forces, and personalization of muscle properties was described. An example of the model procedure including data collection, personalization, and data evaluation was also illustrated. FINDINGS: Three-dimensional curved muscle geometry was developed based on a predictive model using magnetic resonance imaging and anthropometric measures to personalize the model for each individual. Calibration algorithms were able to reverse-engineer personalized muscle properties to calculate active and passive muscle forces of each individual. INTERPRETATION: This biologically-assisted curved muscle model will significantly increase the accuracy of spinal tissue load predictions for the entire lumbar spine during complex dynamic occupational tasks. Personalized active and passive muscle force algorithms will help to more robustly investigate person-specific muscle forces and spinal tissue loads.

Prediction of magnetic resonance imaging-derived trunk muscle geometry with application to spine biomechanical modeling.

BACKGROUND: Accurate geometry of the trunk musculature is essential for reliably estimating spinal loads in biomechanical models. Currently, many models employ straight muscle path assumptions that yield far less accurate tissue loads, particularly in extreme postures. Precise muscle moment-arms and physiological cross-sectional areas are important when incorporating curved muscle geometry in biomechanical models. The objective of this study was to develop a predictive model of moment arms and physiological cross-sectional areas of trunk musculature at multiple levels in the thoracic/lumbar spine as a function of anthropometric measures. METHODS: Based on magnetic resonance imaging data from thirty subjects (10 male and 20 female) reported in a previous study, a polynomial regression analysis was conducted to estimate the muscle moment-arms and physiological cross-sectional areas of trunk muscles through thoracic/lumbar spine as a function of vertebral level, gender, age, height, and body mass. FINDINGS: Gender, body mass, and height were the best predictors of muscle moment-arms and physiological cross-sectional areas. The predictability of muscle parameters tended to be higher for erector spinae than other muscles. Most muscles showed a curved muscle path along the thoracic/lumbar spine. INTERPRETATION: The polynomial regression model of the muscle geometry in this study generally showed good predictability compared to previous reports. The predictive model in this study will be useful to develop personalized biomechanical models that incorporate curved trunk muscle geometries.

An EMG-assisted model calibration technique that does not require MVCs.

As personalized biologically-assisted models of the spine have evolved, the normalization of raw electromyographic (EMG) signals has become increasingly important. The traditional method of normalizing myoelectric signals, relative to measured maximum voluntary contractions (MVCs), is susceptible to error and is problematic for evaluating symptomatic low back pain (LBP) patients. Additionally, efforts to circumvent MVCs have not been validated during complex free-dynamic exertions. Therefore, the objective of this study was to develop an MVC-independent biologically-assisted model calibration technique that overcomes the limitations of previous normalization efforts, and to validate this technique over a variety of complex free-dynamic conditions including symmetrical and asymmetrical lifting. The newly developed technique (non-MVC) eliminates the need to collect MVCs by combining gain (maximum strength per unit area) and MVC into a single muscle property (gain ratio) that can be determined during model calibration. Ten subjects (five male, five female) were evaluated to compare gain ratio prediction variability, spinal load predictions, and model fidelity between the new non-MVC and established MVC-based model calibration techniques. The new non-MVC model calibration technique demonstrated at least as low gain ratio prediction variability, similar spinal loads, and similar model fidelity when compared to the MVC-based technique, indicating that it is a valid alternative to traditional MVC-based EMG normalization. Spinal loading for individuals who are unwilling or unable to produce reliable MVCs can now be evaluated. In particular, this technique will be valuable for evaluating symptomatic LBP patients, which may provide significant insight into the underlying nature of the LBP disorder.