Wearable motion-based platform for functional spine health assessment.

INTRODUCTION: Low back pain is a significant burden to society and the lack of reliable outcome measures, combined with a prevailing inability to quantify the biopsychosocial elements implicated in the disease, impedes clinical decision-making and distorts treatment efficacy. This paper aims to validate the utility of a biopsychosocial spine platform to provide standardized wearable sensor-derived functional motion assessments to assess spine function and differentiate between healthy controls and patients. Secondarily, we explored the correlation between these motion features and subjective biopsychosocial measures. METHODS: An observational study was conducted on healthy controls (n=50) and patients with low back pain (n=50) to validate platform utility. The platform was used to conduct functional assessments along with patient-reported outcome assessments to holistically document cohort differences. Our primary outcomes were motion features; and our secondary outcomes were biopsychosocial measures (pain, function, etc). RESULTS: Our results demonstrated statistically significant differences in motion features between healthy and patient cohorts across anatomical planes. Importantly, we found velocity and acceleration in the axial plane showed the largest difference, with healthy controls having 49.7% and 55.7% higher values, respectively, than patients. In addition, we found significant correlations between motion features and biopsychosocial measures for pain, physical function and social role only. CONCLUSIONS: Our study validated the use of wearable sensor-derived functional motion metrics in differentiating healthy controls and patients. Collectively, this technology has the potential to facilitate holistic biopsychosocial evaluations to enhance spine care and improve patient outcomes. TRIAL REGISTRATION NUMBER: NCT05776771.

Computational lumbar spine models: A literature review.

BACKGROUND: Computational spine models of various types have been employed to understand spine function, assess the risk that different activities pose to the spine, and evaluate techniques to prevent injury. The areas in which these models are applied has expanded greatly, potentially beyond the appropriate scope of each, given their capabilities. A comprehensive understanding of the components of these models provides insight into their current capabilities and limitations. METHODS: The objective of this review was to provide a critical assessment of the different characteristics of model elements employed across the spectrum of lumbar spine modeling and in newer combined methodologies to help better evaluate existing studies and delineate areas for future research and refinement. FINDINGS: A total of 155 studies met selection criteria and were included in this review. Most current studies use either highly detailed Finite Element models or simpler Musculoskeletal models driven with in vivo data. Many models feature significant geometric or loading simplifications that limit their realism and validity. Frequently, studies only create a single model and thus can't account for the impact of subject variability. The lack of model representation for certain subject cohorts leaves significant gaps in spine knowledge. Combining features from both types of modeling could result in more accurate and predictive models. INTERPRETATION: Development of integrated models combining elements from different model types in a framework that enables the evaluation of larger populations of subjects could address existing voids and enable more realistic representation of the biomechanics of the lumbar spine.

A physiological and biomechanical investigation of three passive upper-extremity exoskeletons during simulated overhead work.

The objective of this study was to evaluate three passive upper-extremity exoskeletons relative to a control condition. Twelve subjects performed an hour-long, simulated occupational task in a laboratory setting. Independent measures of exoskeleton, exertion height (overhead, head height), time, and their interactions were assessed. Dependent measures included changes in tissue oxygenation (ΔTSI) in the anterior deltoid and middle trapezius, peak resultant lumbar spine loading, and subjective discomfort in various body regions. A statistically significant reduction in ΔTSI between exoskeleton and control was only observed in one instance. Additionally, neither increases in spinal loading nor increases in subjective discomfort ratings were observed for any of the exoskeletons. Ultimately, the exoskeletons offered little to no physiological benefit for the conditions tested. However, the experimental task was not highly fatiguing to the subjects, denoted by low ΔTSI values across conditions. Results may vary for tasks requiring constant arm elevation or higher force demands. Practitioner summary This study quantified the benefits of upper-extremity exoskeletons using NIRS, complementary to prior studies using EMG. The exoskeletons offered little to no physiological benefit for the conditions tested. However, the experimental task was not highly fatiguing, and results may vary for an experimental task with greater demand on the shoulders. Abbreviations: WMSD: work-related musculoskeletal disorder; EMG: electromyography; NIRS: near-infrared spectroscopy; NIR: near-infrared; Hb: haemoglobin; Mb: myoglobin; TSI: tissue saturation index; ATT: adipose tissue thickness.

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.

Biomechanical musculoskeletal models of the cervical spine: A systematic literature review.

BACKGROUND: As the work load has been shifting from heavy manufacturing to office work, neck disorders are increasing. However, most of the current cervical spine biomechanical models were created to simulate crash situations. Therefore, the biomechanics of cervical spine during daily living and occupational activities remain unknown. In this effort, cervical spine biomechanical models were systematically reviewed based upon different features including approach, biomechanical properties, and validation methods. METHODS: The objective of this review was to systematically categorize cervical spine models and compare the underlying logic in order to identify voids in the literature. FINDINGS: Twenty-two models met our selection criteria and revealed several trends: 1) The multi-body dynamics modeling approach, equipped for simulating impact situations were the most common technique; 2) Straight muscle lines of action, inverse dynamic/optimization muscle force calculation, Hill-type muscle model with only active component were typically used in the majority of neck models; and 3) Several models have attempted to validate their results by comparing their approach with previous studies, but mostly were unable to provide task-specific validation. INTERPRETATION: EMG-driven dynamic model for simulating occupational activities, with accurate muscle geometry and force representation, and person- or task-specific validation of the model would be necessary to improve model fidelity.

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.

Application of MR-derived cross-sectional guideline of cervical spine muscles to validate neck surface electromyography placement.

The importance of surface-EMG placement for development and interpretation of EMG-assisted biomechanical models is well established. Since MR has become a reliable noninvasive cervical spine musculoskeletal diagnostic tool, this investigation attempted to illustrate the anatomical relationships of individual cervical spine muscles with their paired surface-EMG electrodes. The secondary purpose of this investigation was to provide an MR cross-sectional pictorial and descriptive guideline of the cervical spine musculature. MR scans were performed on a healthy adult male subject from skull to manubrium of the sternum. Prior to scanning, MR safe markers were placed over neck muscles following surface EMG placement recommendations. Twenty-three neck muscles were traced manually in each of 267 scan slices. 3-D models of the neck musculoskeletal structure were constructed to aid with understanding the complex anatomy of the region as well as to identify correct EMG electrode locations and to identify muscles' curved lines-of-action. 3D models of the MR-safe markers were constructed relative to the target muscles. Based on the findings of this study, muscle palpation and bony landmarks can be used to effectively identify appropriate surface EMG electrode locations to record upper trapezius, middle trapezius, semispinalis capitis, splenius capitis, levator scapulae, scalenus, sternocleidomastoid and hyoid muscles activities.

Biomechanical evaluation of exoskeleton use on loading of the lumbar spine.

The objective of this study was to investigate biomechanical loading to the low back as a result of wearing an exoskeletal intervention designed to assist in occupational work. Twelve subjects simulated the use of two powered hand tools with and without the use of a Steadicam vest with an articulation tool support arm in a laboratory environment. Dependent measures of peak and mean muscle forces in ten trunk muscles and peak and mean spinal loads were examined utilizing a dynamic electromyography-assisted spine model. The exoskeletal device increased both peak and mean muscle forces in the torso extensor muscles (p < 0.001). Peak and mean compressive spinal loads were also increased up to 52.5% and 56.8%, respectively, for the exoskeleton condition relative to the control condition (p < 0.001). The results of this study highlight the need to design exoskeletal interventions while anticipating how mechanical loads might be shifted or transferred with their use.

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.

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.

Objective classification of vehicle seat discomfort.

The objective of this study was to identify how physiological measures relate to self-reported vehicle seating discomfort. Twelve subjects of varied anthropometric characteristics were enrolled in the study. Subjects sat in two seats over a 2-h period and were evaluated via three physiological measures (near-infrared spectroscopy, electromyography and pressure mapping) yielding six testing sessions. Subjective discomfort surveys were recorded before and after each session for nine regions of the body. Conditional classification discomfort models were developed through dichotomised physiological responses and anthropometry to predict subjective discomfort in specific body locations. Models revealed that subjects taller than 171 cm with reduced blood oxygenation in the biceps femoris or constant, low-level muscle activity in the trapezius tended to report discomfort in the lower extremities or neck, respectively. Subjects weighing less than 58 kg with reduced blood oxygenation in the biceps femoris or unevenly distributed pressure patterns tended to report discomfort in the buttocks. The sensitivities and specificities of cross-validated models ranged between 0.69 and 1.00.

Addressing methodological and ethical challenges of qualitative health research on persons with schizophrenia and bipolar disorder.

Qualitative studies of persons with schizophrenia and bipolar disorder may affect clinical practice and social policy. However, methodological and ethical challenges may present during studies of persons with these specific mental illnesses. The purpose of this paper is to increase transparency about how researchers addressed these challenges during a recent grounded theory study about engagement in primary care. As the researchers addressed the challenges, they increased understanding about persons with schizophrenia and bipolar disorder. They also gained insight about the challenges of studying persons with these specific mental illnesses and about the rigor and credibility of qualitative methods.

Comparison of the accuracy of Biomet 3i Encode Robocast Technology and conventional implant impression techniques.

PURPOSE: To compare the accuracy of implant master casts fabricated using Robocast Technology (Biomet 3i) with that of master casts fabricated using traditional transfer (closed-tray) and pick-up (open-tray) techniques. MATERIALS AND METHODS: A stereolithographic replica of a Kennedy Class I human mandible was fabricated for use as the master model. Implants were placed into both posterior quadrants (both second premolars and second molars) and set parallel (P) on one side and divergent (nonparallel, NP) on the opposite side. Impressions were made of the master model (patient replica model) with Encode Healing Abutments, open-tray, and closed-tray impression copings. Identical metallic spheres were placed onto each implant analog in the stone master casts, and the casts/spheres were scanned using a digital scanner. Measurements were made between the center points of the spheres and compared to the master model. Data were divided into P, NP, and individual sites, and the differences were analyzed statistically (α = .05). RESULTS: Encode master casts were less accurate than the open-tray casts in NP sites. Encode master casts were less accurate than the open-tray and closed-tray casts in P sites. NP sites demonstrated less accuracy than P sites within the Encode group. Encode master casts were less accurate than the open- and closed-tray casts at the mandibular right second premolar site. The mandibular left second premolar was less accurate than the mandibular right second molar in the Encode group. CONCLUSIONS: Within the limitations of this lab-based study and analysis, the Encode technique resulted in master casts that were less accurate than master casts made from traditional open- and closed-tray impression techniques. Further research is necessary before specific clinical judgments can be made.

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.