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.

Reliability of a Wearable Motion Tracking System for the Clinical Evaluation of a Dynamic Cervical Spine Function.

Neck pain is a common cause of disability worldwide. Lack of objective tools to quantify an individual's functional disability results in the widespread use of subjective assessments to measure the limitations in spine function and the response to interventions. This study assessed the reliability of the quantifying neck function using a wearable cervical motion tracking system. Three novice raters recorded the neck motion assessments on 20 volunteers using the device. Kinematic features from the signals in all three anatomical planes were extracted and used as inputs to repeated measures and mixed-effects regression models to calculate the intraclass correlation coefficients (ICCs). Cervical spine-specific kinematic features indicated good and excellent inter-rater and intra-rater reliability for the most part. For intra-rater reliability, the ICC values varied from 0.85 to 0.95, and for inter-rater reliability, they ranged from 0.7 to 0.89. Overall, velocity measures proved to be more reliable compared to other kinematic features. This technique is a trustworthy tool for evaluating neck function objectively. This study showed the potential for cervical spine-specific kinematic measurements to deliver repeatable and reliable metrics to evaluate clinical performance at any time points.

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.

Reliability of a Wearable Motion System for Clinical Evaluation of Dynamic Lumbar Spine Function.

Background: Low back pain is the leading cause of disability worldwide. Subjective assessments are often used to assess extent of functional limitations and treatment response. However, these measures have poor sensitivity and are influenced by the patient's perception of their condition. Currently, there are no objective tools to effectively assess the extent of an individual's functional disability and inform clinical decision-making. Objective: The purpose of this study was to evaluate the reliability of a wearable motion system based on Inertial Measurement Unit (IMU) sensors for use in quantifying low back function. Methods: Low back motion assessments were conducted by 3 novice raters on 20 participants using an IMU-based motion system. These assessments were conducted over 3 days with 2 days of rest in between tests. A total of 37 kinematic parameters were extracted from the low back motion assessment in all three anatomical planes. Intra-rater and inter-rater reliability were assessed using Intraclass Correlation Coefficients (ICCs) calculated from repeated measures, mixed-effects regression models. Results: Lumbar spine-specific kinematic parameters showed moderate to excellent reliability across all kinematic parameters. The ICC values ranged between 0.84-0.93 for intra-rater reliability and 0.66 - 0.83 for inter-rater reliability. In particular, velocity measures showed higher reliabilities than other kinematic variables. Conclusion: The IMU-based wearable motion system is a valid and reliable tool to objectively assess low back function. This study demonstrated that lumbar spine-specific kinematic metrics have the potential to provide good, repeatable metrics to assess clinical function over time.

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.

An Exploratory Electromyography-Based Coactivation Index for the Cervical Spine.

Objective Develop a coactivation index for the neck and test its effectiveness with complex dynamic head motions. Background Studies describing coactivation for the cervical spine are sparse in the literature. Of those in existence, they were either limited to a priori definitions of agonist/antagonist activity that limited the testing to sagittal and lateral planes or consisted of isometric exertions. Multiplanar movements would allow for a more realistic understanding of naturalistic movements in the cervical spine and propensity for neck pain. However, a gap in the literature exists in which a method to describe coactivation during complex dynamic motions does not exist for the cervical spine. Methods An electromyography-based coactivation index was developed for the cervical spine based on previously tested methodology used on the lumbar spine without a high-end model and tested using a series of different postures and speeds. Results Complex motions involving twisting (i.e., flexion and twisting) and higher speed had higher magnitudes of coactivation than uniplanar motions in the sagittal or lateral plane, which was expected. The coupled motion of flexion and twisting showed four to five times higher coactivation than uniplanar (sagittal or lateral) movements. Conclusion The coactivation index developed accommodates multiplanar, naturalistic movements. Testing of the index showed that motions requiring higher degrees of head control had higher effort due to coactivation, which was expected. Application Overall, this coactivation index may be utilized to understand the neuromuscular effort of various tasks in the cervical spine.

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 of a lumbar EMG-based coactivation index for the assessment of complex dynamic tasks.

The objective of this study was to develop and test an EMG-based coactivation index and compare it to a coactivation index defined by a biologically assisted lumbar spine model to differentiate between tasks. The purpose was to provide a universal approach to assess coactivation of a multi-muscle system when a computational model is not accessible. The EMG-based index developed utilised anthropometric-defined muscle characteristics driven by torso kinematics and EMG. Muscles were classified as agonists/antagonists based upon 'simulated' moments of the muscles relative to the total 'simulated' moment. Different tasks were used to test the range of the index including lifting, pushing and Valsalva. Results showed that the EMG-based index was comparable to the index defined by a biologically assisted model (r2 = 0.78). Overall, the EMG-based index provides a universal, usable method to assess the neuromuscular effort associated with coactivation for complex dynamic tasks when the benefit of a biomechanical model is not available. Practitioner Summary: A universal coactivation index for the lumbar spine was developed to assess complex dynamic tasks. This method was validated relative to a model-based index for use when a high-end computational model is not available. Its simplicity allows for fewer inputs and usability for assessment of task ergonomics and rehabilitation.

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).

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.