Jaejin Hwang

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.

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.

The effect of camera location on observation-based posture estimation

This study used the observation-based method showing images on computer to evaluate angle estimation errors of 8 body segments in 3 motion planes at up to 28 segment angles and 5 camera locations with respect to goniometric measurements. Thirty observers participated in evaluating segment angles. Forearm (9.9°) and thigh (9.5°) had smaller errors than hand (14.0°) and foot had the smallest error (8.7°) due to its narrow range of motion (ROM). Errors were small with camera locations perpendicular to motions in the planes, such as 90° camera location for the flexion and extension of arm (6.3°), forearm (7.9°), thigh (6.5°), and leg (8.1°) in the sagittal plane. Segments had small errors of 3.1°, 4.6°, and 3.8° at segment angles of −90°, 0° and 90°, respectively. Care should be taken when estimating angles by the observation-based method for a specific segment motion and viewing direction is suggested to be perpendicular to the motion plane. Practitioner Summary: Some companies may not allow many cameras or have obstacles for working posture evaluation in the workplace. These study results can be a guideline on proper selection of the number of cameras and their locations for a specific segment and its motion of interest to reduce visual segment angle estimation errors.

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

Abstract 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.

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.

Age and sex differences in ranges of motion and motion patterns.

This study investigated the effects of age and sex on joint ranges of motion (ROMs) and motion patterns. Forty participants performed 18 motions using eight body segments at self-selected speeds. Older subjects showed smaller ROMs than younger subjects for 11 motions; the greatest difference in ROM was 44.9% for eversion/inversion of the foot. Older subjects also required more time than younger subjects to approach the peak angular velocity for six motions. In contrast, sex significantly affected ROMs but not motion patterns. Male subjects exhibited smaller ROMs than female subjects for four motions; the greatest sex-dependent difference in ROM was 29.7% for ulnar/radial deviation of the hand. The age and sex effects depended on the specific segments used and motions performed, possibly because of differences in anatomical structures and frequencies of use of the joints in habitual physical activities between the groups.

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 models 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.

Armrests and back support reduced biomechanical loading in the neck and upper extremities during mobile phone use

Mobile phone use is known to be associated with musculoskeletal pain in the neck and upper extremities because of related physical risk factors, including awkward postures. A chair that provides adequate support (armrests and back support) may reduce biomechanical loading in the neck and shoulder regions. Therefore, we conducted a repeated-measures laboratory study with 20 participants (23 ± 1.9 years; 10 males) to determine whether armrests and back support during mobile phone use reduced head/neck flexion, gravitational moment, and muscle activity in the neck and shoulder regions. The results showed that the chair support (armrests and back support) reduced head/neck flexion (p < 0.001), gravitational moment (p < 0.001), and muscle activity (p < 0.01) in the neck and shoulder regions significantly compared to no chair support. These results indicate that a chair with adequate support can be an effective intervention to reduce the biomechanical exposures and associated muscular pain in the neck and shoulders during mobile phone use.

A Comparison of Performance Between Straight-Line Muscle and Curved Muscle Models

The straight-line muscle biomechanical models of the lumbar spine have been utilized to predict spinal loads to assess the potential risk of work-related injuries. The curved muscle paths have been suggested to realistically simulate muscles’ behavior in complex lumbar motions. However, the effect of curved muscle paths on the modeling performances and spinal loads in the lumbar spine model during complex lifting exertions has not been fully investigated. The objective of this study was to characterize the differences in modeling performances and spinal loads between the conventional straight-line muscle model and the curved muscle model of the lumbar spine. Twelve subjects (6 males and 6 females) participated in this study. Mean values and standard deviations of age, body mass, and height of all subjects were 26.6 (5.3) years, 73.6 (13.3) kg, and 172.7 (5.4) cm, respectively. Electromyographic (EMG) activities with surface electrodes (Motion Lab Systems MA300-XVI, Baton Rouge, Louisiana, USA) were collected over 10 trunk muscles (pair of the latissimus dorsi, erector spinae, rectus abdominis, external oblique, and internal oblique) with 1000 Hz sampling rate. The OptiTrack optical motion capture system (NaturalPoint, Corvallis, OR, USA) with 24 Flex 3 infrared cameras was used to monitor whole body kinematics with 100 Hz sampling rate. A Bertec 4060A force plate (Bertec, Worthington, OH, USA) was used to measure ground reaction forces with 1000 Hz sampling rate. Customized Laboratory software via a National Instruments USB-6225 data acquisition board (National Instruments, Austin, TX, USA) was utilized to collect all signals simultaneously and efficiently run the model. Subjects performed complex lifting tasks by various load weight (9.1kg and 15.9kg), load origins (counterclockwise 90⁰, counterclockwise 45⁰, 0⁰, clockwise 45⁰, and clockwise 90⁰), and load height (mid-calf, mid-thigh, and shoulder). Both curved muscle model and straight-line muscle model were tested under same experiment conditions, respectively. The curved muscle model showed better model fidelity (average coefficient of determination (R2) = 0.83; average absolute error (AAE) = 14.4%) than the straight-line muscle model (R2 = 0.79; AAE = 20.7%), especially in upper levels of the lumbar spine. The curved muscle model showed higher R2 than the straight-line muscle model, and the T12/L1 level showed the biggest difference as 0.1. The curved muscle model had lower AAE than the straight-line muscle model, and the T12/L1 showed the biggest difference as 18%. The curved muscle model generally showed higher compression (up to 640N at T12/L1), lower anterior-posterior shear loads (up to 575N at T12/L1), and lower lateral shear loads (up to 521N at T12/L1) than the straight-line muscle model. The biggest difference in spinal loads between two models (especially in anterior-posterior shear and lateral shear loads) occurred at upper levels of the lumbar spine, which could be related to the amount of muscle curvatures at each spine level. The curved muscle model generally showed higher compression and lower anterior-posterior and lateral shear loads than the straight-line muscle model. It might be partially related to the muscle paths of the erector spinae (major power producing muscle). In curved muscle model, erector spinae was placed more parallel with the lumbar spine curvature than the straight-line muscle model. It could affect the spinal load distributions such as higher compression and lower shears loads in the curved muscle model compared to the straight-line muscle model. In conclusion, the improved performance of the curved muscle model indicated that the curved muscle approach would be advantageous to estimate precise spinal loads in complex lifting jobs compared to the straight-line muscle approach.

A Biologically-Assisted Curved Muscle Model of the Lumbar Spine

Biomechanically-assisted models have been developed to estimate spine tissue loads in vivo and used to assess the potential risk of injuries in workers. However, most biomechanical models represented trunk muscles as straight-lines vectors acting between a muscle origin and insertion. Even though straight-line muscles behaved reasonably well in simple dynamic occupational tasks, this assumption could be problematic in complex multidimensional dynamic tasks that include highly asymmetric or extreme bending postures. Previous efforts at developing curved muscle models were not empirically validated or tested under dynamic loading conditions. Hence, the accuracy of spine tissue load estimations of such models has not been well documented. In this study, a curved muscle representation was developed and validated to overcome this concern. The objective of this study was to investigate the model fidelity of a biologically-assisted curved muscle model during complex dynamic lifting tasks. Twelve subjects (7 males and 5 females) participated in this study. Subjects performed dynamic lifting tasks as a function of load weight, load origin, and load height to simulate complex lifting activities from extreme and highly dynamic postures. The moment matching measures were calculated to evaluate how well model estimated the spinal moment of L5/S1 compared to measured spinal moments in terms of correlation (R2) and average absolute error (AAE). The model demonstrated good repeatability and very good model fidelity between various experimental conditions. The mean and standard deviations of multi-planar R2 were 0.85 (0.07), with 78% of all trials (411/528) having R2 > 0.8. For the multi-planar normalized AAE (%), mean and standard deviations were 12.1% (3.9), with 80% of all trials (425/528) having AAE < 15%. The results of this study indicated that curved muscle representation in the biologically-assisted model was an empirically reasonable approach to estimate accurate spine tissue loads of the lumbar spine during complex occupational circumstances.