Trunk stiffness decreases and trunk damping increases with experimental low back pain

Comparative evaluation of different spinal stability metrics

Direct in vivo measurements of spinal stability are not possible, leaving computational estimations (such as dynamic time series and structural analyses) as the feasible option. However, differences between different stability assessment approaches and metrics remain unclear. To explore this, we asked 32 participants to perform 35 cycles of repetitive lifts with and without load (4/2.6 kg for males/females). EMG signals and 3D kinematics were collected via 12 surface electrodes and 17 inertial sensors, and three dynamical stability measures were computed: short and long temporal and conventional maximum Lyapunov exponents (LyE) and maximum Floquet multipliers (FM). A dynamic subject-specific EMG-assisted musculoskeletal model computed four structural stability measures (critical muscle stiffness coefficient at which spine becomes unstable, average spine stiffness, minimum and geometric average of Hessian matrix eigenvalues). Across cycles, dynamical and structural stability outcomes varied noticeably. Temporal short-term LyE and all structural stability measures were more influenced by the cycle percentage (posture factor) than by phase (lifting, lowering) or load factor. The effect of all factors were non-significant for FM and long LyE, except for the posture on LyE-L with a small effect size. Pearson's correlations revealed a weak to moderate, or non-existent, correlation between structural and dynamical stability metrics, with small shared variances, underscoring their distinct and independent nature and theoretical foundations. Moreover, the low sensitivity of dynamic measures to posture and load factors, found in this study, calls for further examination. Considering the limitations and shortcomings of both dynamical and structural stability assessment approaches, there is a need for the development of improved musculoskeletal stability evaluation techniques.

Neuromuscular adaptations to experimentally induced pain in the lumbar region: systematic review and meta-analysis

ABSTRACT

Experimental pain models are frequently used to understand the influence of pain on the control of human movement. In this systematic review, we assessed the effects of experimentally induced pain in the lumbar region of healthy individuals on trunk muscle activity and spine kinematics. Databases were searched from inception up to January 31, 2022. In total, 26 studies using either hypertonic saline injection (n = 19), heat thermal stimulation (n = 3), nociceptive electrical stimulation (n = 3), or capsaicin (n = 1) were included. The identified adaptations were task dependent, and their heterogeneity was partially explained by the experimental pain model adopted. Meta-analyses revealed an increase of erector spinae activity (standardized mean difference = 0.71, 95% confidence interval [CI] = 0.22-1.19) during full trunk flexion and delayed onset of transversus abdominis to postural perturbation tasks (mean difference = 25.2 ms, 95% CI = 4.09-46.30) in the presence of pain. Low quality of evidence supported an increase in the activity of the superficial lumbar muscles during locomotion and during voluntary trunk movements during painful conditions. By contrast, activity of erector spinae, deep multifidus, and transversus abdominis was reduced during postural perturbation tasks. Reduced range of motion of the lumbar spine in the presence of pain was supported by low quality of evidence. Given the agreement between our findings and the adaptations observed in clinical populations, the use of experimental pain models may help to better understand the mechanisms underlying motor adaptations to low back pain.

Predicting Noncontact Lower Limb Injury Using Lumbar Morphology in Professional Australian Football and Rugby League Players

INTRODUCTION

Noncontact lower limb injuries are common within the Australian Football League (AFL) and National Rugby League (NRL). Smaller (<8.5 cm2) lumbar multifidus at the fifth vertebra (LM L5) and larger (>8.2 cm2) quadratus lumborum (QL) cross-sectional area (CSA) have been associated with increased noncontact lower limb injury risk in AFL players. These associations have not been explored in an NRL cohort. This study will attempt to replicate previous research findings by confirming that muscle morphology is associated with noncontact lower limb injury.

METHODS

AFL (n = 87) and NRL (n = 151) players underwent LM L2-L5 and QL CSA ultrasound measures during preseason. Each club's medical staff reported all noncontact lower limb injuries sustained in the subsequent regular season. LM and QL CSA, age, body mass index, and noncontact lower limb injuries were analyzed using multivariable logistic regression.

RESULTS

Seventy-two players sustained a noncontact lower limb injury in the 2020 regular season (AFL = 21, NRL = 51). The multivariable logistic regression (odds ratio (OR) = 1.36; 95% confidence interval (CI), 1.02-1.85; P = 0.038) identified AFL players with larger QL CSA at increased risk of sustaining a noncontact lower limb injury during the regular season, but no relationship was found for LM CSA and noncontact lower limb injuries in the AFL (OR = 1.01; 95% CI, 0.36-2.78; P = 0.591) or NRL (OR = 0.63; 95% CI, 0.29-1.33; P = 0.149).

CONCLUSIONS

AFL players who sustained regular season noncontact lower limb injuries had larger QL CSA in preseason tests. No significant associations between either LM L5 CSA or LM L5 to QL ratio and regular season noncontact lower limb injuries were found.

Evaluating stability of human spine in static tasks: a combined in vivo-computational study

Various interpretations and parameters have been proposed to assess spinal stability such as antagonist muscle coactivity, trunk stiffness and spinal buckling load; however, the correlation between these parameters remains unknown. We evaluated spinal stability during different tasks while changing the external moment and load height and investigated likely relationships between different EMG- and model-based parameters (e.g., EMG coactivity ratio, trunk stiffness, force coactivity ratio) and stability margins. EMG and kinematics of 40 young healthy subjects were recorded during various quasi-static tasks. Muscle forces, trunk stiffness and stability margins were calculated by a nonlinear subject-specific EMG-assisted-optimization musculoskeletal model of the trunk. The load elevation and external moment increased muscle activities and trunk stiffness while all stability margins (i.e., buckling loads) decreased. The force coactivity ratio was strongly correlated with the hand-load stability margin (i.e., additional weight in hands to initiate instability; R² = 0.54) demonstrating the stabilizing role of abdominal muscles. The total trunk stiffness (Pearson's r = 0.96) and the sum of EMGs of back muscles (Pearson's r = 0.65) contributed the most to the T1 stability margin (i.e., additional required load at T1 for instability/buckling). Force coactivity ratio and trunk stiffness can be used as alternative spinal stability metrics.

Directional Dependence of Experimental Trunk Stiffness: Role of Muscle-Stiffness Variation of Nonneural Origin

Trunk stiffness is an important parameter for trunk stability analysis and needs to be evaluated accurately. Discrepancies regarding the dependence of trunk stiffness on the direction of movement in the sagittal plane suggest inherent sources of error that require explanation. In contrast to the common assumption that the muscle stiffness remains constant prior to the induction of a reflex during position perturbations, it is postulated that muscle-stiffness changes of nonneural origin occur and alter the experimental trunk stiffness, causing it to depend on the sagittal direction. This is confirmed through reinterpretation of existing test data for a healthy subject, numerical simulation, and sensitivity analysis using a biomechanical model. The trunk stiffness is determined through a static approach (in forward and backward directions) and compared with the model stiffness for assumed scenarios involving deactivated muscles. The difference in stiffness between the opposite directions reaches 17.5% without a preload and decreases when a moderate vertical preload is applied. The increased muscle activation induced by preloads or electrical stimuli explains the apparent discrepancies observed in previous studies. The experimental stiffness invariably remains between low and high model-stiffness estimates based on extreme scenarios of the postulated losses of muscle activation, thereby confirming our hypothesis.