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Background
Back pain patients (BPP) show delayed muscle onset, increased co-contractions, and variability as response to quasi-static sudden trunk loading in comparison to healthy controls (H). However, it is unclear whether these results can validly be transferred to suddenly applied walking perturbations, an automated but more functional and complex movement pattern. There is an evident need to develop research-based strategies for the rehabilitation of back pain. Therefore, the investigation of differences in trunk stability between H and BPP in functional movements is of primary interest in order to define suitable intervention regimes. The purpose of this study was to analyse neuromuscular reflex activity as well as three-dimensional trunk kinematics between H and BPP during walking perturbations.
Methods
Eighty H (31m/49f;29±9yrs;174±10cm;71±13kg) and 14 BPP (6m/8f;30±8yrs;171±10cm;67±14kg) walked (1m/s) on a split-belt treadmill while 15 right-sided perturbations (belt decelerating, 40m/s2, 50ms duration; 200ms after heel contact) were randomly applied. Trunk muscle activity was assessed using a 12-lead EMG set-up. Trunk kinematics were measured using a 3-segment-model consisting of 12 markers (upper thoracic (UTA), lower thoracic (LTA), lumbar area (LA)). EMG-RMS ([%],0-200ms after perturbation) was calculated and normalized to the RMS of unperturbed gait. Latency (TON;ms) and time to maximum activity (TMAX;ms) were analysed. Total motion amplitude (ROM;[°]) and mean angle (Amean;[°]) for extension-flexion, lateral flexion and rotation were calculated (whole stride cycle; 0-200ms after perturbation) for each of the three segments during unperturbed and perturbed gait. For ROM only, perturbed was normalized to unperturbed step [%] for the whole stride as well as the 200ms after perturbation. Data were analysed descriptively followed by a student´s t-test to account for group differences. Co-contraction was analyzed between ventral and dorsal muscles (V:R) as well as side right:side left ratio (Sright:Sleft). The coefficient of variation (CV;%) was calculated (EMG-RMS;ROM) to evaluate variability between the 15 perturbations for all groups. With respect to unequal distribution of participants to groups, an additional matched-group analysis was conducted. Fourteen healthy controls out of group H were sex-, age- and anthropometrically matched (group Hmatched) to the BPP.
Results
No group differences were observed for EMG-RMS or CV analysis (EMG/ROM) (p>0.025). Co-contraction analysis revealed no differences for V:R and Srigth:Sleft between the groups (p>0.025). BPP showed an increased TON and TMAX, being significant for Mm. rectus abdominus (p = 0.019) and erector spinae T9/L3 (p = 0.005/p = 0.015). ROM analysis over the unperturbed stride cycle revealed no differences between groups (p>0.025). Normalization of perturbed to unperturbed step lead to significant differences for the lumbar segment (LA) in lateral flexion with BPP showing higher normalized ROM compared to Hmatched (p = 0.02). BPP showed a significant higher flexed posture (UTA (p = 0.02); LTA (p = 0.004)) during normal walking (Amean). Trunk posture (Amean) during perturbation showed higher trunk extension values in LTA segments for H/Hmatched compared to BPP (p = 0.003). Matched group (BPP vs. Hmatched) analysis did not show any systematic changes of all results between groups.
Conclusion
BPP present impaired muscle response times and trunk posture, especially in the sagittal and transversal planes, compared to H. This could indicate reduced trunk stability and higher loading during gait perturbations.
Stumbling led to an increase in ROM, compared to unperturbed gait, in all segments and planes. These increases ranged between 107 +/- 26% (UTA/rotation) and 262 +/- 132% (UTS/lateral flexion), significant only in lateral flexion. EMG activity of the trunk was increased during stumbling (abdominal: 665 +/- 283%; back: 501 +/- 215%), without significant differences between muscles. Provoked stumbling leads to a measurable effect on the trunk, quantifiable by an increase in ROM and EMG activity, compared to normal walking. Greater abdominal muscle activity and ROM of lateral flexion may indicate a specific compensation pattern occurring during stumbling. (C) 2015 Elsevier Ltd. All rights reserved.
The aim of this study was to investigate the effect of a 6-week sensorimotor or resistance training on maximum trunk strength and response to sudden, high-intensity loading in athletes. Interventions showed no significant difference for maximum strength in concentric and eccentric testing (p>0.05). For perturbation compensation, higher peak torque response following SMT (Extension: +24Nm 95%CI +/- 19Nm; Rotation: + 19Nm 95%CI +/- 13Nm) and RT (Extension: +35Nm 95%CI +/- 16Nm; Rotation: +5Nm 95%CI +/- 4Nm) compared to CG (Extension: -4Nm 95%CI +/- 16Nm; Rotation: -2Nm 95%CI +/- 4Nm) was present (p<0.05).
Investigating of locomotor disturbances are relevant in human injury and performance. Therefore, lower extremity kinematics were analysed in response to decelerative perturbations during running using statistical parametric mapping (SPM). 13 asymptomatic individuals (8 females & 5 males, 28 +/- 3 years, 171 +/- 9 cm, 68 +/- 10 kg) completed an 8-minute running protocol with 30 one-sided perturbations (15 each side) to generate decelerative disturbances.
A 3D-motion capture system was employed to record kinematic data. Joint angles of the ankle, knee, and hip in addition to stride duration, stride length and step width were calculated for leading and trailing strides.
Results were analysed descriptively, followed by SPM of paired t-tests (P < 0.025). Reactively (after perturbation), perturbations caused decreased hip adduction and stride duration of the leading leg. The trailing leg reacted with ankle inversion, knee and hip flexion, hip abduction, as well as an increase in stride duration and step width (P < 0.025). In preparation for perturbation, the trailing leg reduced ankle dorsiflexion, knee flexion, hip flexion, and adduction. In summary, applied perturbations produced substantial reactive (feedback) and predictive (feedforward) responses of the lower limbs, most apparent in the trailing leg.
This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators' experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes.