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Register a new userBetween-session reliability of skin marker-derived spinal kinematics during functional activities
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Background: Skin marker-based analysis of functional spinal movement is a promising method for quantifying longitudinal effects of treatment interventions in patients with spinal pathologies. However, observed day-to-day changes might not necessarily be due to a treatment intervention, but can result from errors related to soft tissue artifacts, marker placement inaccuracies or biological day-to-day variability. Research question: How reliable are skin marker-derived three-dimensional spinal kinematics during functional activities between two separate measurement sessions? Methods: Twenty healthy adults (11f/9m) were invited to a movement analysis laboratory for two visits separated by 7-10 days. At each visit, they performed various functional activities (i.e. sitting, standing, walking, running, chair rising, box lifting and vertical jumping), while marker trajectories were recorded using a skin marker-based 10-camera optical motion capture system and used to calculate sagittal and frontal plane spinal curvature angles as well as transverse plane segmental rotational angles in the lumbar and thoracic regions. Between-session reliability for continuous data and discrete parameters was determined by analyzing systematic errors using one sample T-tests as well as by calculating intraclass correlation coefficients (ICCs) and minimal detectable changes (MDCs). Results and Significance: The analysis indicated high relative consistency for sagittal plane curvature angles during all activities, but not for frontal and transverse plane angles during walking and running. MDCs were mostly below 15{deg}, with relative values ranging between 10% and 750%. This study provides important information that can serve as a basis for researchers and clinicians aiming at investigating longitudinal effects of treatment interventions on spinal motion behavior in patients with spinal pathologies.
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Musculoskeletal models have the potential to improve diagnosis and optimize clinical treatment by predicting accurate outcomes on an individual basis. However, the subject-specific modeling of spinal alignment is often strongly simplified or is based on radiographic assessments, exposing subjects to unnecessary radiation. We therefore developed a novel skin marker-based approach for modeling subject-specific spinal alignment and evaluated its feasibility by comparing the predicted with the actual intervertebral joint (IVJ) locations/orientations (ground truth) using lateral-view radiographic images. Moreover, the predictive performance of the subject-specific models was evaluated by comparing the predicted L1/L2 spinal loads during various functional activities with in vivo measured data obtained from the OrthoLoad database. IVJ locations/orientations were predicted closer to ground truth as opposed to standard model scaling, with average location prediction errors of 0.99+/-0.68 cm on the frontal and 1.21+/-0.97 cm on the transverse axis as well as an average orientation prediction error of 4.74{deg}+/-2.80{deg}. Simulated spinal loads showed similar curve patterns but considerably larger values as compared to in vivo measured data. Differences in spinal loads between generic and subject-specific models become only apparent on an individual subject level. These results underline the feasibility of the proposed method and associated workflow for inter- and intra-subject investigations using musculoskeletal simulations. When implemented into standard model scaling workflows, it is expected to improve the accuracy of muscle activity and joint loading simulations, which is crucial for investigations of treatment effects or pathology-dependent deviations.
The pathogenesis of adolescent idiopathic scoliosis (AIS) remains poorly understood and biomechanical data are limited. A deeper insight into spinal loading could provide valuable information for the improvement of current treatment strategies. This work therefore aimed at using subject-specific musculoskeletal full-body models of patients with AIS to predict segmental compressive forces around the curve apex and to investigate how these forces are affected by simulated load carrying. Models were created based on spatially calibrated biplanar radiographic images from 24 patients with mild to moderate AIS and validated by comparing predictions of paravertebral muscle activity with reported values from in vivo studies. Spinal compressive forces were predicted during unloaded upright standing as well as upright standing with external loads of 10%, 15% and 20% of body weight (BW) applied to the scapulae to simulate carrying a backpack in the regular way, in front of the body and over both shoulders. The validation studies showed higher convex muscle activity, which was comparable to the literature. The implementation of spinal deformity resulted in a 10% increase of compressive force at the curve apex during unloaded upright standing. Apical compressive forces further increased by 50-62%, 77-94% and 103-128% for 10%, 15% and 20% BW loads, respectively. Moreover, load-dependent compressive force increases were the lowest in the regular backpack and the highest in the frontpack and convex conditions. The predictions indicated increased segmental compressive forces during unloaded standing, which could be ascribed to the scoliotic deformation. When carrying loads, compressive forces further increased depending on the carrying mode and the weight of the load. These results can be used as a basis for further studies investigating segmental loading in AIS patients during functional activities.
In humans, the tactile perception of fine textures is mediated by skin vibrations when scanning the surface with the fingertip. These vibrations are encoded by specific mechanoreceptors, Pacinian corpuscules (PCs), located about 2 mm below the skin surface. In a recent article, we performed experiments using a biomimetic sensor which suggest that fingerprints (epidermal ridges) may play an important role in shaping the subcutaneous stress vibrations in a way which facilitates their processing by the PC channel. Here we further test this hypothesis by directly recording the modulations of the fingerpad/substrate friction force induced by scanning an actual fingertip across a textured surface. When the fingerprints are oriented perpendicular to the scanning direction, the spectrum of these modulations shows a pronounced maximum around the frequency v/lambda, where v is the scanning velocity and lambda the fingerprints period. This simple biomechanical result confirms the relevance of our previous finding for human touch.
We analyze the connectivity structure of weighted brain networks extracted from spontaneous magnetoencephalographic (MEG) signals of healthy subjects and epileptic patients (suffering from absence seizures) recorded at rest. We find that, for the activities in the 5-14 Hz range, healthy brains exhibit a sparse connectivity, whereas the brain networks of patients display a rich connectivity with clear modular structure. Our results suggest that modularity plays a key role in the functional organization of brain areas during normal and pathological neural activities at rest.
Lifting up objects from the floor has been identified as a risk factor for low back pain, whereby a flexed spine during lifting is often associated with producing higher loads in the lumbar spine. Even though recent biomechanical studies challenge these assumptions, conclusive evidence is still lacking. This study therefore aimed at comparing lumbar loads among different lifting styles using a comprehensive state-of-the-art motion capture-driven musculoskeletal modeling approach. Thirty healthy pain-free individuals were enrolled in this study and asked to repetitively lift a 15 kg-box by applying 1) a freestyle, 2) a squat and 3) a stoop lifting technique. Whole-body kinematics were recorded using an optical motion capture system and used to drive a full-body musculoskeletal model including a detailed thoracolumbar spine. Compressive, shear and total loads were calculated based on a static optimization approach and expressed as factor body weight (BW). In addition, lumbar lordosis angles and total lifting time were calculated. All parameters were compared among the lifting styles using a repeated measures design. For all lumbar segments, stoop lifting showed significantly lower compressive and total loads (-0.3 to -1.0BW) when compared to freestyle and squat lifting. Stoop lifting produced higher shear loads (+0.1 to +0.8BW) in the segments T12/L1 to L4/L5, but lower loads in L5/S1 (-0.2 to -0.4BW). Peak compressive and total loads during squat lifting occurred approximately 30% earlier in the lifting cycle compared to stoop lifting. Stoop lifting showed larger lumbar lordosis range of motion (35.9+/-10.1{deg}) than freestyle (24.2+/-7.3{deg}) and squat (25.1+/-8.2{deg}) lifting. Lifting time differed significantly with freestyle being executed the fastest (4.6+/-0.7s), followed by squat (4.9+/-0.7s) and stoop (5.9+/-1.1s).
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