Effect of a back-support exoskeleton on internal forces and lumbar spine stability during low load lifting task.

This study assessed the effect of a small-torque generating passive back-support exoskeleton during a low demanding occupational task, namely a repetitive lifting/lowering of an empty crate between the knee and shoulder heights. A comprehensive set of outcomes was considered, ranging from the measured trunk muscle activation and trunk movement to the estimated muscle group forces/coordination, spine loading and spine stability, using a dynamic subject-specific EMG-assisted musculoskeletal model. The exoskeleton decreased back muscle activation and corresponding muscle forces in the lowering phase and reduced spinal loading at larger trunk flexion angles (decreased peak compression and shear forces by ∼ 15%).

Machine learning applications in spine biomechanics.

Spine biomechanics is at a transformation with the advent and integration of machine learning and computer vision technologies. These novel techniques facilitate the estimation of 3D body shapes, anthropometrics, and kinematics from as simple as a single-camera image, making them more accessible and practical for a diverse range of applications. This study introduces a framework that merges these methodologies with traditional musculoskeletal modeling, enabling comprehensive analysis of spinal biomechanics during complex activities from a single camera.

A Biomechanics-Aware Robot-Assisted Steerable Drilling Framework for Minimally Invasive Spinal Fixation Procedures.

In this paper, we propose a novel biomechanics-aware robot-assisted steerable drilling framework with the goal of addressing common complications of spinal fixation procedures occurring due to the rigidity of drilling instruments and implants. This framework is composed of two main unique modules to design a robotic system including (i) a Patient-Specific Biomechanics-aware Trajectory Selection Module used to analyze the stress and strain distribution along an implanted pedicle screw in a generic drilling trajectory (linear and/or curved) and obtain an optimal trajectory; and (ii) a complementary semi-autonomous robotic drilling module that consists of a novel Concentric Tube Steerable Drilling Robot (CT-SDR) integrated with a seven degree-of-freedom robotic manipulator. This semi-autonomous robot-assisted steerable drilling system follows a multi-step drilling procedure to accurately and reliably execute the optimal hybrid drilling trajectory (HDT) obtained by the Trajectory Selection Module.

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.

Validation of an EMG submaximal method to calibrate a novel dynamic EMG-driven musculoskeletal model of the trunk: Effects on model estimates.

Background: Multijoint EMG-assisted optimization models are reliable tools to predict muscle forces as they account for inter- and intra-individual variations in activation. However, the conventional method of normalizing EMG signals using maximum voluntary contractions (MVCs) is problematic and introduces major limitations. The sub-maximal voluntary contraction (SVC) approaches have been proposed as a remedy, but their performance against the MVC approach needs further validation particularly during dynamic tasks.

Submaximal electromyography-driven musculoskeletal modeling of the human trunk during static tasks: Equilibrium and stability analyses.

Conventional electromyography-driven (EMG) musculoskeletal models are calibrated during maximum voluntary contraction (MVC) tasks, but individuals with low back pain cannot perform unbiased MVCs. To address this issue, EMG-driven models can be calibrated in submaximal tasks. However, the effects of maximal (when data points include the maximum contraction) and submaximal calibration techniques on model outputs (e.

Modeling of human intervertebral disc annulus fibrosus with complex multi-fiber networks.

Collagen fibers within the annulus fibrosus (AF) lamellae are unidirectionally aligned with alternating orientations between adjacent layers. AF constitutive models often combine two adjacent lamellae into a single equivalent layer containing two fiber networks with a crisscross pattern. Additionally, AF models overlook the inter-lamellar matrix (ILM) as well as elastic fiber networks in between lamellae.

On the modeling of human intervertebral disc annulus fibrosus: Elastic, permanent deformation and failure responses.

As a primary load-resisting component, annulus fibrosus (AF) maintains structural integrity of the entire intervertebral disc. Experiments have demonstrated that permanent deformation and damage take place in the tissue under mechanical loads. Development of an accurate model to capture the complex behaviour of AF tissue is hence crucial in disc model studies.

Analysis of developmental level of counties of Fars in terms of health infrastructure indicators using standardized scores pattern approach and factor analysis.

Introduction: It is necessary for planning in order to achieve optimal development, to have knowledge and understanding of the current situation. This identification requires separate areas of study into planning and assessing regions of each area with development indicators and analysis and ranking each area in terms of having gifts of development. The study also aims to analyze the development level of counties of Fars in terms of health infrastructure indicators using standardized scores pattern and factor analysis.