Musculoskeletal models have traditionally relied on measurements of segment kinematics and ground reaction forces and moments (GRF&Ms) from marked-based motion capture and floor-mounted force plates, which are typically limited to laboratory settings. Recent advances in inertial motion capture (IMC) as well as methods for predicting GRF&Ms have enabled the acquisition of these input data in the field. Therefore, this study evaluated the concurrent validity of a novel methodology for estimating the dynamic loading of the lumbar spine during manual materials handling based on a musculoskeletal model driven exclusively using IMC data and predicted GRF&Ms. Trunk kinematics, GRF&Ms, L4-L5 joint reaction forces (JRFs) and erector spinae muscle forces from 13 subjects performing various lifting and transferring tasks were compared to a model driven by simultaneously recorded skin-marker trajectories and force plate data. Moderate to excellent correlations and relatively low magnitude differences were found for the L4-L5 axial compression, erector spinae muscle and vertical ground reaction forces during symmetrical and asymmetrical lifting, but discrepancies were also identified between the models, particularly for the trunk kinematics and L4-L5 shear forces. Based on these results, the presented methodology can be applied for estimating the relative L4-L5 axial compression forces under dynamic conditions during manual materials handling in the field.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s10439-019-02409-8DOI Listing

Publication Analysis

Top Keywords

manual materials
12
materials handling
12
motion capture
12
reaction forces
12
inertial motion
8
ground reaction
8
model driven
8
trunk kinematics
8
erector spinae
8
spinae muscle
8

Similar Publications

Background: The main challenge in new drug development is accurately predicting the human response in preclinical models.

Methods: In this study, we developed three different intestinal barrier models using advanced biofabrication techniques: (i) a manual model containing Caco-2 and HT-29 cells on a collagen bed, (ii) a manual model with a Caco-2/HT-29 layer on a HDFn-laden collagen layer, and (iii) a 3D bioprinted model incorporating both cellular layers. Each model was rigorously tested for its ability to simulate a functional intestinal membrane.

View Article and Find Full Text PDF

Mitochondrial segmentation and function prediction in live-cell images with deep learning.

Nat Commun

January 2025

Frontiers Science Center for Flexible Electronics, Xi'an Institute of Flexible Electronics (IFE) and Xi'an Institute of Biomedical Materials & Engineering, Northwestern Polytechnical University, Xi'an, China.

Mitochondrial morphology and function are intrinsically linked, indicating the opportunity to predict functions by analyzing morphological features in live-cell imaging. Herein, we introduce MoDL, a deep learning algorithm for mitochondrial image segmentation and function prediction. Trained on a dataset of 20,000 manually labeled mitochondria from super-resolution (SR) images, MoDL achieves superior segmentation accuracy, enabling comprehensive morphological analysis.

View Article and Find Full Text PDF

Toward a Computable Phenotype for Determining Eligibility of Lung Cancer Screening Using Electronic Health Records.

JCO Clin Cancer Inform

January 2025

Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL.

Purpose: Lung cancer screening (LCS) has the potential to reduce mortality and detect lung cancer at its early stages, but the high false-positive rate associated with low-dose computed tomography (LDCT) for LCS acts as a barrier to its widespread adoption. This study aims to develop computable phenotype (CP) algorithms on the basis of electronic health records (EHRs) to identify individual's eligibility for LCS, thereby enhancing LCS utilization in real-world settings.

Materials And Methods: The study cohort included 5,778 individuals who underwent LDCT for LCS from 2012 to 2022, as recorded in the University of Florida Health Integrated Data Repository.

View Article and Find Full Text PDF

Widespread screening is crucial for the early diagnosis and treatment of glaucoma, the leading cause of visual impairment and blindness. The development of portable technologies, such as smartphone-based ophthalmoscopes, able to image the optical nerve head, represents a resource for large-scale glaucoma screening. Indeed, they consist of an optical device attached to a common smartphone, making the overall device cheap and easy to use.

View Article and Find Full Text PDF

Background: The rising global burden of breast cancer demands early detection and effective treatment, with a focus on prognostic and predictive markers. The eighth edition of the American Joint Committee on Cancer staging manual introduced a new prognostic staging system to increase the predictive power of the existing anatomical staging system of breast cancer. The current study aimed to establish the correlation between Ki67 expression with molecular subtypes and with the pathological prognostic stage of invasive ductal carcinoma.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!