LI Li

Works (3)

Updated: July 9th, 2023 19:45

2020 article

A novel vision-based real-time method for evaluating postural risk factors associated with musculoskeletal disorders

Li, L., Martin, T., & Xu, X. (2020, May 4). Applied Ergonomics, Vol. 87.

By: L. Li n, T. Martin n & X. Xu n 

author keywords: RULA; Deep learning; MSD risk assessment
MeSH headings : Adult; Deep Learning; Ergonomics / methods; Female; Humans; Image Processing, Computer-Assisted / methods; Lifting; Male; Musculoskeletal Diseases / diagnostic imaging; Musculoskeletal Diseases / etiology; Occupational Diseases / diagnostic imaging; Occupational Diseases / etiology; Photography / methods; Posture; Risk Assessment; Risk Factors; Upper Extremity / diagnostic imaging
topics (OpenAlex): Musculoskeletal pain and rehabilitation; Ergonomics and Musculoskeletal Disorders; Occupational Health and Safety Research
TL;DR: This document examines a novel end-to-end implementation of a deep learning-based algorithm for rapid upper limb assessment (RULA) and indicates that using data augmentation (a strategy to diversify the training data) can significantly improve the robustness of the model. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: June 22, 2020

2019 article

Video-Based Driver’s Hand Tracking using Fast Normalized Cross Coefficient with Improved Computational Efficiency

Li, L., Hutmacher, C. M., & Xu, X. (2019, April 17). Transportation Research Record Journal of the Transportation Research Board, Vol. 2673, pp. 233–241.

By: L. Li n, C. Hutmacher n & X. Xu n 

topics (OpenAlex): Human-Automation Interaction and Safety; Gaze Tracking and Assistive Technology; EEG and Brain-Computer Interfaces
TL;DR: A computer vision-based method to track hand movement from the recorded driving behavior using fast normalized cross coefficient (NCC) and a novel searching strategy is proposed, which outperformed a state of the art algorithm in MOTA and MT. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: October 14, 2019

2007 article

Non-monotonic dose–response relationship in steroid hormone receptor-mediated gene expression

Li, L., Andersen, M. E., Heber, S., & Zhang, Q. (2007, May 1). Journal of Molecular Endocrinology, Vol. 38, pp. 569–585.

By: L. Li n, M. Andersen *, S. Heber n  & Q. Zhang *

MeSH headings : Animals; Dimerization; Dose-Response Relationship, Drug; Gene Expression Regulation / drug effects; Hormones / pharmacology; Humans; Ligands; Models, Biological; Models, Theoretical; Receptors, Steroid / agonists; Receptors, Steroid / antagonists & inhibitors; Receptors, Steroid / genetics; Receptors, Steroid / metabolism; Repressor Proteins / metabolism; Repressor Proteins / pharmacology; Trans-Activators / metabolism; Trans-Activators / pharmacology
topics (OpenAlex): Estrogen and related hormone effects; Effects and risks of endocrine disrupting chemicals; Gene Regulatory Network Analysis
TL;DR: This work provides a novel mechanism for non-monotonic, particularly U-shaped, dose-response behaviors observed with certain steroid mimics, and may help not only understand how selective steroid receptor modulators work but also improve risk assessment for EACs. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

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