Li Li

College of Engineering

Works (3)

Updated: July 5th, 2023 14:27

2021 journal article

Lifting Posture Prediction With Generative Models for Improving Occupational Safety

IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 51(5), 494–503.

By: L. Li n, S. Prabhu n, Z. Xie n, H. Wang n , L. Lu n & X. Xu n 

author keywords: Generative models; lifting tasks; neural networks; occupational injuries; posture prediction
TL;DR: The results prove that using a generative model to predict lifting posture prediction is able to predict postures with reasonable accuracy and validity and can support biomechanical analysis and ergonomics assessment of a lifting task to reduce the risk of low back injuries. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID
Added: September 27, 2021

2021 journal article

Real-Time Driving Distraction Recognition Through a Wrist-Mounted Accelerometer

HUMAN FACTORS, 64(8), 1412–1428.

By: Z. Xie n, L. Li n & X. Xu n 

author keywords: accident analysis; distractions and interruptions; risk assessment; biomechanics; kinematics
MeSH headings : Humans; Accidents, Traffic; Wrist; Pilot Projects; Automobile Driving; Accelerometry
TL;DR: The results of this pilot study indicate that the proposed driving distraction mitigation system that uses a wrist-worn IMU and ConvLSTM deep neural network classifier may have potential for improving transportation safety. (via Semantic Scholar)
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Sources: Web Of Science, ORCID, NC State University Libraries
Added: April 5, 2021

2020 journal article

MOPED25: A multimodal dataset of full-body pose and motion in occupational tasks

JOURNAL OF BIOMECHANICS, 113.

By: L. Li n, Z. Xie n & X. Xu n 

author keywords: Pose dataset; Kinematics; Postural risk; Computer vision
MeSH headings : Algorithms; Ergonomics; Humans; Motion; Neural Networks, Computer; Posture
TL;DR: A new posture dataset named, MOPED25 (Multimodal Occupational Posture Dataset with 25 tasks) is presented, which includes full-body kinematics data and the synchronized videos of 11 participants, performing commonly seen tasks at workplaces. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: January 11, 2021

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