Feasibility of Tree-Based Machine Learning Models to Discriminate Safe and Unsafe Posture During Weight Lifting-Reference-Cited by-同舟云学术

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Feasibility of Tree-Based Machine Learning Models to Discriminate Safe and Unsafe Posture During Weight Lifting

Published:2023-10-25 Issue: Volume:24 Page:870-875
ISSN:
Container-title:2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)
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Author:

Prisco Giuseppe¹,Romano Maria²,Esposito Fabrizio³,Cesarelli Mario⁴,Santone Antonella¹,Donisi Leandro³

Affiliation:

1. University of Molise,Dept. of Medicine and Health Sciences,Campobasso,Italy

2. University of Naples Federico II,Dept. of Information Technology and Electrical Engineering,Naples,Italy

3. University of Campania Luigi Vanvitelli,Dept. of Advanced Medical and Surgical Sciences,Naples,Italy

4. University of Sannio,Dept. of Engineering,Benevento,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10405419/10405547/10405830.pdf?arnumber=10405830

Reference43 articles.

1. Risk factors for work-related musculoskeletal disorders: a systematic review of recent longitudinal studies

2. Musculoskeletal disorders and workplace factors. A critical review of epidemiologic evidence for work-related musculoskeletal disorders of the neck, upper extremity, and low back.

3. RULA: a survey method for the investigation of work-related upper limb disorders;McAtamney;Applied ergonomics,1993

4. Rapid entire body assessment (REBA);Hignett;App. Ergon,2000

5. MAPO index for risk assessment of patient manual handling in hospital wards: a validation study

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Capability of Machine Learning Algorithms to Classify Safe and Unsafe Postures during Weight Lifting Tasks Using Inertial Sensors;Diagnostics;2024-03-08

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