NDLI: Predicting the Risk of Low Back Disorders due to Manual Handling Tasks

Content Provider	IEEE Xplore Digital Library
Author	Zurada, J.
Copyright Year	2012
Abstract	Work related low back disorders (LBDs) due to manual material handling (MMH) tasks have long been recognized as one of the main occupational disabling injury that affects the quality of life of the industrial working population in the U.S. One of the efforts to comprehend the nature and phenomenon of LBDs due to MMH tasks was undertaken by Marras [18]. Based on multiple experiments they created a seminal data set and used it to build logistic regression models to identify significant variables and classify manual lifting tasks into high risk and low risk with respect to LBDs. Since then a number of studies have used the same data set to build and test various classification models. This paper analyzes the previous studies and employs the same data set to build and test seven classification methods. Though the performances of our best models are better than those reported in National Institute for Occupational Health and Safety (NIOHS) Guides and two of our previous studies, they are generally less optimistic than those reported in several other studies, this paper proposes a more systematic and reliable approach to creating and validating classifiers to distinguish between low and high risk manual lifting jobs that contribute to LBDs.
Starting Page	1080
Ending Page	1088
File Size	327086
Page Count	9
File Format	PDF
ISBN	9781457719257
ISSN	15301605
e-ISBN	9780769545257
DOI	10.1109/HICSS.2012.482
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-01-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Accuracy Data models Training Artificial neural networks Neurons Vegetation Data mining methods Low back disorders Manual handling tasks Classification Low risk and high risk jobs
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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