Vol 7, No 4 (2016) > Industrial Engineering >

A Shoveling-related Pain Intensity Prediction Expert System for Workers’ Manual Movement of Material

Adeyemi Hezekiah Oluwole, Adefemi A. Adekunle, Akinyemi O. Olasunkanmi, Adefemi O. Adeodu

 

Abstract: In
this study, a fuzzy-based expert system called the Pain Intensity Prediction
Expert System (PIPES) was developed to predict pain severity risk (PSR) in
shoveling-related tasks. The primary objective was to develop a non-changing rating risk assessment ergonomics
tool that both efficient
and comparable with those obtained from human ergonomics experts in the field
of application.  PIPES used fuzzy set
theory (FST) to make decisions about the level of pain associated with a
selected worker base on the measured task variables, namely scooping rate, scooping time, shovel load, and
throw distance as input and PSR as the result. Values obtained from variable measurements from a sand shoveling task
were run with PIPES, and the results were compared with the workers’
self-reported pain (WSRP) intensity using a numeric rating scale (NRS) tool. The result of validation showed that there was a
strong positive relationship between WSRP NRS and PIPES NRS, with a correlation
coefficient of 0.70. The independent sample t-test for mean difference showed that WSRP had a statistically significantly lower level of NRS (4.35 ± 2.1)
compared to PIPES (4.75 ± 2.2), t (38) = - 0.591, p = 0.558. With a
significance level of 0.001 at 95% confidence, the groups’ means were not
significantly different. The study developed an expert system, PIPES, which can be used as a computerized
representation of ergonomics experts, who are scarce. PIPES can be applied to construction industries, sand mine locations,
and any workplace where materials are manually moved using a shovel.
Keywords: Expert system; Fuzzy; Pain ; Risk; Sand; Severity; Shoveling; Task

Full PDF Download

References


Adeyemi, H.O., Adejuyigbe, S.B., Ismaila, S.O., Adekoya, A.F., 2015. Low Back Pain Assessment Application for Construction Workers. Journal of Engineering, Design and Technology, Volume 13(3), pp. 419–434

Adeyemi, H.O., Adejuyigbe, S.B., Ismaila, S.O., Adekoya, A.F., Akanbi, O.G., 2013. Modelling Manual Material Lifting Risk Evaluation: A Fuzzy Logic Approach. International Journal of Applied Sciences and Engineering Research, Volume 2(1), pp. 44–59

Anahad, O., 2011. Really? The claim: Shovelling Snow Raises the Risk of a Heart Attack. Available online at: http://well.blogs.nytimes.com/, Accessed on 16 September 2014

Ann, L., 2011. Many Risk of Shovelling Snow. Available online at: www.wsj.com/articles, Accessed on 11 January 2014

Araujo, E., Miyahira, S.A., 2011. Tridimensional Fuzzy Pain Assessment. In: IEEE International Conference on Fuzzy Systems (FUZZ), Taipei, pp. 1634–1639

Bansal, A., 2011. Trapezoidal Fuzzy Numbers (a,b,c,d): Arithmetic Behaviour. International Journal of Physical and Mathematical Sciences, Volume 2(1), pp 39–44

Breivik, E.K, Bjornsson, G.A, Skovlund, E., 2000. A Comparison of Pain Rating Scales by Sampling from Clinical Trial Data. Clinical Journal of Pain, Volume 16, pp. 8–22

Breivik, H., Borchgrevink, P.C., Allen, S.M., Rosseland, L.A., Romundstad, L., Breivik, E.K., Kvarstein, G., Stubhaug, A., 2008. Assessment of Pain. British Journal of Anaesthesia, Volume 101(1), pp. 17–24

Bridger, R.S., Sparto, P., Marras, W.S., 1998. Spade Design, Lumbar Motions, Risk of Low Back Injury and Digging Posture. Occupation Ergonomics, Volume 1(3), pp. 157–172

Canadian Centre for Occupational Health and Safety (CCOHS), 1999. Shovelling. Available online at: http://www.ccohs.ca, Accessed on 3 February 2014

Canadian Physiotherapy Association (CPA) 2009. The Scoop on Snow Shovelling: Physiotherapists Offer Advice for Safe Shovelling. Available online at: www.physiotherapyns.ca, Accessed on 5 January 2015

Dhananjay, S.B., Mohammed, R.K., 2013. Ergonomic Assessment Methods for the Evaluation of Hand Held Industrial Products: A Review. In: Proceedings of the World Congress on Engineering, London, U.K., Volume 1

Ellen, F., 2012. Pain Assessment for Older Adults. New York University College of Nursing, Available online at: www.ConsultGeriRN.org, Accessed on 6 May 2015

Fathallah, F.A., 2010. Musculoskeletal Disorders in Labor-intensive Agriculture. Applied Ergonomics, Volume 41(6), pp. 738–743

Garcia, E., 2011. A Tutorial on Correlation Coefficients. Available online at: www.Simmons.edu, Accessed on 3 May 2015

Gerstman, B.B., 2006. Correlation. Available online at: www.sjsu.edu/, Accessed 17 May 2015

Health and Safety Executive (HSE), 2004. Manual Handling Operations Regulations 1992 (as Amended). Guidance on Regulations, Available online at: www.hse.gov.uk, Accessed on 10 July 2015

Jack, G., 2015. Why Does Shovelling Snow Increase Risk of Heart Attacks?. Division of Cardiology, Mt. Sinai Hospital at University of Toronto, Available online at: www.science20.com/news_articles/, Accessed on 7 February 2015

Jang, J.S.R., Sun, C.T., 1996. Neuro-fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence. Prentice-Hall, Inc. ,New York

Javad, H., Reza, J., Ayoob, N., 2015. Fuzzy Rule Based Diagnostic System for Detecting the Lung Cancer Disease. Journal of Renewable Natural Resources, Volume 3(1), pp. 147–157

Kaj, H., 2014. Urban Snow Removal: Modelling and Relaxations. Department of Mathematics Linköping Institute of Technology, Sweden, Available online at: www.liu.diva-portal.org, Accessed on 15 June 2015

Kelli, M., 2011. Shovelling Snow Injures Thousands Each Year. Available online at: http://www.m.webmd.com/, Accessed on 15 June 2015

Kroemer, K.H.E., 1989. Cumulative Trauma Disorders: Their Recognition and Ergonomics Measures to Avoid Them. Applied Ergonomics, Volume 20(4), pp. 274–280

Kuorinka, I., Jonsson, B., Kilbom, A., 1987. Standardized Nordic Questionnaires for the Analysis of Musculoskeletal Symptoms. Applied Ergonomics, Volume 18, pp. 233–237

MathWorks, 2002. Fuzzy Logic Toolbox User’s Guide (version 2). Available online at: www.mathworks.com, Accessed on 12 September 2013

MathWorks, 2016. Trapezoidal-shaped Membership Function. Available online at: http://www.mathworks.com/help/fuzzy/trapmf.html, Accessed on 26 February 2016

Matthew, R., 2004. Advanced Research Methods in Psychology. Available online at: www.psychologyaustralia.homestead.com, Accessed on 12 September 2013

Mayilvaganan, M., Rajeswari, K., 2014 Health Care Analysis based on Fuzzy Logic Control System. International Journal of Computer Science Trends and Technology, Volume 2(4), pp. 119–122

Mikaela, C., 2011. Snow Shovelling May Put Health at Risk. Available online at: www.abcnews.go.com/Health/risks, Accessed on 15 March 2015

Monish, K.C., Neelanjana, B., 2015. A Fuzzy Logic–based Expert System for Determination of Health Risk Level of Patient. International Journal of Research in Engineering and Technology, Volume 4(5), pp. 261–267

Occupational Safety and Health Administration (OSHA), 2000. Ergonomics: The Study of Work. Available online at: www.osha.gov, Accessed on May 5, 2014

Pagano, R.R., 2004. Understanding Statistics in the Behavioral Sciences (7th ed.). Thompson/Wadsworth, Belmont, CA, USA

Ryan, T.L., Gholamreza, R., Douglas, G.R., 2013. Influence of Snow Shaft Configuration on Lumbosacral Biomechanics During a Load-lifting Task. Applied Ergonomics, Volume 42(2), pp. 234–238