Archives of Occupational Health | Volume 3 | Issue 2 | April 2019 | 339-45.

Citation: Samiei S, Alefi M, Alaei Z, Pourbabaki R. Risk Factors of Low Back Pain Using Adaptive Neuro-Fuzzy. Archives of Occupational Health. 2019; 3(2): 339-45. Article History: Received: 4 October 2018, Revised: 7 November 2018, Accepted: 7 December 2018 Copyright: ©2019 The Author(s); Published by Shahid Sadoughi University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1Msc, Department of Occupational Health Engineering, School of health, Tehran University of medical sciences, Tehran, Iran• *Corresponding Author: Reza Pourbabaki , Email:yasin.babaki@gmail.com, Tel: +98-913-2937194

Abstract

Background:

. Methods:

Results:

. Conclusion:

.

Keyword:

Introduction

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Figure 1. An example of the structure of the ANFIS model

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Samiei S, et al. | Archives of Occupational Health | Volume 3 | Issue 2 | April 2019 | 339-45.

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Methods

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Results

.

Table 1. Participant’s individual characteristics

Individual characteristics Number

(percentage)

Gender Male 35 (38/80) Female 55 (61/20)

Working hours per day Less than or equal to 8 h 43)47/80) Over 8 h 47 (52/20)

Resting hours per day Less than or equal to 8 h (93/30) 84 Over 8 h 6 (6/70)

Exercise hours per week Less than 3 h 74 (82/20) 3 h and over 16 (17/80)

Figure 2. The structure of the ANFIS model used in this study

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Table 2. The results of the linear regression test between

posterior posture and pain in the lower back region

Posture P- value

Repeated movements 0.03 Long-standing 0.03 Hands extension 0.07 Load carrying and displacement 0.02 Back rotation 0.06 Neck posture 0.74 Back bending 0.00

Table 3. Different structures of input into the ANFIS

Model Model input R2))

ANFIS ) ) ) ) 0.9117

Table 4. Statistical Parameters of the accuracy of the ANFIS

model in predicting pain in the lower extremity

RMSE MAE d MSE NMSE R2 Model

0.9257 0.40 0.9762 0.8568 0.0884 0.9117 1

Figure 3. Distribution of observational data and predicted data

:

:

:

:

Discussion and conclusion

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