Article
Effects of Pause Design on the Decline in Pulling Effort
and the Evaluation of Perceived Effort in Pulling Tasks
Cannan Yi
1
, Fan Tang
1
, Kaiway Li
1,2,
* , Hong Hu
1,
*, Huali Zuo
1
and Caijun Zhao
1
Citation: Yi, C.; Tang, F.; Li, K.W.;
Hu, H.; Zuo, H.; Zhao, C. Effects of
Pause Design on the Decline in Pulling
Effort and the Evaluation of Perceived
Effort in Pulling Tasks. Appl. Sci.
2021, 11, 12022. https://doi.org/
10.3390/app112412022
Academic Editor: João Carlos de
Oliveira Matias
Received: 18 November 2021
Accepted: 15 December 2021
Published: 17 December 2021
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4.0/).
1
Hunan Institute of Technology, School of Safety and Management Engineering, Hengyang 421102, China;
cannanyi@hnit.edu.cn (C.Y.); Fantang@hnit.edu.cn (F.T.); Hualizuo@hnit.edu.cn (H.Z.);
caijunzhao@hnit.edu.cn (C.Z.)
2
Department of Industrial Management, Chung Hua University, Hsin-Chu 300, Taiwan
* Correspondence: kai@chu.edu.tw (K.L.); Honghu@hnit.edu.cn (H.H.)
Abstract:
Pulling is one of the manual material handling activities that could lead to work-related
musculoskeletal disorders. The objectives of this study were to explore the development of muscular
fatigue when performing intermittent pulling tasks and to establish models to predict the pull
strength decrease due to performing the tasks. A simulated truck pulling experiment was conducted.
Eleven healthy male adults participated. The participants pulled a handle with a load of 40 kg, which
resulted in a pulling force of approximately 123 N. The pulling tasks lasted for 9 or 12 min with one,
two, or three pauses embedded. The total time period of the embedded pauses was 3 min. The pull
strength after each pull and rest was measured. Ratings of the perceived exertion on body parts after
each pull were also recorded. The results showed insignificant differences regarding the development
of muscular fatigue related to rest frequency. We found that the development of muscular fatigue for
pulling tasks with embedded pauses was significantly slower than that for continuous pulls. The
forearm had a higher CR-10 score than the other body parts indicating that the forearm was the body
part suffering early muscle fatigue. An exponential model was developed to predict the pull strength
of the pulling tasks with embedded pauses. This model may be used to assess the developing of
muscular fatigue for pulling tasks.
Keywords: musculoskeletal disorders; pulling tasks; muscular fatigue; pull strength
1. Introduction
Musculoskeletal disorders (MSDs) have been a significant burden for both workers and
industries worldwide. In 2017, there were 1.3 billion MSD cases and 138.7 million disability-
adjusted life years, a measure of lifetime with disability and the time lost due to premature
mortality, in the world [1]. These numbers highlight the significance of MSD problems.
There is a huge amount of literature discussing work-related MSD problems. Manual
materials handling has been blamed as the leading causes for those problems at work-
places [
2
]. MSDs occur primarily because the repetitive and/or forceful loading on the
joints and body tissues while performing physical demanding tasks, such as lifting, lower-
ing, pushing, pulling, carrying, and so on [
3
–
5
]. Lower back, shoulder, and wrist are the
primary body parts that suffer from MSDs [6–9].
In order to reduce lifting, lowering, and carrying, carts, trolleys, and other material
handling aids are widely used. These aids may be operated manually or powered. Powered
material handling aids, such as forklift trucks, are used to handle materials in batches or
are very heavy, and may not be handled by a person manually. Manual material handling
aids, such as carts and trolleys, are used to handle materials in relatively small amount.
However, using manual material handling aids, such as a pallet jack, to handle a large
amount of materials or heavy loads are also common.
Pushing or pulling is normally required to maneuver those material handling aids.
The literature has shown that about 10% of all working processes in the automotive industry
Appl. Sci. 2021, 11, 12022. https://doi.org/10.3390/app112412022 https://www.mdpi.com/journal/applsci
