How To Calculate Time To Fatigue
J Phys Ther Sci. 2015 Jul; 27(7): 2323–2326.
Muscle action, time to fatigue, and maximum task duration at different levels of production standard time
Nurhayati Mohd Nur
1) Department of Mechanical Engineering science, University of Malaya, Malaysia
Siti Zawiah Md Dawal
1) Section of Mechanical Technology, University of Malaya, Malaysia
Mahidzal Dahari
one) Department of Mechanical Engineering, Academy of Malaya, Malaysia
Junedah Sanusi
two) Department of Anatomy, University of Malaya, Malaysia
Received 2015 Mar 9; Accepted 2015 Apr 16.
Abstract
[Purpose] This study investigated the variations in muscle fatigue, time to fatigue, and maximum chore elapsing at unlike levels of production standard time. [Methods] Twenty subjects performed repetitive tasks at three different levels of production standard fourth dimension corresponding to "normal", "hard" and "very hard". Surface electromyography was used to measure out the musculus activity. [Results] The results showed that muscle action was significantly affected by the production standard fourth dimension level. Muscle activity increased twice in percentage as the production standard fourth dimension shifted from hard to very hard (half-dozen.9% vs. 12.9%). The musculus activeness increased over fourth dimension, indicating musculus fatigue. The muscle fatigue rate increased for the harder production standard time (Difficult: 0.105; Very hard: 0.115), which indicated the associated higher take a chance of piece of work-related musculoskeletal disorders. Musculus fatigue was also plant to occur earlier for hard and very difficult product standard times. [Conclusion] It is recommended that the maximum task duration should not exceed five.half dozen, 2.9, and ii.2 hours for normal, difficult, and very difficult production standard times, respectively, in order to maintain work performance and minimize the risk of work-related musculoskeletal disorders.
Key words: Muscle activeness, Muscle fatigue, Chore duration
INTRODUCTION
The term "musculoskeletal disorders" (MSDs) refers to conditions that affect muscles, nerves, tendons, and other soft tissues1 ). MSDs are common amongst the working population. Work-related musculoskeletal disorders (WMSDs) accept go a major social concern, which bear upon a company'due south bottom linetwo , 3 ). Issues related to WMSDs pose a meaning threat to employees' health and well-being across a wide range of industries and occupations4 , v , 6 ). Workers involved in static low loads or repetitive work frequently have complaints associated with WMSD7 , 8 , nine ). In France, it is estimated that upper limb MSDs account for approximately two-thirds of the reported work-related disorders10 ). In Malaysia, the upper limb is the most commonly affected region in piece of work-related injuries, with 22,978 cases constituting 39.five% of the full in the year 201011 ). Therefore, there is a critical need to forestall WMSDs among workers with the use of ergonomic interventions12 ) and by integrating ergonomic measures for upper extremities in the assembly line design13 ).
Most tasks in the manufacturing industry, particularly associates tasks, are repetitive and performed manually14 , xv ). The tasks get more repetitive with harder production standard times and may predispose workers to a higher risk for WMSDs. The muscle fatigue rate may besides vary according to the levels of the production standard fourth dimension. Hence, the ability to assign maximum task elapsing according to the levels of the product standard fourth dimension may reduce the adventure of WMSDs. However, there is a lack of established references concerning variations in muscle fatigue, fourth dimension to fatigue, and maximum task elapsing at different levels of product standard time. Therefore, this is a timely investigation of the variations in muscle fatigue at dissimilar levels of product standard time to predict the time to fatigue and maximum task duration, which are important factors in job design for minimizing the risk of WMSDs.
SUBJECTS AND METHODS
Twenty industrial workers (10 females and 10 males) were recruited to participate in this study. The subjects were between the ages of 22 and 45 years (thirty.ix±vii.711). None of the recruited participants had a history of any musculoskeletal injuries. The subjects gave their written consent prior to study initiation. The written report was approved by the local Ethics Commission. Muscle activity was recorded using Noraxon Surface Electromyography (EMG) and Telemyo 2400 Gen2 Telemetric Existent Time 8 Channel SEMG System (Noraxon, INC, Usa) with disposable Ag/AgCl pregelled electrodes. The subjects' peel was cleaned thoroughly and prepared before electrode placement. The surface electrodes were fastened to the belly of the forearm muscles bilaterally. The subjects were then instructed to adopt a comfy sitting posture, and the sitting height was adjusted individually so that the subjects' knees were flexed to 90°. The working height was standardized by placing the table surface 5 cm beneath the position of the wrist, with the elbow flexed to 90°16 ).
The subjects were instructed to perform a maximum voluntary contraction (MVC) job as soon every bit the signals from all sensors were stable. The subjects performed the MVC task three times in the seated position; the duration of each task was approximately ten seconds, with 30 seconds of rest provided in between contractions. The 30 seconds of rest served as recovery time after each task. A stable forearm back up was arranged, and transmission resistance was used. The MVC measurement process used in this study was based on Konrad'southward guidelines17 ). MVC refers to the highest EMG amplitude obtained from the iii recordings and is expressed equally the percentage of MVC (%MVC). The MVC was used to normalize the surface EMG signals that were recorded during the serial of experimental tasks.
The subjects were required to perform the experimental tasks afterwards familiarizing themselves with the tasks for 30 minutes. They performed the tasks according to assigned production standard times over a one-60 minutes period for each production standard time. Muscle activity was recorded using surface EMG. The tasks involved repetitive assembly actions, like to the actual industrial associates task. The subjects were given ii types of components: plastic clips and plastic foam rings. These components were placed into a polybox and plastic container, respectively. The subjects were instructed to assemble the ring foam onto the plastic clip using a jig, which pushes the foam onto the prune. The subjects performed the tasks according to the production standard times assigned to them. The production standard times used in the experimental tasks were 100% normal standard time (normal, PSN), 126% normal standard fourth dimension (hard, PSH) and 140% normal standard time (Very hard, PSVH). The normal standard time was determined to exist five southward from the Methods-Time-Measurement (MTM) assay, and the task was categorized as a highly repetitive light task18 ).
EMG signals were recorded from four forearm muscles: the flexor carpi radialis (FCR) and extensor carpi radialis (ECR) on the correct and left artillery. Raw EMG signals were sampled during the exam contraction with a sample frequency of 1,500 Hz and were band-pass filtered (20–400 Hz). Information were continuously recorded with the Telemyo 2400T G2 Telemetry EMG Organization. The EMG data were normalized with MVC to obtain the root-mean-square (RMS, %MVC). The RMS value corresponds to the square root of the boilerplate power of the raw EMG signal over a given menstruation of timexix ). The normalized RMS (%MVC) was averaged for every v minutes. In this report, the mean value of the normalized RMS represents the muscle activeness, while the charge per unit of muscle fatigue is represented by the linear regression gradient of the normalized RMS.
RESULTS
The mean value and standard deviation of the normalized RMS for all muscles are summarized in Table 1.
Tabular array one.
Hateful and standard deviation of normalized RMS
| Production standard | FCRR | FCRL | ECRR | ECRL | ||||
|---|---|---|---|---|---|---|---|---|
| | | | | |||||
| Mean | SD | Mean | SD | Mean | SD | Mean | SD | |
| PSN | eight.viii* | 1.8 | eleven.0* | two.8 | 10.4* | 2.iii | xi.4* | iii.4 |
| PSH | 9.6* | 2.2 | 11.9* | two.5 | xi.0* | 2.v | 11.9* | 3.4 |
| PSVH | 9.ix* | 2.4 | 12.four* | 2.ix | eleven.9* | 3.one | 12.seven* | iii.five |
*Production standard time has a pregnant effect on the hateful RMS for all muscles, p<0.05.
Musculus activity increased with harder production times. PSVH had the highest RMS value for all muscles. The highest RMS value was obtained for ECR-left (ECRL) followed by FCR-left (FCRL), ECR-correct (ECRR), and FCR-correct (FCRR). Repeated measures ANOVA was conducted to investigate the effect of production standard time on muscle activity, and the results revealed that the product standard time has a meaning upshot on the hateful RMS (musculus action) for all muscles (Table 1).
Figure 1 presents the percentage of increment in musculus activity at different levels of production standard times. The increment in musculus activeness for a hard production standard time was in the iv.9–viii.vii% range. The provision of an assigned very hard product standard time showed that the muscle activeness was college than that for an assigned normal production standard time and hard production standard time, with an increment in the eleven.3–14.7% and 3.4–7.8% ranges, respectively, depending on the blazon of muscles. On average, the musculus activity increased half-dozen.9% for the hard production standard times and 12.nine% for the very hard production standard times.
Percentage of increase in muscle activity for different levels of production standard time
The muscle fatigue charge per unit was adamant from the normalized RMS versus time, and the values are summarized in Tabular array two. Information technology can exist seen that the muscle fatigue charge per unit is college for harder production standard times.
Table two.
Musculus fatigue charge per unit
| Production standard | Musculus fatigue rate | |||
|---|---|---|---|---|
| | ||||
| FCRR | FCRL | ECRR | ECRL | |
| PSN | 0.045 | 0.061 | 0.088 | 0.059 |
| PSH | 0.046 | 0.086 | 0.092 | 0.105 |
| PSVH | 0.050 | 0.088 | 0.103 | 0.115 |
Based on the prediction of time to fatigue at 15%MVC, it was found that muscle fatigue occurs earlier for hard and very hard product standard times compared to the normal production standard time. The time to fatigue at xv%MVC is predicted to exist 5.6 hours. ii.9 hours, and 2.ii hours for continuous piece of work at normal, hard, and very difficult production standard times, respectively.
DISCUSSION
Musculus activity, expressed as the RMS value (%MVC), was observed to increment significantly with harder production standard times. The results of this study reveal that the average muscle activity increases by 6.nine% and 12.9% for hard and very hard product standard times, respectively, whereby the values are determined relative to the normal product standard fourth dimension. This indicates that the muscle activity is twice its initial value as the product standard time shifts from difficult to very hard. This issue is consistent with the findings of previous studies, which reported that an increase in work pace leads to an increase in muscle activeness20 , 21 ).
The maximum muscle activity occurred at the ECRL, with a value of 12.7%MVC at 140% of the normal standard fourth dimension. The ECRL muscle exhibited the highest muscle activeness, followed past the FCRL, ECRR, and FCRR. The results are likewise consistent with the findings of previous studies, which were focused on repetitive hand tasks, during which the forearm extensor musculus activity increases with respect to fourth dimension20 , 21 ).
Information technology was found that the RMS value increases with respect to time for all muscles, which signifies the development of musculus fatigue. The highest indication of muscle fatigue was detected in the ECRL. The left-sided muscles were constitute to exist more active compared to the right-sided muscles, which was possibly due to all subjects beingness right-handed. Moreover, the left-sided muscles are used to grip and concord the components while carrying out a task, and thus they have a greater number of active motor units22 ). The greater the motor unit recruitment and firing rate, the greater is the generated force23 ). The force generated shows a rapid turn down when the muscles are stimulated continuously at a frequency shut to the maximal force and leads to muscle fatigue24 ). Therefore, these findings explained the highest indication of musculus fatigue detected in the left extensor muscle.
Musculus activeness was also constitute to increment over time for different production standard times. The result indicates musculus fatigue at different levels of production standard time. This upshot is in agreement with that of previous studies, which found that increment of muscle activity over time indicated a sign of muscle fatigue25 ). In improver, muscle fatigue rates were found to be higher every bit the production standard time became harder. The result showed that college muscle activity corresponds to a higher muscle fatigue charge per unit26 ). Manifestation of muscle fatigue was detected during the ane-hour chore elapsing, and the consequence was in understanding with previous studies, which reported musculus fatigue and reduction in worker performance due to WMSDs associated with tasks that were one 60 minutes27 ) or less28 ) in duration. Previous studies also found that muscle fatigue develops over time29 ), and the aggregating of musculus fatigue caused functional disability resulting in musculoskeletal disordersthirty ). Therefore, long-term effects and longitudinal studies are required to further investigate WMSDs. Even so, the power to control muscle fatigue, which is an indicator of WMSDs, will help to minimize the risk of developing WMSDs and maintain worker performance.
In general, information technology can exist deduced that the musculus fatigue rate is higher for harder production standard times due to the shorter job time and higher frequency of movement. The muscle fatigue rate increases with a corresponding increase in musculus activeness. An increment in muscle activity indicates the development of muscle fatigue. These results are in understanding with the results of previous studies in which an increase in muscle activity resulted in an increase in musculus fatigue and WMSD risks25 , 30 ).
The maximum muscle activeness is institute to be below 15% of the MVC. Rohmert31 ) suggested that muscle fatigue occurs when the muscular activity exceeds 15%MVC. Notwithstanding, contempo studies reported that muscle fatigue and fatigue-related changes occur at lower force levels32 ). To date, at that place is no consensus regarding the acceptable levels of muscle fatigue at the workplace, and fatigue risks are withal debated33 ). The fourth dimension to fatigue in this written report was predicted at 15%MVC, and information technology was establish that fourth dimension to fatigue occurs earlier for harder product standard times compared to the normal production standard time. The time to fatigue at 15%MVC is predicted later on 5.6, 2.9, and ii.2 hours for normal, difficult, and very difficult production standard times, respectively, assuming that the workers perform the repetitive tasks continuously.
In the manufacturing industry, workers are usually given rest breaks after a certain task duration. Previous studies suggested that recovery from muscle fatigue tin be accomplished with appropriate rest breaks, such every bit a one-60 minutes break34 , 35 ). Shin and Kim36 ) suggested that an advisable residual intermission can be used equally an early on intervention to preclude muscle fatigue at the workplace. Meanwhile, other studies accept shown that setting a limit for the task duration is more useful than improving interruption allowance37 ). Based on these findings, we advise that the maximum task duration for normal, hard, and very difficult production standard times should be limited before time to fatigue. Hence, the maximum job duration should not exceed 5.half dozen, 2.nine, and ii.2 hours for normal, hard, and very difficult production standard times, respectively. The maximum chore duration for unlike levels of production standard fourth dimension is an important gene in the work design for sustaining the desired work performance and for minimizing the adventure of developing WMSDs.
Acknowledgments
This work was financially supported by the Ministry of Higher Didactics Malaysia under the High Impact Enquiry Grant UM.C/HIR/MOHE/ENG/35 (D000035) and UM.C/HIR/MOHE/ENG/23 (D000023).
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4540872/
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