Work capacity assessment of Nigerian bricklayers

Ismaila, Salami Olasunkanmi; Oriolowo, Kolawole Taofik; Akanbi, O.G.

doi:10.5267/j.msl.2011.08.014

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…The energy expenditure of workers was found to fall under the heavy workload category as recommended by the Indian Council of Medical Research (2010).The heart rate of workers also indicated that their job fell under the heavy workload category as it exceeded 120 beats/min which ultimately puts adverse stress on the human body (Maiti, R., 2008). The mean BMI of the majority of workers exceeded the normal range, and this consequently lowers the physical work capacity of these workers (Ismaila, S., Oriolowo, K., et al, 2012;Xu, X., Mirka, G. A. et al, 2008). The results from the Analytical Hierarchy Process showed the physical workload as the most significant factor as the workers lift and carry 50 kg loads for 7.5 meters.…”

Section: Discussionmentioning

confidence: 98%

Evaluation and Prioritization of Factors Affecting Energy Expenditure of Workers Engaged in Manual Material Handling Using Analytical Hierarchy Process

Singh

Bilga

et al. 2015

IJAHP

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<p class="MainHeadings">The present study aimed to evaluate energy expenditure of workers engaged in a manual material handling task .The various factors/sub factors influencing energy expenditure with physical impact on the human body were prioritized in terms of weight values by using the Analytical Hierarchy Process. The study included a sample of sixty male workers with a mean age ± SD of 40.34 ± 7.65, data with respect to their job activity and physical characteristics were collected using a validated questionnaire. The results showed an average working heart rate ± SD of 124.5±12.24 beats/min and average energy expenditure ± SD of 3370.33 ± 283.86 kcal; these are clear indicators of strenuous activity. The results of the AHP evaluation showed physical workload (PW) as the most important factor followed by physical work capacity (PWC), type of activity (TOA), organizational factors (OF) and personal factors (PF) with weight values of 0.454139, 0.252781, 0.129274, 0.125318 and 0.038488 respectively. The study concluded with prioritization of various factors contributing to a high rate of energy expenditure which may lead to overexertion and musculoskeletal injuries. The findings indicated an utmost need to redesign job content with the addition of some periods of break time in order for the body to recover from the excessive energy expenditure.</p>

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Section: Discussionmentioning

confidence: 98%

Evaluation and Prioritization of Factors Affecting Energy Expenditure of Workers Engaged in Manual Material Handling Using Analytical Hierarchy Process

Singh

Bilga

et al. 2015

IJAHP

View full text Add to dashboard Cite

show abstract

“…The following data were obtained from the subjects after the purpose of study has been thoroughly explained to them and they all gave their consents; age in years, heart beat rate per minute at rest and while working, volume of oxygen consumption while working (VO 2w ). The heart beat rate per minute for each worker was measured as described by [13]. Measurement of heart beat rate per minute while at rest (HR r ) and when working (HR w ) were taken three times for each worker and the mean value for each were recorded as the heart beat rate per minute while at rest and while working respectively.…”

Section: Methodsmentioning

confidence: 99%

“…As activities of ergonomists are becoming more in Nigeria, research works are being conducted in order to solve workplace problems that are associated with manual tasks; e.g. [12] and [13]. However the case of oil and gas industry in Nigeria seems not to have been explored sufficiently perhaps due to high level of automation in the sector.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of The Impact Of Manual Tasks On Workers In An Oil Servicing Company

Kolawole¹

2014

IOSRJEN

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Manual task activities have been found to contribute to a number of musculoskeletal disorders such as sprain and strain of the muscles and low back pain among others. This study examined the impact of manual tasks on workers in an oil and gas company in Nigeria. Twenty six manual task workers participated in the study and their physiological responses during work were evaluated through heart beat rate per minute and volume of oxygen consumption. Relative aerobic strain (RAS) for each of the 26 subjects was calculated through the volume of oxygen consumption as RAS 1 and through the heart beat rate per minute as RAS 2. The results showed that based on RAS 1 and RAS 2, 8 or 30.77% and 9 or 34.62% out of the 26 workers have the impact of the job within their capacity respectively while 18 or 69.23% and 17 (65.38%) have the task beyond their capability based on RAS 1 and RAS 2 respectively. In order to ensure the safety and comfort of the workers, it may be necessary to assess the physical fitness of an intending manual task worker before employment

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Predicting relative and working heart rates of bricklaying jobs using neural network

Ismaila

Oriolowo

Akanbi

2013

OER

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Background Many ways have been adopted in measuring workers', responses to manual tasks in order to appraise the incompatibility of work demands to the capabilities of the workers. Heart rate is commonly used to estimate the energy expenditure or physical strain in physically demanding job. Objective: The main purpose of this study was to build a prediction model using the neural network to reflect the effects of age, body height, body mass, and resting heart rate on the working heart rate (HWorking) and % relative heart rate (%RHR) of bricklayers. Methods: A neural network in SPSS 16.0 was applied to identify the importance of the inputs (age, body height, body mass, resting heart rate) in predicting the outputs (working heart rate and % RHR) of a function. Results: The results show that the mean % relative heart rate (RHR) was 57.4%. The mean working heart rate was 120.8 bpm and that of resting heart rate was 68.6 bpm. It was also shown that the neural network could be trained to predict HWorking and % RHR. This also demonstrates that there is a non-linear relationship between the age, body height, body mass, resting heart rate, working heart rate and % RHR. The neural network results for the HWorking and % RHR were dominated by resting heart rate, followed by body mass, age and body height in that order. The predicted values of % RHR and HWorking did not differ significantly from the actual values though the relationships were non-linear. Conclusions: The neural network might be used to predict the % RHR and HWorking of bricklayers in Nigeria given age, body height, body mass and resting heart rate.

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Work capacity assessment of Nigerian bricklayers

Cited by 4 publications

References 13 publications

Evaluation and Prioritization of Factors Affecting Energy Expenditure of Workers Engaged in Manual Material Handling Using Analytical Hierarchy Process

Evaluation and Prioritization of Factors Affecting Energy Expenditure of Workers Engaged in Manual Material Handling Using Analytical Hierarchy Process

Evaluation of The Impact Of Manual Tasks On Workers In An Oil Servicing Company

Predicting relative and working heart rates of bricklaying jobs using neural network

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