Biomechanical investigation of tasks concerning manual materials handling using response surface methodology

Author:

Adhaye Amit M.,Jolhe Dhananjay A.,Loyte Akshay R.,Devarajan Yuvarajan,Thanappan Subash

Abstract

AbstractIn typical manual material handling, the variations in walking pattern are decided by various factors, such as load being handled, frequency of handling, walking surface, etc. Traditional gait analysis protocols commonly evaluate individual factor within specified ranges associated with particular activities or pathologies. However, existing literature underscores the concurrent impact of multiple factors on gait. This study identifies five pivotal factors—walking speed, surface slope, load carried, carrying method, and footwear—as contributors to gait alterations. To address risk factors in manual material handling activities, we propose a unique design-of-experiment-based approach for multi-task gait analysis. Unraveling the relationship between manual handling attributes and human gait holds paramount importance in formulating effective intervention strategies. We optimized the five input factors across a cohort of 15 healthy male participants by employing a face-centered central composite design experimentation. A total of 29 input factor combinations were tested, yielding a comprehensive dataset encompassing 18 kinematic gait parameters (such as cadence, step length etc., measured using inertial measurement system), the isolated impacts of factors, and the interplay of two-factor interactions with corresponding responses. The results illuminate the optimal scenarios of input factors that enhance individual gait performance—these include wearing appropriate footwear, employing a backpack for load carriage, and maintaining a moderate walking pace on a medium slope with minimal load. The study identifies walking speed and load magnitude as primary influencers of gait mechanics, followed by the chosen carrying method. In consequence, the insights gained advocate for the refinement of manual material handling tasks based on the outcomes, effectively mitigating the risk of musculoskeletal disorders by suggesting the interventions for posture correction.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference40 articles.

1. Ingber, D. E. The architecture of life. Sci. Am. 278(1), 48–57 (1998).

2. Kumar, S. Theories of musculoskeletal injury causation. Ergonomics 44(1), 17–47 (2001).

3. Devarajan, Y., Munuswamy, D., Nagappan, B., & Choubey, G. Study on the effect on combining long-chain additive with neat bio-diesel fueled engine to examine its ignition characteristics. Fuel. 279, 118400. https://doi.org/10.1016/j.fuel.2020.118400 (2020).

4. Manjunatha, R., Kiran, D. & Thankappan, K. R. Sickness absenteeism, morbidity and workplace injuries among iron and steel workers—A cross sectional study from Karnataka, Southern India. Australas. Med. J. 4(3), 143–147 (2011).

5. Paul, S. P., Mitra, K., Chakrabarty, A. & Das, D. K. Prevalence of musculoskeletal disorders and its correlates among agricultural workers in Bhatar block of Purba Bardhaman District, West Bengal. IOSR J. Dent. Med. Sci. 18(1), 22–28 (2019).

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