Modeling of predictive muscular strength for sustained one-handed carrying task.

Abstract

Manual materials handling (MMH) tasks are common. They are considered major contributors of musculoskeletal injuries and are the sources of financial burden for industries in terms of lost work days and worker compensation costs. One-handed carrying is common and could result in arm fatigue. The purpose of this study was to establish predictive models for one-handed carrying strength considering weight handed and handedness conditions. Twenty male subjects were recruited for the study. The subject carried a weight of 6 or 12 kg using either dominant or non-dominant hand lasting a time period of 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, or 4 minutes. The results showed that handedness (p < 0.0001), weight (p < 0.05), and time period (p < 0.0001) were all significant factors affecting single arm carrying strength. Predictive models of single arm carrying strength were established under handedness and weight conditions. The MADs of these models ranged from 0.39 to 2.19 kgf. The exponential function based predictive models may be adopted to describe the single arm carrying strength with reasonable predictive errors. The trend of the carrying strength after carrying a load for a certain period may be employed to describe muscular fatigue for sustained carrying tasks.