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Investigation of Hand Forces, Shoulder and Trunk Muscle Activation Patterns and EMG/force Ratios in Push and Pull ExertionsChow, Amy 27 September 2010 (has links)
When designing work tasks, one goal should be to enable postures that maximize the force capabilities of the workers while minimizing the overall muscular demands; however, little is known regarding specific shoulder tissue loads during pushing and pulling. This study quantitatively evaluated the effects of direction (anterior-posterior pushing and pulling), handle height (100 cm and 150 cm), handle orientation (vertical and horizontal), included elbow angle (extended and flexed) as well as personal factors (gender, mass and stature) on hand force magnitudes, shoulder and L5/S1 joint moments, normalized mean muscle activation and electromyography (EMG)/force ratios during two-handed maximal push and pull exertions. Twelve female and twelve male volunteers performed maximal voluntary isometric contractions under 10 push and pull experimental conditions that emulated industrial tasks. Hand force magnitudes, kinematic data and bilateral EMG of seven superficial shoulder and trunk muscles were collected. Results showed that direction had the greatest influence on dependent measures. Push exertions produced the greatest forces while also reducing L5/S1 extensor moments, shoulder moments with the 150 cm height and overall muscular demands (p < 0.0001). The 100 cm handle height generated the greatest forces (p < 0.0001) and reduced muscular demands (p < 0.05), but were associated with greater sagittal plane moments (p < 0.05). Females generated, on average, 67% of male forces in addition to incurring greater muscular demands (p < 0.05). The flexed elbows condition in conjunction with pushing produced greater forces with reduced overall muscular demands (p < 0.0001). Furthermore, horizontal handle orientation caused greater resultant moments at all joints (p <. 0.05) The results have important ergonomics implications for evaluating, designing or modifying workstations, tasks or equipment towards improved task performance and the prevention of musculoskeletal injuries and associated health care costs.
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Investigation of Hand Forces, Shoulder and Trunk Muscle Activation Patterns and EMG/force Ratios in Push and Pull ExertionsChow, Amy 27 September 2010 (has links)
When designing work tasks, one goal should be to enable postures that maximize the force capabilities of the workers while minimizing the overall muscular demands; however, little is known regarding specific shoulder tissue loads during pushing and pulling. This study quantitatively evaluated the effects of direction (anterior-posterior pushing and pulling), handle height (100 cm and 150 cm), handle orientation (vertical and horizontal), included elbow angle (extended and flexed) as well as personal factors (gender, mass and stature) on hand force magnitudes, shoulder and L5/S1 joint moments, normalized mean muscle activation and electromyography (EMG)/force ratios during two-handed maximal push and pull exertions. Twelve female and twelve male volunteers performed maximal voluntary isometric contractions under 10 push and pull experimental conditions that emulated industrial tasks. Hand force magnitudes, kinematic data and bilateral EMG of seven superficial shoulder and trunk muscles were collected. Results showed that direction had the greatest influence on dependent measures. Push exertions produced the greatest forces while also reducing L5/S1 extensor moments, shoulder moments with the 150 cm height and overall muscular demands (p < 0.0001). The 100 cm handle height generated the greatest forces (p < 0.0001) and reduced muscular demands (p < 0.05), but were associated with greater sagittal plane moments (p < 0.05). Females generated, on average, 67% of male forces in addition to incurring greater muscular demands (p < 0.05). The flexed elbows condition in conjunction with pushing produced greater forces with reduced overall muscular demands (p < 0.0001). Furthermore, horizontal handle orientation caused greater resultant moments at all joints (p <. 0.05) The results have important ergonomics implications for evaluating, designing or modifying workstations, tasks or equipment towards improved task performance and the prevention of musculoskeletal injuries and associated health care costs.
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DEVELOPMENT OF A NOVEL ERGONOMICS METHOD FOR DETERMINING MANUAL ARM STRENGTHLa Delfa, Nicholas Joseph 06 1900 (has links)
The primary purpose of this thesis was to develop, validate and implement a novel ergonomics tool for manual arm strength (MAS) prediction. In Chapter 2, an empirical study was conducted to: 1) fill in gaps in our MAS database, and 2) examine the relationships between MAS and shoulder/elbow moments, to help identify important sources of variance for future predictive modeling attempts. Chapter 3 focused on the evaluation of artificial neural network (ANN) and traditional multiple regression approaches for MAS prediction, and revealed that ANNs provided a more accurate and generalizable prediction of MAS for our specific dataset. Chapter 4 drew on the data and findings of Chapters 2 & 3, and described the development of the ‘Arm Force Field’ (AFF) method for MAS prediction. The AFF method can be used to predict the MAS for any percentage of the population, given only the simple inputs of force vector direction, hand location (relative to the right shoulder), and torso orientation. In Chapter 5, a theoretical examination of the relative changes in wrist strength, due to interacting forearm and wrist postures, was conducted. That study resulted in a set of regression equations that can be used to predict wrist strength correction factors in complex wrist and forearm postures, allowing for more accurate estimations of the limiting joint once the MAS is calculated. An example of the AFF method’s implementation is provided and discussed in Chapter 6. The four studies, presented in this thesis, add to the current knowledge related to strength prediction in ergonomics, and the AFF method has the potential to be easily integrated within digital human models, for more valid estimates of manual force capabilities for the population. / Dissertation / Doctor of Philosophy (PhD)
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