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Design and Manufacturing of Wearable System for Assessment Risk Factor in Symmetric Lifting Task

Keshavarz Moghadam, Hossein | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 51462 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Firoozbakhsh, Keikhosro; Narimani, Roya
  7. Abstract:
  8. Low back disorders (LBD) is one of the most musculo-skeletal disorders in industrial environments in which it can impose to the society.Therefore, it is very important to reaserch the causes of LBDs, prevention methods and evaluation risk factor in lifting tasks in order to avoid the prevalence of LBDs in society. There is no doubt heavy lifting has a significant role in emerging of LBDs. Hence, many safety risk assessment tools have been made by researchers.Using assessment tools, we need to know the input parameters corrospending to the assessment tools. Input parameters in assessment tools have been measured in a way of traditional method or by expensive equipment in laboratories. On the other hand, wearable technologies has a dramatic growth in health improvement in all over the world, then it can be one of the applicable way as novel approach in prevention of diseases.The purpose of this study is design and manufacturing of the wearable system for assessment risk factor in symmetric lifting tasks via measuring NIOSH equation parameters. The benefit of the wearable system is portable, low cost and lack of affecting on natural lifting. Then Mean square error of the weight estimating of wearable system is 5.35(kg) and also this error for distance estimation is 8.36(cm). Finally, the mean square error of the Lifting_Index in which has magnitude between zero and one is 0.047. It means the proposed wearable system gives a new applicable method to the ergonomy
  9. Keywords:
  10. Low Back Pain ; National Institute for Occupational Safety and Health (NIOSH) Equation ; Assessment System ; Assessment Risk Factor in Lifting Tucks ; Wearable Sensor

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