• DocumentCode
    2554264
  • Title

    Applying TAFEI method to orthopaedic robot system´s requirements analysis

  • Author

    Kuang, S.L. ; Hu, L. ; Zhang, S.T. ; Gao, D.H.

  • Author_Institution
    Dept. of Ind. Eng., Shandong Inst. of Bus. & Technol., Yantai, China
  • fYear
    2009
  • fDate
    21-23 Oct. 2009
  • Firstpage
    66
  • Lastpage
    70
  • Abstract
    Medical robot can enhance surgery through improved precision, stability, and dexterity, which has brought great benefits for patients. However, it yields a series of disadvantages to the surgeons, such as the bad eye-hand coordination, the ill-designed workstations etc. All these disadvantages can cause human error during operations, and human error is considered to be the major contributing factor of medical accidents. To improve the safety of the orthopaedic robot system, the task analysis for human error identification (TAFEI) method is used to predict the human error during the requirements analysis stage. By analyzing the potential undesired operations, which will influence the usability of the system, the protection measures are proposed to reduce the errors of the applied system. It is concluded that this method is feasible during the requirements analysis stage of the design.
  • Keywords
    human-robot interaction; medical robotics; orthopaedics; precision engineering; stability; task analysis; TAFEI method; dexterity; human error; human error identification method; medical accident; medical robot; orthopaedic robot systems requirements analysis; precision; stability; task analysis; Accidents; Error analysis; Humans; Medical robotics; Orthopedic surgery; Robot kinematics; Safety; Stability; Usability; Workstations; hierarchical task analysis; human error; orthopaedic robot system; requirements analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3671-2
  • Electronic_ISBN
    978-1-4244-3672-9
  • Type

    conf

  • DOI
    10.1109/ICIEEM.2009.5344634
  • Filename
    5344634