• DocumentCode
    1784430
  • Title

    Lift-up motion generation of nursing-care assistant robot based on human muscle force and body softness estimation

  • Author

    Ming Ding ; Ikeura, Ryojun ; Mori, Yojiro ; Mukai, Toshiharu ; Hosoe, Shigeyuki

  • Author_Institution
    Dept. of Mech. Sci. & Eng., Nagoya Univ., Nagoya, Japan
  • fYear
    2014
  • fDate
    8-11 July 2014
  • Firstpage
    1302
  • Lastpage
    1307
  • Abstract
    In our research center, we have developed a nursing-care assistant robot. This robot can lift up and transfer patient between bed and wheelchair using two human like arms. In this research, in order to generate comfortable lift-up motion automatically for this robot, we proposed a new method by reducing patient´s load and pain feeling during lifting-up. We developed a musculoskeletal model to estimate muscle force, which shows the load of human body. A stiffness sensor was also developed to measure the softness distribution of human body. Contact human body on soft place can make people feel less pain. In simulation, we estimate human posture and comfortable robot motion by minimizing muscle force and contacting human body on the softest places. In experiments, the measured subjects´ postures were compared with the estimated value using the estimated motions. Measured postures were very close to simulation, which shows the effectiveness of proposed method.
  • Keywords
    manipulators; medical robotics; patient care; body softness estimation; human like arms; human muscle force; lift-up motion generation; muscle force estimation; musculoskeletal model; nursing-care assistant robot; patient load reduction; patient pain feeling reduction; softness distribution; stiffness sensor; Biological system modeling; Force; Joints; Manipulators; Muscles; Robot sensing systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Intelligent Mechatronics (AIM), 2014 IEEE/ASME International Conference on
  • Conference_Location
    Besacon
  • Type

    conf

  • DOI
    10.1109/AIM.2014.6878262
  • Filename
    6878262