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Prediction of anatomically and biomechanically feasible precision grip posture of the human hand based on minimization of muscle effort.
Nakajima, Takayuki; Asami, Yuki; Endo, Yui; Tada, Mitsunori; Ogihara, Naomichi.
Affiliation
  • Nakajima T; Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Yokohama, 223-8522, Japan.
  • Asami Y; Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Yokohama, 223-8522, Japan.
  • Endo Y; Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, 135-0064, Japan.
  • Tada M; Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, 135-0064, Japan.
  • Ogihara N; Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Yokohama, 223-8522, Japan. ogihara@bs.s.u-tokyo.ac.jp.
Sci Rep ; 12(1): 13247, 2022 08 02.
Article in En | MEDLINE | ID: mdl-35918451
ABSTRACT
We developed a method to estimate a biomechanically feasible precision grip posture of the human hand for a given object based on a minimization of the muscle effort. The hand musculoskeletal model was constructed as a chain of 21 rigid links with 37 intrinsic and extrinsic muscles. To grasp an object, the static force and moment equilibrium condition of the object, force balance between the muscle and fingertip forces, and static frictional conditions must be satisfied. We calculated the hand posture, fingertip forces, and muscle activation signals for a given object to minimize the square sum of the muscle activations while satisfying the above kinetic constraints using an evolutionary optimization technique. To evaluate the estimated hand posture and fingertip forces, a wireless fingertip force-sensing device with two six-axis load cells was developed. When grasping the object, the fingertip forces and hand posture were experimentally measured to compare with the corresponding estimated values. The estimated hand postures and fingertip forces were in reasonable agreement to the corresponding measured data, indicating that the proposed hand posture estimation method based on the minimization of muscle effort is effective for the virtual ergonomic assessment of a handheld product.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Hand Strength / Hand Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Japan

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Hand Strength / Hand Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Japan