ArticleScientific reports2022
Prediction of anatomically and biomechanically feasible precision grip posture of the human hand based on minimization of muscle effort.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Human Posture Estimation: A Systematic Review on Force-Based Methods-Analyzing the Differences in Required Expertise and Result Benefits for Their Utilization.Sensors (Basel, Switzerland) · 2023Pooled it
- Force prediction in the cylindrical grip for a model of hand prosthesis.Scientific reports · 2023Article
- SenGlove-A Modular Wearable Device to Measure Kinematic Parameters of The Human Hand.Bioengineering (Basel, Switzerland) · 2023Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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