Investigation on the Cooperative Grasping Capabilities of Human Thumb and Index Finger
Xiaojing Chen, Zhiguo Li, Yuqing Wang, Jizhan Liu, Dezong Zhao
Abstract
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Xiaojing Chen, Zhiguo Li, Yuqing Wang, Jizhan Liu, Dezong Zhao
Abstract
Open-access reader
The maximum cooperative grasping mass and diameter of the human thumb and index finger were investigated by 7560 grasp-release trials on various masses of solid cylinders and various sizes of hollow rings. The maximum grasping mass of the participants’ thumb-index finger depended on gender, age and the sum of thumb-index finger lengths (P 0.05). The maximum grasping diameter of the participants’ thumb-index finger depended on the age, sum of thumb-index finger lengths and ratio of index finger to thumb length (P 0.05). There was a nonlinear regression model for the dependence of the maximum grasping mass on gender, age and the sum of thumb-index finger lengths and another nonlinear regression model for the dependence of the maximum grasping diameter on the age, sum of thumb-index finger lengths and ratio of index finger to thumb length. Two regression models were useful in the optimal size design of robotic hands intending to replicate thumb-index finger grasping ability. This research can help to define not only a reasonable grasp mass and size for a bionic robotic hand, but also the requirements for hand rehabilitation.
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The maximum cooperative grasping mass and diameter of the human thumb and index finger were investigated by 7560 grasp-release trials on various masses of solid cylinders and various sizes of hollow rings. The maximum grasping mass of the participants’ thumb-index finger depended on gender, age and the sum of thumb-index finger lengths (P 0.05). The maximum grasping diameter of the participants’ thumb-index finger depended on the age, sum of thumb-index finger lengths and ratio of index finger to thumb length (P 0.05). There was a nonlinear regression model for the dependence of the maximum grasping mass on gender, age and the sum of thumb-index finger lengths and another nonlinear regression model for the dependence of the maximum grasping diameter on the age, sum of thumb-index finger lengths and ratio of index finger to thumb length. Two regression models were useful in the optimal size design of robotic hands intending to replicate thumb-index finger grasping ability. This research can help to define not only a reasonable grasp mass and size for a bionic robotic hand, but also the requirements for hand rehabilitation.
Key concepts: Thumb, Index finger, GRASP, Middle finger, Index (typography), Computer science, Little finger, Ring finger