Identification of a Human Hand Kinematics by Measuring and Merging of Nail-Based Finger Motions

Author(s):  
Hidenori Tani ◽  
Ryo Nozawa ◽  
Tomomichi Sugihara
Keyword(s):  
Author(s):  
Hyosang Moon ◽  
Nina P. Robson

The design of human interactive robotic systems requires additional considerations compared to conventional robotic designs to take into account human factors. In this paper, a recently developed linkage kinematic synthesis incorporating higher order motion constraints is utilized to the synthesis of a five degree of freedom serial TS linkage for human interactive applications. The T represents a universal two degrees-of-freedom shoulder, while the S defines a spherical three degrees-of-freedom wrist joint. The desired hand kinematics and its time derivatives can be obtained by a motion capture system as well as from the hand-object/environment contact geometries at two task locations. In order to determine the design parameters (i.e., locations of the base/shoulder and moving/wrist pivots, as well as the link length connecting these joints), position, velocity and acceleration constraint equations of the TS linkage are solved in the vicinity of the initial and the final reaching locations. The entire robotic joint trajectories are formulated via minimum jerk theory to closely approximate human natural hand profile with an elbow joint constraint. In this manner, the TS linkage system can be designed to guarantee to reproduce the natural human hand kinematics with the minimum amount of information about the desired hand kinematic specifications. The applicability of the proposed technique was verified by designing a TS linkage system from a captured human data, and then comparing the generated end-effector trajectory with the human hand motion trajectory, which show promising results.


Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 362
Author(s):  
Fei Fei ◽  
Sifan Xian ◽  
Xiaojian Xie ◽  
Changcheng Wu ◽  
Dehua Yang ◽  
...  

In traditional hand function assessment, patients and physicians always need to accomplish complex activities and rating tasks. This paper proposes a novel wearable glove system for hand function assessment. A sensing system consisting of 12 nine-axis inertial and magnetic unit (IMMU) sensors is used to obtain the acceleration, angular velocity, and geomagnetic orientation of human hand movements. A complementary filter algorithm is applied to calculate the angles of joints after sensor calibration. A virtual hand model is also developed to map with the glove system in the Unity platform. The experimental results show that this glove system can capture and reproduce human hand motions with high accuracy. This smart glove system is expected to reduce the complexity and time consumption of hand kinematics assessment.


2018 ◽  
Vol 21 (2) ◽  
pp. 113-128 ◽  
Author(s):  
Jumana Ma’touq ◽  
Tingli Hu ◽  
Sami Haddadin
Keyword(s):  

Author(s):  
Fai Chen Chen ◽  
Alain Favetto ◽  
Mehdi Mousavi ◽  
Elisa Ambrosio ◽  
Silvia Appendino ◽  
...  

2014 ◽  
Vol 4 (2) ◽  
pp. 245-249 ◽  
Author(s):  
Hisyam Abdul Rahman ◽  
Yeong Che Fai ◽  
Eileen Su Lee Ming
Keyword(s):  

1976 ◽  
Author(s):  
C. W. Suggs ◽  
John Wayne Mishoe

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