Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164)
DOI: 10.1109/robot.2001.932807
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Proposal of a SkilMate finger for EVA gloves

Abstract: It has been pointed out that the hard structure of an EVA glove deteriorates e±ciency of tasks in the space environment. We also found a claim that an EVA glove did not allow an astronaut to acquire contact information at the¯ngertips. In the study, we proposed a SkilMate Hand for space EVA gloves which has both a tactile media and a power assist devices. We locate SkilMate in a wider framework of wearable intelligent machines which assist in a®ording such working surroundings that they can exhibit their skill… Show more

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Cited by 19 publications
(9 citation statements)
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“…The sensors detecting physical signal such as the force and position (or motion) are the most used sensors in the robot system of hand rehabilitation [ 24 ]. The function of force or position signal is to provide the physical state of the hand such as the exerted force of motion or the bending angle of the finger [ 84 88 ]. For example, the sensing and force-feedback exoskeleton (SAFE) robotics was designed by Ben-Tzvi et al, in which an optical position sensor and strain gauges are set to detect the motion and force signal [ 89 ].…”
Section: Classification Of Hand Rehabilitation Robotsmentioning
confidence: 99%
“…The sensors detecting physical signal such as the force and position (or motion) are the most used sensors in the robot system of hand rehabilitation [ 24 ]. The function of force or position signal is to provide the physical state of the hand such as the exerted force of motion or the bending angle of the finger [ 84 88 ]. For example, the sensing and force-feedback exoskeleton (SAFE) robotics was designed by Ben-Tzvi et al, in which an optical position sensor and strain gauges are set to detect the motion and force signal [ 89 ].…”
Section: Classification Of Hand Rehabilitation Robotsmentioning
confidence: 99%
“…The majority of the hand exoskeletons that have been developed so far can be classified into three categories according to the source of intention extraction: fingerpad contact force [7]- [10], finger motion [11]- [13], and surface electromyography (sEMG) [14]- [17]. Although muscle hardness can also be utilized for intention extraction [18], it has neither been proven to be able to identify individual finger force nor been widely adopted.…”
Section: Introductionmentioning
confidence: 99%
“…To assist reduced grip strength or prevent WMSDs, many assistive hand exoskeletons have been developed [8][9][10][11][12][13][14][15][16] that detect the intention of the wearer's intention via fingerpad contact forces [17][18][19][20], finger motion [20][21][22][23][24], surface electromyography (sEMG) [25][26][27], or multimodal sensing [28]. Although the measurement of fingerpad contact force enables the acquisition of individual finger forces with simple sensors, the tactile sensation of the wearer is inevitably diminished because of the presence of the force sensor between the fingerpad and object being manipulated.…”
Section: Introductionmentioning
confidence: 99%