To improve the control effectiveness and make the prosthetic hand not only controllable but also perceivable, an EMG prosthetic hand control strategy was proposed in this paper. The control strategy consists of EMG self-learning motion recognition, backstepping controller with stiffness fuzzy observation, and force tactile representation. EMG self-learning motion recognition is used to reduce the influence on EMG signals caused by the uncertainty of the contacting position of the EMG sensors. Backstepping controller with stiffness fuzzy observation is used to realize the position control and grasp force control. Velocity proportional control in free space and grasp force tracking control in restricted space can be realized by the same contr...
This paper intends to provide a critical review of the literature on the technological issues on con...
This paper proposes a novel method of using electromyographic (EMG) potentials generated by the fore...
A real-time pattern recognition algorithm based on k-nearest neighbors and lazy learning was used to...
The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedd...
Some of the traditional methods used to control a conventional prosthetic device are described along...
Grasping is a complex task routinely performed in an anticipatory (feedforward) manner, where sensor...
In this study, we hypothesized that haptic feedback would enhance grip force control of surface elec...
Despite recent advances in prostheses, intuitive and robust control of poly-articulated prosthetic h...
Tactile feedback about, at least, hand aperture and grasping force, is required for (1) optimal cont...
Background: The users of today's commercial prosthetic hands are not given any conscious sensory fee...
This paper presents a prosthetic hand control system for trans-radial amputees based on electromyogr...
The hand is a very complex organ that possesses an incredible versatility. Besides its grasping and ...
Abstract A major drawback with myoelectric prostheses is that they do not provide the user with sens...
The control of the Touch Hand: a low-cost electrically powered prosthetic hand is explored in this p...
Myoelectric prosthetic hands aim to serve upper limb amputees. The myoelectric control of the hand g...
This paper intends to provide a critical review of the literature on the technological issues on con...
This paper proposes a novel method of using electromyographic (EMG) potentials generated by the fore...
A real-time pattern recognition algorithm based on k-nearest neighbors and lazy learning was used to...
The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedd...
Some of the traditional methods used to control a conventional prosthetic device are described along...
Grasping is a complex task routinely performed in an anticipatory (feedforward) manner, where sensor...
In this study, we hypothesized that haptic feedback would enhance grip force control of surface elec...
Despite recent advances in prostheses, intuitive and robust control of poly-articulated prosthetic h...
Tactile feedback about, at least, hand aperture and grasping force, is required for (1) optimal cont...
Background: The users of today's commercial prosthetic hands are not given any conscious sensory fee...
This paper presents a prosthetic hand control system for trans-radial amputees based on electromyogr...
The hand is a very complex organ that possesses an incredible versatility. Besides its grasping and ...
Abstract A major drawback with myoelectric prostheses is that they do not provide the user with sens...
The control of the Touch Hand: a low-cost electrically powered prosthetic hand is explored in this p...
Myoelectric prosthetic hands aim to serve upper limb amputees. The myoelectric control of the hand g...
This paper intends to provide a critical review of the literature on the technological issues on con...
This paper proposes a novel method of using electromyographic (EMG) potentials generated by the fore...
A real-time pattern recognition algorithm based on k-nearest neighbors and lazy learning was used to...