Myoelectric control of prosthetic hands: state-of-the-art review

Abstract

Myoelectric signals (MES) have been used in various applications, in particular, for identification of user intention to potentially control assistive devices for amputees, orthotic devices, and exoskeleton in order to augment capability of the user. MES are also used to estimate force and, hence, torque to actuate the assistive device. The application of MES is not limited to assistive devices, and they also find potential applications in teleoperation of robots, haptic devices, virtual reality, and so on. The myoelectric control-based prosthetic hand aids to restore activities of daily living of amputees in order to improve the self-esteem of the user. All myoelectric control-based prosthetic hands may not have similar operations and exhibit variation in sensing input, deciphering the signals, and actuating prosthetic hand. Researchers are focusing on improving the functionality of prosthetic hand in order to suit the user requirement with the different operating features. The myoelectric control differs in operation to accommodate various external factors. This article reviews the state of the art of myoelectric prosthetic hand, giving description of each control strategy.

Evaluating Internal Model Strength and Performance of Myoelectric Prosthesis Control Strategies

“…Time domain and frequency domain features are some of the most referenced of these features and are commonly used in conjunction with pattern recognition algorithms implemented in myoelectric control systems [5], [6]. The current myoelectric control systems can be broadly categorized as on/off control, proportional control, classifier-based control, and regression-based control [7].…”

Introductory Chapter: Toward Near-Natural Assistive Devices

“…Many current active prosthetics are myoelectric, which are controlled through the use of electromyography (EMG) signals, allowing the device to better reflect the intention of the user [21]. EMG signals have been utilized to successfully control prosthetic hands [37].…”

“…Myoelectric control also relies on undamaged neuromuscular pathways being accessible to present the EMG signal [7]. Although strides are being taken in targeted muscle reinnervation (TMR) to allow for greater EMG accessibility [21], this may not be possible in all cases. Electroencephalogram (EEG)-based control of prosthetics attempts to bypass this problem [21].…”

“…Although strides are being taken in targeted muscle reinnervation (TMR) to allow for greater EMG accessibility [21], this may not be possible in all cases. Electroencephalogram (EEG)-based control of prosthetics attempts to bypass this problem [21]. EEG-controlled prosthetics employ the user's brain signals in conjunction with brain-computer interface (BCI) systems for control.…”

A Graphic User Interface (GUI) to build a cost-effective customizable 3D printed Prosthetic Hand

“…However, neither of these solutions seems possible to be applied to current prosthetic devices in an affordable way. Besides detecting electrical impulses, another method that is used to control prosthetic arms is via pressure sensors located in the shoe 11 . Although not exactly intuitive to use, it did seem like a more reliable solution than EMG sensors.…”