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

Purushothaman Geethanjali
2016 Medical Devices : Evidence and Research  
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  ...  All myoelectric control-based prosthetic hands may not have similar operations and exhibit variation in sensing input, deciphering the signals, and actuating prosthetic hand.  ...  Many time domain features have been investigated and compared for their effectiveness in pattern recognition for myoelectric control.  ... 
doi:10.2147/mder.s91102 pmid:27555799 pmcid:PMC4968852 fatcat:dp2kffj4vzcfhklopmlplxttbq

Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation

Nawadita Parajuli, Neethu Sreenivasan, Paolo Bifulco, Mario Cesarelli, Sergio Savino, Vincenzo Niola, Daniele Esposito, Tara J. Hamilton, Ganesh R. Naik, Upul Gunawardana, Gaetano D. Gargiulo
2019 Sensors  
(EMG)-pattern recognition methods.  ...  Modified machine learning schemes for pattern recognition have the potential to significantly reduce the factors (movement of users and contraction of the muscle) affecting the traditional electromyography  ...  Pattern Recognition-Based Myoelectric Control Myoelectric control systems can be classified as a pattern recognition control system and a non-pattern recognition control system.  ... 
doi:10.3390/s19204596 pmid:31652616 pmcid:PMC6832440 fatcat:kxbk2qiysfdzrb24xhp4s7roli

Electromyography Pattern-Recognition-Based Control of Powered Multifunctional Upper-Limb Prostheses [chapter]

Guanglin Li
2011 Advances in Applied Electromyography  
Myoelectric signals detected with electrodes placed on the skin surface overlying the muscles, well-known as electromyography (EMG), have been used in control of motorized upper-limb prostheses for several  ...  In order to operate a body-powered prosthesis, the upper limb amputees have to possess significant strength and control over various body parts, including the shoulders, chest, and residual limb which  ...  Neural-machine interface for improvement of control performance 3.1 A paradox As discussed above, EMG pattern recognition based control strategy seems highly promising in developing the novel myoelectric  ... 
doi:10.5772/22876 fatcat:gcosmzkhqzculntrflniqcpamu

Application of Artificial Intelligence (AI) in Prosthetic and Orthotic Rehabilitation [chapter]

Smita Nayak, Rajesh Kumar Das
2020 Service Robotics [Working Title]  
prosthesis and exoskeletons.  ...  Technological integration of Artificial Intelligence (AI) and machine learning in the Prosthetic and Orthotic industry and in the field of assistive technology has become boon for the Persons with Disabilities  ...  The advancement in EMG control myoelectric prosthesis was with use of EMG pattern recognition based control strategy [28] .  ... 
doi:10.5772/intechopen.93903 fatcat:jp2h7xcms5h3tjx7ichkckplty

Bio-signal based control in assistive robots: a survey

Ericka Janet Rechy-Ramirez, Huosheng Hu
2015 Digital Communications and Networks  
Abstract Recently, bio-signal based control has been gradually deployed in biomedical devices and assistive robots for improving the quality of life of disabled and elderly people, among which EMG (Electromyography  ...  The main aim of this paper is to describe the techniques used for: i) collecting EMG and EEG signals and diving these signals into segments (data acquisition and data segmentation stage), ii) emphasizing  ...  Acknowledgments The 1st author has been supported by the Mexican National Council of Science and Technology (CONACYT), through the program -Becas para estudios de posgrado en el extranjero‖ (no. 183592  ... 
doi:10.1016/j.dcan.2015.02.004 fatcat:bkgdv7lywbgtnnoxbwdxtvxpom

A Comprehensive Review of Myoelectric Prosthesis Control [article]

Mohammad Reza Mohebbian, Marjan Nosouhi, Farzaneh Fazilati, Zahra Nasr Esfahani, Golnaz Amiri, Negar Malekifar, Fatemeh Yusefi, Mohsen Rastegari, Hamid Reza Marateb
2021 arXiv   pre-print
In this paper, the following myoelectric prosthesis control methods were discussed in detail: On-off and finite-state, proportional, direct, and posture, simultaneous, classification and regression-based  ...  Myoelectric control performance indices, such as completion time and rate, throughput, lag, and path length, were reviewed.  ...  Data Availability Statement: Data supporting the reported results can be found at PubMed ( and Cochrane Library (  ... 
arXiv:2112.13192v1 fatcat:oc6kfbcrerduxfselt7izd2lp4

Design and Implementation of Myoelectric Controlled Arm

Tariq M. Younes, Mohammad A. AlKhedher, Abdel-Hamid Soliman, Aiman Al Alawin
2019 Journal of Mechatronics and Robotics  
In this study a discrimination system, using a neural network for Electromyogram (EMG) externally controlled Arm is proposed.  ...  The Neural Network can discriminate 4 performances of the EMG signals simultaneously. The digital signal processing was realized using MATLAB and LabVIEW software.  ...  I'd like to thank Al-Balqa Applied University Abu Dhabi University for their support and Staffordshire University for their logistic aid. Author's Contributions Dr.  ... 
doi:10.3844/jmrsp.2019.552.562 fatcat:wcdh4q2pzzhapnpx4qnxjnaj3i

Multifunctional Prosthesis Control with Simulation of Myoelectric Signals

João Fermeiro, Filipa Moreira, José Pombo, Rosário Calado, Sílvio Mariano
2020 KnE Engineering  
(NN) and Support Vector Machines (SVM).  ...  Keywords: EMG, Signal conditioning, Wavelet Packet Transform (WPT), Neural Networks (NN), Support Vector Machines (SVM)  ...  Acknowledgments This work is funded by FCT/MEC through national funds and when applicable co-funded by FEDER-PT2020 partnership agreement under the project UID/EEA/50008/2019. DOI  ... 
doi:10.18502/keg.v5i6.7101 fatcat:tljqog3z4ngoritvhqrcyxkzta

Quantifying Pattern Recognition—Based Myoelectric Control of Multifunctional Transradial Prostheses

Guanglin Li, Aimee E Schultz, Todd A Kuiken
2010 IEEE transactions on neural systems and rehabilitation engineering  
We evaluated real-time myoelectric pattern recognition control of a virtual arm by transradial amputees.  ...  The outcomes of this study could aid the development of a practical multifunctional myoelectric prosthesis for transradial amputees, and suggest that increased EMG information-such as made available through  ...  Stubblefield and E. Corbett for their assistance in the experiments.  ... 
doi:10.1109/tnsre.2009.2039619 pmid:20071269 pmcid:PMC3024915 fatcat:5aqw2zzvbbdvxjfp7oxnm2djly

Towards a high-stability EMG recognition system for prosthesis control: A one-class classification based non-target EMG pattern filtering scheme

Yi-Hung Liu, Han-Pang Huang
2009 2009 IEEE International Conference on Systems, Man and Cybernetics  
This paper aims at dealing with a critical issue for electromyography (EMG) recognition. The issue is related to the stability of an EMG-based prosthesis control.  ...  Traditional EMG recognition systems receive EMG patterns and send them into classifiers directly, which generally results in unstable situations if the classes of some of the input EMG patterns are not  ...  INTRODUCTION Electromyography (EMG) signal recognition plays a key role in neural-machine/human-robot interface. The most commonly seen application is the myoelectric prosthesis control.  ... 
doi:10.1109/icsmc.2009.5346086 dblp:conf/smc/LiuH09 fatcat:ogfe2q7hvvekbks56urvqujpd4

Moving sliding mode control for sEMG based prosthetic hand

Beyda Tasar, Alper K Tanyildizi, Arif Gulten, Oguz Yakut
2018 Biomedical Research  
Proportional myoelectric hand Figure 10. Control signal for pattern 3. a) Index fingers; b) Thumb control: an evaluation.  ...  Recognition of Hand via EMG Signals high.  ... 
doi:10.4066/biomedicalresearch.29-18-461 fatcat:2ja52zy36rarxbnkyjutvhab4u

Simple and Computationally Efficient Movement Classification Approach for EMG-controlled Prosthetic Hand: ANFIS vs. Artificial Neural Network

Hessam Jahani Fariman, Siti A. Ahmad, M. Hamiruce Marhaban, M. Ali Jan Ghasab, Paul H. Chappell
2015 Intelligent Automation and Soft Computing  
Thus, an affordable prosthetic 39 hand should be developed in consideration of the tradeoff between accuracy and price. 40 The first step is designing an effective yet simple control system for prosthetic  ...  The 20 surface myoelectric signals were acquired from 2 muscles -Flexor Carpi Ulnaris and Extensor Carpi 21 Radialis of 4 normal-limb subjects.  ...  Support vector machine-based classification scheme for myoelectric control 467 applied to upper limb.  ... 
doi:10.1080/10798587.2015.1008735 fatcat:bc54hzag65glropicoyqn22ifa


Parag Thote
2019 International Journal of Advanced Research  
Map (SOM) and Support Vector Machines (SVM) [04] .  ...  EMG methods were categorized based on structure of the control algorithm as pattern recognition-based control system and non-pattern recognition-based control system.  ... 
doi:10.21474/ijar01/8889 fatcat:i4utovmfazcyjd5w2uymkrlb3m

Pattern recognition of hand movements with low density sEMG for prosthesis control purposes

J. J. Villarejo, A. Frizera, T. F. Bastos, J. F. Sarmiento
2013 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR)  
The results showed 95.4% higher than recognitions. Index Terms-sEMG, multifunction myoelectric control system, low level movements, pattern recognition, isometric task.  ...  This paper presents a study related to the identification of different hand gestures from EMG signals from forearm muscles, to be used as human machine interface system in a hand prosthesis.  ...  Fig. 1 1 Myoelectric control system based on pattern recognition. Fig. 2 2 Myoelectric control system based on pattern recognition for 4 channel and 1 channel.  ... 
doi:10.1109/icorr.2013.6650361 pmid:24187180 dblp:conf/icorr/VillarejoFBS13 fatcat:6mp5notdvjf6dlfsr7tlizfrqe

A Neuro-Fuzzy System for Characterization of Arm Movements

Alexandre Balbinot, Gabriela Favieiro
2013 Sensors  
control of prosthesis.  ...  To recognize certain hand-arm segment movements, was developed an algorithm for pattern recognition technique based on neuro-fuzzy, representing the core of this research.  ...  The classification was with Linear Support Vector Machines. Boschmann et al. [20] , introduce an approach for classifying EMG signals taken from forearm muscles using support vector machines.  ... 
doi:10.3390/s130202613 pmid:23429579 pmcid:PMC3649412 fatcat:3rr45244xrgbbko7y323bqvuji
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