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Naslov:The extraction of neural information from the surface EMG for the control of upper-limb prostheses : emerging avenues and challenges
Avtorji:ID Farina, Dario (Avtor)
ID Jiang, Ning (Avtor)
ID Rehbaum, Hubertus (Avtor)
ID Holobar, Aleš (Avtor)
ID Graimann, Bernhard (Avtor)
ID Dietl, Hans (Avtor)
ID Aszmann, Oskar (Avtor)
Datoteke: Gradivo nima datotek. Gradivo je morda fizično dosegljivo v knjižnici fakultete, zalogo lahko preverite v COBISS-u. Povezava se odpre v novem oknu
Jezik:Angleški jezik
Vrsta gradiva:Neznano
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FERI - Fakulteta za elektrotehniko, računalništvo in informatiko
Opis:Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e., the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time ( 200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards.
Ključne besede:neural drive to muscle, high-density EMG, motor neuron, motor unit, myoelectronic control, pattern recognition, regression
Leto izida:2014
Št. strani:str. 797-809
Številčenje:#Vol. #22, #no. #4
PID:20.500.12556/DKUM-48144 Novo okno
UDK:007.5:61
COBISS.SI-ID:18018070 Novo okno
DOI:10.1109/TNSRE.2014.2305111 Novo okno
ISSN pri članku:1534-4320
NUK URN:URN:SI:UM:DK:NVDQBX2R
Datum objave v DKUM:25.05.2015
Število ogledov:1554
Število prenosov:0
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
Področja:Ostalo
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Gradivo je del revije

Naslov:IEEE transactions on neural systems and rehabilitation engineering
Skrajšan naslov:IEEE trans. neural syst. rehabil. eng.
Založnik:IEEE
ISSN:1534-4320
COBISS.SI-ID:320873 Novo okno

Gradivo je financirano iz projekta

Financer:EC - European Commission
Program financ.:FP7
Številka projekta:251555
Naslov:Advanced Myoelectric Control of Prosthetic Systems
Akronim:AMYO

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