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1.
Motor unit characteristics after targeted muscle reinnervation
Tamás Kapelner, Ning Jiang, Aleš Holobar, Ivan Vujaklija, Aidan Roche, Dario Farina, Oskar Aszmann, 2016, original scientific article

Abstract: Targeted muscle reinnervation (TMR) is a surgical procedure used to redirect nerves originally controlling muscles of the amputated limb into remaining muscles above the amputation, to treat phantom limb pain and facilitate prosthetic control. While this procedure effectively establishes robust prosthetic control, there is little knowledge on the behavior and characteristics of the reinnervated motor units. In this study we compared the m. pectoralis of five TMR patients to nine able-bodied controls with respect to motor unit action potential (MUAP) characteristics. We recorded and decomposed high-density surface EMG signals into individual spike trains of motor unit action potentials. In the TMR patients the MUAP surface area normalized to the electrode grid surface (0.25 ± 0.17 and 0.81 ± 0.46, p < 0.001) and the MUAP duration (10.92 ± 3.89 ms and 14.03 ± 3.91 ms, p < 0.01) were smaller for the TMR group than for the controls. The mean MUAP amplitude (0.19 ± 0.11 mV and 0.14 ± 0.06 mV, p = 0.07) was not significantly different between the two groups. Finally, we observed that MUAP surface representation in TMR generally overlapped, and the surface occupied by motor units corresponding to only one motor task was on average smaller than 12% of the electrode surface. These results suggest that smaller MUAP surface areas in TMR patients do not necessarily facilitate prosthetic control due to a high degree of overlap between these areas, and a neural information—based control could lead to improved performance. Based on the results we also infer that the size of the motor units after reinnervation is influenced by the size of the innervating motor neuron.
Keywords: target muscle reinnervation, motor unit, controlling muscles
Published in DKUM: 19.06.2017; Views: 915; Downloads: 346
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Noninvasive, accurate assessment of the behavior of representative populations of motor units in targeted reinnervated muscles
Dario Farina, Hubertus Rehbaum, Aleš Holobar, Ivan Vujaklija, Ning Jiang, Christian Hofer, Stefan Salminger, Hans-Willem van Vliet, Oskar Aszmann, 2014, original scientific article

Abstract: Targeted muscle reinnervation (TMR) redirects nerves that have lost their target, due to amputation, to remaining muscles in the region of the stump with the intent of establishing intuitive myosignals to control a complex prosthetic device. In order to directly recover the neural code underlying an attempted limb movement, in this paper, we present the decomposition of high-density surface electromyographic (EMG) signals detected from three TMR patients into the individual motor unit spike trains. The aim was to prove, for the first time, the feasibility of decoding the neural drive that would reach muscles of the missing limb in TMR patients, to show the accuracy of the decoding, and to demonstrate the representativeness of the pool of extracted motor units. Six to seven flexible EMG electrode grids of 64 electrodes each were mounted over the reinnervated muscles of each patient, resulting in up to 448 EMG signals. The subjects were asked to attempt elbow extension and flexion, hand open and close, wrist extension and flexion, wrist pronation and supination, of their missing limb. The EMG signals were decomposed using the Convolution Kernel Compensation technique and the decomposition accuracy was evaluated with a signal-based index of accuracy, called pulse-to-noise ratio (PNR). The results showed that the spike trains of 3 to 27 motor units could be identified for each task, with a sensitivity of the decomposition > 90%, as revealed by PNR. The motor unit discharge rates were within physiological values of normally innervated muscles. Moreover, the detected motor units showed a high degree of common drive so that the set of extracted units per task was representative of the behavior of the population of active units. The results open a path for a new generation of human-machine interfaces in which the control signals are extracted from noninvasive recordings and the obtained neural information is based directly on the spike trains of motor neurons.
Keywords: electromyographic, EMG, decomposition, high-density EMG, motor neuron, motor unit, myoelectronic control, neural drive to muscle, target muscle reinervation, TMR
Published in DKUM: 25.05.2015; Views: 1133; Downloads: 0

5.
The extraction of neural information from the surface EMG for the control of upper-limb prostheses : emerging avenues and challenges
Dario Farina, Ning Jiang, Hubertus Rehbaum, Aleš Holobar, Bernhard Graimann, Hans Dietl, Oskar Aszmann, 2014, original scientific article

Abstract: 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.
Keywords: neural drive to muscle, high-density EMG, motor neuron, motor unit, myoelectronic control, pattern recognition, regression
Published in DKUM: 25.05.2015; Views: 964; Downloads: 0

6.
Human-machine interfacing by decoding surface electromyogram
Dario Farina, Aleš Holobar, 2015, original scientific article

Keywords: decoding, electromyography, human computer interaction, neurons, accuracyuser interfaces
Published in DKUM: 25.05.2015; Views: 1125; Downloads: 0

7.
Adjustments differ among low-threshold motor units during intermittent, isometric contractions
Dario Farina, Aleš Holobar, Marco Gazzoni, Damjan Zazula, Roberto Merletti, Roger M. Enoka, 2009, original scientific article

Abstract: We investigated the changes in muscle fiber conduction velocity, recruitment and derecruitment thresholds, and discharge rate of low-threshold motor units during a series of ramp contractions. The aim was to compare the adjustments in motor unit activity relative to the duration that each motor unit was active during the task. Multichannel surface electromyographic (EMG) signals were recorded from the abductor pollicis brevis muscle of eight healthy men during 12-s contractions (n = 25) in which the force increased and decreased linearly from 0 to 10% of the maximum. The maximal force exhibited a modest decline (8.5 +- 9.3%; P < 0.05) at the end of the task. The discharge times of 73 motor units that were active for 16-98% of the time during the first five contractions were identified throughout the task by decomposition of the EMG signals. Action potential conduction velocity decreased during the task by a greater amount for motor units that were initially active for >70% of the time compared with that of less active motor units. Moreover, recruitment and derecruitment thresholds increased for these most active motor units, whereas the thresholds decreased for the less active motor units. Another 18 motor units were recruited at an average of 171 +- 32 s after the beginning of the task. The recruitment and derecruitment thresholds of these units decreased during the task, but muscle fiber conduction velocity did not change. These results indicate that low-threshold motor units exhibit individual adjustments in muscle fiber conduction velocity and motor neuron activation that depended on the relative duration of activity during intermittent contractions.
Keywords: electromyography, surface electromyography, multi-channel EMG, motor units, decompostion, recruitment treshold, derecruitment treshold_
Published in DKUM: 01.06.2012; Views: 1464; Downloads: 205
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