Publications
787 results found
Boudreau SA, Farina D, Falla D, 2010, The role of motor learning and neuroplasticity in designing rehabilitation approaches for musculoskeletal pain disorders., Man Ther, Vol: 15, Pages: 410-414
The extent of cortical neuroplastic changes has been shown to be a key neurophysiological feature that correlates with the level of functional recovery. Therefore, rehabilitation efforts that attempt to maximize cortical reorganization provide the greatest potential for rehabilitation success. This paper reviews the evidence of cortical neuroplastic changes that have been shown to occur in association with experimental or chronic pain disorders. Further, the promising role of novel motor-skill training is discussed in order to best direct the clinician to optimize rehabilitation strategies for patients with musculoskeletal pain disorders.
Farina D, Holobar A, Merletti R, et al., 2010, Decoding the neural drive to muscles from the surface electromyogram., Clin Neurophysiol, Vol: 121, Pages: 1616-1623
This brief review discusses the methods used to estimate the neural drive to muscles from the surface electromyogram (EMG). Surface EMG has been classically used to infer the neural activation of muscle by associating its amplitude with the number of action potentials discharged by a population of motor neurons. Although this approach is valuable in some applications, the amplitude of the surface EMG is only a crude indicator of the neural drive to muscle. More advanced methods are now available to estimate the neural drive to muscle from the surface EMG. These approaches identify the discharge times of a few motor units by decomposing the EMG signal to determine the relative changes in neural activation. This approach is reliable in several conditions and muscles for isometric contractions of moderate force, but is limited to the few superficial units that can be identified in the recordings.
Kamavuako EN, Farina D, 2010, Time-dependent effects of pre-conditioning activation on muscle fiber conduction velocity and twitch torque., Muscle Nerve, Vol: 42, Pages: 547-555
In this study we investigate the range of interstimulus intervals influencing the recovery functions for conduction velocity (velocity recovery function, or VRF) and twitch torque (twitch torque recovery function, or TRF) of muscle fibers. We studied the tibialis anterior muscle of 8 healthy men by varying the time interval between a pair of stimuli in the range of 4-1000 ms, with (triplet) and without (doublet) a preconditioning stimulus. For triplet stimulations, the interval between the first and second stimulus or between the second and third stimulus was fixed, and the other interval was varied. VRF and TRF were influenced by a preconditioning stimulus only when it was delivered within 125 ms and 30 ms, respectively, before the doublet stimulation. The results provide evidence of the range of preconditioning intervals influencing the VRF and TRF; this is relevant for understanding the mechanisms of force generation and for standardizing compound action potential measurements.
Gonzalez-Izal M, Malanda A, Rodríguez-Carreño I, et al., 2010, Linear vs. non-linear mapping of peak power using surface EMG features during dynamic fatiguing contractions., J Biomech, Vol: 43, Pages: 2589-2594
This study compares a non-linear (neural network) and a linear (linear regression) power mapping using a set of features of the surface electromyogram recorded from the vastus medialis and lateralis muscles. Fifteen healthy participants performed 5 sets of 10 repetitions leg press using the individual maximum load corresponding what they could perform 10 times (10RM) with 120s of rest between them. The following sEMG variables were computed from each extension contraction and used as inputs to both approaches: mean average value (MAV), median frequency (Fmed), the spectral parameter proposed by Dimitrov (FInsm5), average (over the observation interval) of the instantaneous mean frequency obtained from a Choi-Williams distribution (MFM), and wavelet indices ratio between moments at different scales (WIRM1551, WIRM1M51, WIRM1522, WIRE51, and WIRW51). The non-linear mapping (neural network) provided higher correlation coefficients and signal-to-noise ratios values (although not significantly different) between the actual and the estimated changes of power compared to linear mapping (linear regression) using the sEMG variables alone and a combination of WIRW51 and MFM (obtained by a stepwise multiple linear regression). In conclusion, non-linear mapping of force loss during dynamic knee extension exercise showed higher signal-to-noise ratio and correlation coefficients between the actual and estimated power output compared to linear mapping. However, since no significant differences were observed between linear and non-linear approaches, both were equally valid to estimate changes in peak power during fatiguing repetitive leg extension exercise.
Gonzalez-Izal M, Falla D, Izquierdo M, et al., 2010, Predicting force loss during dynamic fatiguing exercises from non-linear mapping of features of the surface electromyogram., J Neurosci Methods, Vol: 190, Pages: 271-278
This study proposes a method for estimating force loss during fatiguing maximal isokinetic knee extension contractions using a set of features from surface EMG signals recorded from multiple locations over the quadriceps muscle. Nine healthy participants performed fatiguing tests which consisted of 50 and 75 isokinetic leg extensions at a speed of 30 degrees /s and 80 degrees /s in two experimental sessions on different days. The set of data recorded from one of the experimental sessions (at both velocities) was used to train a multi-layer perceptron neural network to associate force loss (direct measure of fatigue) to EMG features. The data from the other session (obtained from the tests at both velocities) were used for testing the neural network performance. The proposed method was compared with a previous approach for the assessment of fatigue (Mapping Index, MI) using a signal to noise metrics computed on the estimated trend of fatigue. The signal to noise ratio obtained with the proposed approach was greater (8.83+/-1.07) than that obtained with the MI (5.67+/-1.17) (P<0.05) when the subjects were analyzed individually and when the network was trained over the entire subject group (8.07 vs. 4.42). In conclusion, the proposed approach allows estimation of force loss during maximal dynamic knee extensions from surface EMG signals with greater accuracy than previous methods.
Dideriksen JL, Farina D, Enoka RM, 2010, Influence of fatigue on the simulated relation between the amplitude of the surface electromyogram and muscle force., Philos Trans A Math Phys Eng Sci, Vol: 368, Pages: 2765-2781, ISSN: 1364-503X
A linear relation between surface electromyogram (EMG) amplitude and muscle force is often assumed and used to estimate the contributions of selected muscles to various tasks. In the presence of muscle fatigue, however, changes in the properties of muscle fibre action potentials and motor unit twitch forces can alter the relation between surface EMG amplitude and force. A novel integrative model of motor neuron control and the generation of muscle fibre action potentials was used to simulate surface EMG signals and muscle force during three fatigue protocols. The change in the simulated relation between surface EMG amplitude and force depended on both the level of fatigue and the details of the fatiguing contraction. In general, surface EMG amplitude overestimated muscle force when fatigue was present. For example, surface EMG amplitudes corresponding to 60 per cent of the amplitude obtained at maximal force without fatigue corresponded to forces in the range 10-40% of the maximal force across three representative fatigue protocols. The results indicate that the surface EMG amplitude cannot be used to predict either the level of muscle activation or the magnitude of muscle force when the muscle exhibits any fatigue.
Dideriksen JL, Farina D, Baekgaard M, et al., 2010, An integrative model of motor unit activity during sustained submaximal contractions., J Appl Physiol (1985), Vol: 108, Pages: 1550-1562
The purpose of the study was to expand a model of motor unit recruitment and rate coding (30) to simulate the adjustments that occur during a fatiguing contraction. The major new components of the model were the introduction of time-varying parameters for motor unit twitch force, recruitment, discharge rate, and discharge variability, and a control algorithm that estimates the net excitation needed by the motoneuron pool to maintain a prescribed target force. The fatigue-induced changes in motor unit activity in the expanded model are a function of changes in the metabolite concentrations that were computed with a compartment model of the intra- and extracellular spaces. The model was validated by comparing the simulation results with data available from the literature and experimentally recorded in the present study during isometric contractions of the first dorsal interosseus muscle. The output of the model was able to replicate a number of experimental findings, including the time to task failure for a range of target forces, the changes in motor unit discharge rates, the skewness and kurtosis of the interspike interval distributions, discharge variability, and the discharge characteristics of newly recruited motor units. The model output provides an integrative perspective of the adjustments during fatiguing contractions that are difficult to measure experimentally.
Holobar A, Minetto MA, Botter A, et al., 2010, Experimental analysis of accuracy in the identification of motor unit spike trains from high-density surface EMG., IEEE Trans Neural Syst Rehabil Eng, Vol: 18, Pages: 221-229
The aim of this study was to compare the decomposition results obtained from high-density surface electromyography (EMG) and concurrently recorded intramuscular EMG. Surface EMG signals were recorded with electrode grids from the tibialis anterior, biceps brachii, and abductor digiti minimi muscles of twelve healthy men during isometric contractions ranging between 5% and 20% of the maximal force. Bipolar intramuscular EMG signals were recorded with pairs of wire electrodes. Surface and intramuscular EMG were independently decomposed into motor unit spike trains. When averaged over all the contractions of the same contraction force, the percentage of discharge times of motor units identified by both decompositions varied in the ranges 84%-87% (tibialis anterior), 84%-86% (biceps brachii), and 87%-92% (abductor digiti minimi) across the force levels analyzed. This index of agreement between the two decompositions was linearly correlated with a self-consistency measure of motor unit discharge pattern that was based on coefficient of variation for the interspike interval (R(2) = 0.68 for tibialis anterior, R(2) = 0.56 for biceps brachii, and R(2) = 0.38 for abductor digiti minimi). These results constitute an important contribution to the validation of the noninvasive approach for the investigation of motor unit behavior in isometric low-force tasks.
Falla D, Andersen H, Danneskiold-Samsøe B, et al., 2010, Adaptations of upper trapezius muscle activity during sustained contractions in women with fibromyalgia., J Electromyogr Kinesiol, Vol: 20, Pages: 457-464
The study compared the distribution of electromyographic (EMG) signal amplitude in the upper trapezius muscle in 10 women with fibromyalgia and in 10 healthy women before and after experimentally-induced muscle pain. Surface EMG signals were recorded over the right upper trapezius muscle with a 10 x 5 grid of electrodes during 90 degrees shoulder abduction sustained for 60s. The control subjects repeated the abduction task following injections of isotonic and hypertonic (painful) saline into the upper trapezius muscle. The EMG amplitude was computed for each electrode pair and provided a topographical map of the distribution of muscle activity. The pain level rated by the patients at the beginning of the sustained contraction was 5.9+/-1.5. The peak pain intensity for the control group following the injection of hypertonic saline was 6.0+/-1.6. During the sustained contractions, the EMG amplitude increased relatively more in the cranial than caudal region of the upper trapezius muscle for the control subjects (shift in the distribution of EMG amplitude: 2.3+/-1.3mm; P<0.01). The patient group showed lower average EMG amplitude than the controls during the contraction (P<0.05) and did not show different changes in EMG amplitude between different regions of the upper trapezius. A similar behavior was observed for the control group following injection of hypertonic saline. The results indicate that muscle pain prevents the adaptation of upper trapezius activity during sustained contractions as observed in non-painful conditions, which may induce overuse of similar muscle compartments with fatigue.
Falla D, Lindstrøm R, Rechter L, et al., 2010, Effect of pain on the modulation in discharge rate of sternocleidomastoid motor units with force direction., Clin Neurophysiol, Vol: 121, Pages: 744-753
OBJECTIVE: To compare the behavior of sternocleidomastoid motor units of patients with chronic neck pain and healthy controls. METHODS: Nine women (age, 40.4+/-3.5 yr) with chronic neck pain and nine age- and gender-matched healthy controls participated. Surface and intramuscular EMG were recorded from the sternocleidomastoid muscle bilaterally as subjects performed isometric contractions of 10-s duration in the horizontal plane at a force of 15 N in eight directions (0-360 degrees ; 45 degrees intervals) and isometric contractions at 15 and 30 N force with continuous change in force direction in the range 0-360 degrees . Motor unit behavior was monitored during the 10-s contractions and the subsequent resting periods. RESULTS: The mean motor unit discharge rate depended on the direction of force in the control subjects (P<0.05) but not in the patients. Moreover, in three of the nine patients, but in none of the controls, single motor unit activity continued for 8.1+/-6.1s upon completion of the contraction. The surface EMG amplitude during the circular contraction at 15N was greater for the patients (43.5+/-54.2 microV) compared to controls (16.9+/-14.9 microV; P<0.05). CONCLUSIONS: The modulation in discharge rate of individual motor units with force direction is reduced in the sternocleidomastoid muscle in patients with neck pain, with some patients showing prolonged motor unit activity when they were instructed to rest. SIGNIFICANCE: These observations suggest that chronic neck pain affects the change in neural drive to muscles with force direction.
Ge D, Le Carpentier E, Farina D, 2010, Unsupervised Bayesian decomposition of multiunit EMG recordings using Tabu search., IEEE Trans Biomed Eng, Vol: 57, Pages: 561-571
Intramuscular electromyography (EMG) signals are usually decomposed with semiautomatic procedures that involve the interaction with an expert operator. In this paper, a Bayesian statistical model and a maximum a posteriori (MAP) estimator are used to solve the problem of multiunit EMG decomposition in a fully automatic way. The MAP estimation exploits both the likelihood of the reconstructed EMG signal and some physiological constraints, such as the discharge pattern regularity and the refractory period of muscle fibers, as prior information integrated in a Bayesian framework. A Tabu search is proposed to efficiently tackle the nondeterministic polynomial-time-hard problem of optimization w.r.t the motor unit discharge patterns. The method is fully automatic and was tested on simulated and experimental EMG signals. Compared with the semiautomatic decomposition performed by an expert operator, the proposed method resulted in an accuracy of 90.0% +/- 3.8% when decomposing single-channel intramuscular EMG signals recorded from the abductor digiti minimi muscle at contraction forces of 5% and 10% of the maximal force. The method can also be applied to the automatic identification and classification of spikes from other neural recordings.
Muceli S, Boye AT, d'Avella A, et al., 2010, Identifying Representative Synergy Matrices for Describing Muscular Activation Patterns During Multidirectional Reaching in the Horizontal Plane, JOURNAL OF NEUROPHYSIOLOGY, Vol: 103, Pages: 1532-1542, ISSN: 0022-3077
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- Citations: 123
Kamavuako EN, Jensen W, Yoshida K, et al., 2010, A criterion for signal-based selection of wavelets for denoising intrafascicular nerve recordings., J Neurosci Methods, Vol: 186, Pages: 274-280
In this paper we propose a novel method for denoising intrafascicular nerve signals with the aim of improving action potential (AP) detection. The method is based on the stationary wavelet transform and thresholding of the wavelet coefficients. Since the choice of the mother wavelet substantially impact the performance, a criterion is proposed for selecting the optimal wavelet. The criterion for selection was based on the root mean square of the average of the output signal triggered by the detected APs. The mother wavelet was parameterized through the scaling filter, which allowed optimization through the proposed criterion. The method was tested on simulated signals and on experimental neural recordings. Experimental signals were recorded from the tibial branch of the sciatic nerve of three anaesthetized New Zealand white rabbits during controlled muscle stretches. The simulation results showed that the proposed method had an equivalent effect on AP detection performance (percentage of correct detection at 6 dB signal-to-noise ratio, mean+/-SD, 95.3+/-5.2%) to the a-posteriori choice of the best wavelet (96.1+/-3.6). Moreover, the AP detection after the proposed denoising method resulted in a correlation of 0.94+/-0.02 between the estimated spike rate and the muscle length. Therefore, the study proposes an effective method for selecting the optimal mother wavelet for denoising neural signals with the aim of improving AP detection.
Hedayatpour N, Falla D, Arendt-Nielsen L, et al., 2010, Effect of delayed-onset muscle soreness on muscle recovery after a fatiguing isometric contraction., Scand J Med Sci Sports, Vol: 20, Pages: 145-153
An increase to above-baseline levels of electromyography (EMG) mean power spectral frequency (MPF) has been observed previously during muscle recovery following fatiguing contractions and has been explained by membrane hyperpolarization due to increased activation of the Na+-K+ pump. It is hypothesized that this membrane mechanism is impaired by muscle fiber damage following eccentric exercise. Thus, the aim of the study was to investigate surface EMG signal characteristics during recovery from fatigue after eccentric exercise. Ten healthy subjects performed sustained isometric knee extensions at 40% of the maximal torque (MVC) until task failure before, immediately after and 24 and 48 h after eccentric exercise. Bipolar surface EMG signals were recorded from six locations over the quadriceps during the sustained isometric contraction and during 3-s long contractions at 40% MVC separated by 1-min intervals for 15 min (recovery). Before the eccentric exercise, MPF of EMG signals increased to values above baseline during recovery from the fatiguing isometric contraction (P<0.001), whereas immediately after and 24 and 48 h after the eccentric task, MPF was lower than baseline during the entire recovery period (P<0.01). In conclusion, delayed-onset muscle soreness abolished the supranormal increase in EMG MPF following recovery from fatigue.
Dewhurst S, Macaluso A, Gizzi L, et al., 2010, Effects of altered muscle temperature on neuromuscular properties in young and older women., Eur J Appl Physiol, Vol: 108, Pages: 451-458
Muscle temperature has a profound effect on the neuromuscular system of young individuals, however, little is known about the effects of altered temperature on the muscles of older individuals. The purpose of this study was to investigate the effect of altered local temperature on maximal torque and electromyography signal characteristics in 15 young (21.5 +/- 2.2 years; mean +/- SD) and 12 older (73.6 +/- 3.2 years) women. Subjects completed maximal voluntary isometric knee extension and flexion, together with isokinetic knee extensions (30, 60, 90, 120 and 240 degrees/s) at three muscle temperatures: control (approximately 34 degrees C), cold (approximately 30 degrees C) and warm (approximately 38 degrees C). The torque was lower in the older compared to young subjects at all temperatures (range of difference for 240 degrees /s, 25-40%; P < 0.001). Warming had no effect on torque in either group, whereas cooling decreased the torque during the isokinetic contractions in the young group only (range of decrease 6-10%; P < 0.05). In both groups, muscle fibre conduction velocity was slower with cooling compared to the warm condition (-15% in the young and -17% in the older subjects; P < 0.05).Temperature, however, had no effect on the agonist-antagonist coactivation level or the rate of force development in either group. The results suggest that, in particular, cooling the muscles has a greater effect on motor performance in young than older adults, which may indicate reduced adaptation of the neuromuscular system of older adults to altered temperature.
Cabrera AF, Farina D, Dremstrup K, 2010, Comparison of feature selection and classification methods for a brain-computer interface driven by non-motor imagery., Med Biol Eng Comput, Vol: 48, Pages: 123-132
The aim of this study was to compare methods for feature extraction and classification of EEG signals for a brain-computer interface (BCI) driven by auditory and spatial navigation imagery. Features were extracted using autoregressive modeling and optimized discrete wavelet transform. The features were selected with exhaustive search, from the combination of features of two and three channels, and with a discriminative measure (r (2)). Moreover, Bayesian classifier and support vector machine (SVM) with Gaussian kernel were compared. The results showed that the two classifiers provided similar classification accuracy. Conversely, the exhaustive search of the optimal combination of features from two and three channels significantly improved performance with respect to using r(2) for channel selection. With features optimally extracted from three channels with optimized scaling filter in the discrete wavelet transform, the classification accuracy was on average 72.2%. Thus, the choice of features had greater impact on performance than the choice of the classifier for discrimination between the two non-motor imagery tasks investigated. The results are relevant for the choice of the translation algorithm for an on-line BCI system based on non-motor imagery.
Yoshida K, Farina D, Akay M, et al., 2010, Multichannel intraneural and intramuscular techniques for multiunit recording and use in active prostheses, Proceedings of the IEEE, Vol: 98, Pages: 432-449, ISSN: 0018-9219
During the last decade there has been a renewed interest in the development of advanced, active hand prosthetic devices for amputees. In contrast to passive prostheses, active devices can be controlled by the user's intention. Active prosthetic devices have been substantially improved by integrating robot technology to achieve more functionalities and lifelike movements. Despite important progress in the technological development of prosthetics, their clinical application is still limited by the quantity and quality of biological signals that can be used for understanding the user's intention, and by the relatively poor performance of the algorithms that translate the user's intention into a desired movement. In this review we describe a solution to some of these limitations, i.e., the flexible, multichannel, implantable intraneural and intramuscular electrodes to interface the body's peripheral nerves or muscles. We aim to review the historic development, the underlying technology, and the design concepts of these electrodes. Moreover, the signal processing methods applied to these recordings and their use for the control of prosthetic devices will be discussed. Although the focus is on hand prostheses, the interface approach described is general. © 2006 IEEE.
Koutris M, Naeije M, Lobbezoo F, et al., 2010, Normalization reduces the spatial dependency of the jaw-stretch reflex activity in the human masseter muscle., Muscle Nerve, Vol: 41, Pages: 78-84
The jaw-stretch reflex is the short-latency response in the jaw-closing muscles after a sudden stretch. The hypothesis whether normalization of the jaw-stretch reflex amplitude with respect to prestimulus electromyographic (EMG) activity will make the amplitude more independent of the location of the electrodes over the masseter muscle was tested. A 5 x 6 electrode grid was used to record the jaw-stretch reflex from 25 sites over the right masseter muscle of 15 healthy men. The results showed that there was a significant site dependency of the prestimulus EMG activity and the reflex amplitude. High cross-correlation coefficients were found between the spatial distribution of mean prestimulus EMG activities and reflex amplitude. When the reflex amplitude was normalized with respect to the prestimulus EMG activity, no site dependency was found. In conclusion, normalization of the jaw-stretch reflex amplitude by the prestimulus EMG activity strongly reduces its spatial dependency.
Roatta S, Farina D, 2010, Sympathetic actions on the skeletal muscle., Exerc Sport Sci Rev, Vol: 38, Pages: 31-35
The sympathetic nervous system (SNS) modulates several functions in skeletal muscle fibers, including metabolism, ionic transport across the membrane, and contractility. These actions, together with the sympathetic control of other organ systems, support intense motor activity. However, some SNS actions on skeletal muscles may not always be functionally advantageous. Implications for motor control and sport performance are discussed.
Rocon E, Gallego JA, Barrios L, et al., 2010, Multimodal BCI-Mediated FES Suppression of Pathological Tremor, 32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10), Publisher: IEEE, Pages: 3337-3340, ISSN: 1557-170X
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- Citations: 21
Farina D, Lorrain T, Negro F, et al., 2010, High-density EMG E-textile systems for the control of active prostheses., Annu Int Conf IEEE Eng Med Biol Soc, Vol: 2010, Pages: 3591-3593, ISSN: 2375-7477
Myoelectric control of active prostheses requires electrode systems that are easy to apply for daily repositioning of the electrodes by the user. In this study we propose the use of Smart Fabric and Interactive Textile (SFIT) systems as an alternative solution for recording high-density EMG signals for myoelectric control. A sleeve covering the upper and lower arm, which contains 100 electrodes arranged in four grids of 5 × 5 electrodes, was used to record EMG signals in 3 subjects during the execution of 9 tasks of the wrist and hand. The signals were analyzed by extracting wavelet coefficients which were classified with linear discriminant analysis. The average classification accuracy for the nine tasks was 89.1 ± 1.9 %. These results show that SFIT systems can be used as an effective way for muscle-machine interfacing.
Jiang N, Falla D, d'Avella A, et al., 2010, Myoelectric control in neurorehabilitation., Crit Rev Biomed Eng, Vol: 38, Pages: 381-391, ISSN: 0278-940X
A myoelectric signal, or electromyogram (EMG), is the electrical manifestation of a muscle contraction. Through advanced signal processing techniques, information on the neural control of muscles can be extracted from the EMG, and the state of the neuromuscular system can be inferred. Because of its easy accessibility and relatively high signal-to-noise ratio, EMG has been applied as a control signal in several neurorehabilitation devices and applications, such as multi-function prostheses and orthoses, rehabilitation robots, and functional electrical stimulation/therapy. These EMG-based neurorehabilitation modules, which constitute muscle-machine interfaces, are applied for replacement, restoration, or modulation of lost or impaired function in research and clinical settings. The purpose of this review is to discuss the assumptions of EMG-based control and its applications in neurorehabilitation.
Graversen C, Drewes AM, Farina D, 2010, Support vector machine classification of multi-channel EEG traces: a new tool to analyze the brain response to morphine treatment., Pages: 992-995, ISSN: 2375-7477
The analgesic effect of morphine is highly individual, calling for objective methods to predict the subjective pain relief. Such methods might be based on alteration of brain response caused by morphine during painful stimuli. The study included 11 healthy volunteers subjectively quantifying perception of painful electrical stimulations in the esophagus. Brain evoked potentials following stimulations were recorded from sixty-four electroencephalographic channels at baseline and ninety minutes after morphine administration. Marginals obtained from discrete wavelet coefficients for each channel were used as input to an optimized support vector machine classifying between baseline and after morphine administration. The electroencephalographic channel leading to the best performance was further analyzed to identify brain alterations caused by morphine. Marginals from volunteers with no analgesic effect were examined for differences in comparison to volunteers with effect. The single-channel classification showed best performance at electrode P4 with 84.1 % of the traces classified correctly. When combining features from the 6 best performing channels, the multichannel classification increased to 92.4 %. The most discriminative feature was a decrease in the delta band (0.5 - 4 Hz) after morphine for volunteers with analgesic effect. Volunteers with no effect of morphine showed an increase in the delta band after drug administration. As only a proportion of patients benefit from opioid treatment, the new approach may help to identify non-responders and guide individualized tailored analgesic therapy.
Muceli S, Jiang N, Farina D, 2010, Multichannel Surface EMG Based Estimation of Bilateral Hand Kinematics during Movements at Multiple Degrees of Freedom, 2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), Pages: 6066-6069, ISSN: 1557-170X
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- Citations: 18
Dideriksen JL, Farina D, 2010, An integrative model of the surface EMG in pathological tremor., Annu Int Conf IEEE Eng Med Biol Soc, Vol: 2010, Pages: 6083-6086, ISSN: 2375-7477
A novel integrative model for simulating the surface EMG signal during pathological tremor is presented. The model combines neuromuscular elements, biomechanical descriptions, and surface EMG generation. First single motor unit spike trains are generated based on the sum of the simulated descending drive, afferent input and an oscillatory noise causing tremor. Based on this activity pattern, the muscle force is estimated, from which the limb movement is derived. The surface EMG is simulated as the sum of the surface action potentials generated by the active motor units. The model was able to simulate several features of tremor that have been previously observed experimentally, including the spectral characteristics of the surface EMG during tremor and the pattern of activity of single motor units.
Caldani L, Pacelli M, Farina D, et al., 2010, E-Textile platforms for rehabilitation., Pages: 5181-5184, ISSN: 2375-7477
This paper focus on SFIT platforms for rehabilitations and FES therapy. Two systems will be described, one developed to support patients during motor therapy, when they are still hospitalized, and after discharge, at home; the other is a sleeve integrating multi-electrodes patches, designed to allow FES therapy and EMG acquisition for patients affected by tremor. These examples prove that it is possible to combine fabric electrodes and biomechanical textile sensors to conceive systems where gesture recognition function can be combined with EMG detection and FES capability. These platforms can be easily used at home for daily therapy, as well as for telemedicine services.
Negro F, Holobar A, Farina D, 2009, Fluctuations in isometric muscle force can be described by one linear projection of low-frequency components of motor unit discharge rates., J Physiol, Vol: 587, Pages: 5925-5938
The aim of the study was to investigate the relation between linear transformations of motor unit discharge rates and muscle force. Intramuscular (wire electrodes) and high-density surface EMG (13 x 5 electrode grid) were recorded from the abductor digiti minimi muscle of eight healthy men during 60 s contractions at 5%, 7.5% and 10% of the maximal force. Spike trains of a total of 222 motor units were identified from the EMG recordings with decomposition algorithms. Principal component analysis of the smoothed motor unit discharge rates indicated that one component (first common component, FCC) described 44.2 +/- 7.5% of the total variability of the smoothed discharge rates when computed over the entire contraction interval and 64.3 +/- 10.2% of the variability when computed over 5 s intervals. When the FCC was computed from four or more motor units per contraction, it correlated with the force produced by the muscle (62.7 +/- 10.1%) by a greater degree (P < 0.001) than the smoothed discharge rates of individual motor units (41.4 +/- 7.8%). The correlation between FCC and the force signal increased up to 71.8 +/- 13.1% when the duration and the shape of the smoothing window for discharge rates were similar to the average motor unit twitch force. Moreover, the coefficients of variation (CoV) for the force and for the FCC signal were correlated in all subjects (R(2) range = 0.14-0.56; P < 0.05) whereas the CoV for force was correlated to the interspike interval variability in only one subject (R(2) = 0.12; P < 0.05). Similar results were further obtained from measures on the tibialis anterior muscle of an additional eight subjects during contractions at forces up to 20% of the maximal force (e.g. FCC explained 59.8 +/- 11.0% of variability of the smoothed discharge rates). In conclusion, one signal captures most of the underlying variability of the low-frequency components of motor unit discharge rates and explains large part of the fluctuations in the motor
Kamavuako EN, Farina D, Yoshida K, et al., 2009, Relationship between grasping force and features of single-channel intramuscular EMG signals., J Neurosci Methods, Vol: 185, Pages: 143-150
The surface electromyographic (sEMG) signal can be used for force prediction and control in prosthetic devices. Because of technological advances on implantable sensors, the use of intramuscular EMG (iEMG) is becoming a potential alternative to sEMG for the control of multiple degrees-of-freedom (DOF). An invasive system is not affected by crosstalk, typical of sEMG, and provides more stable and independent control sites. However, intramuscular recordings provide more local information because of their high selectivity, and may thus be less representative of the global muscle activity with respect to sEMG. This study investigates the capacity of selective single-channel iEMG recordings to represent the grasping force with respect to the use of sEMG with the aim of assessing if iEMG can be an effective method for proportional myoelectric control. sEMG and iEMG were recorded concurrently from 10 subjects who exerted six grasping force profiles from 0 to 25/50N. The linear correlation coefficient between features extracted from iEMG and force was approximately 0.9 and was not significantly different from the degree of correlation between sEMG and force. This result indicates that a selective iEMG recording is representative of the applied grasping force and can be used for proportional control.
Gu Y, do Nascimento OF, Lucas M-F, et al., 2009, Identification of task parameters from movement-related cortical potentials., Med Biol Eng Comput, Vol: 47, Pages: 1257-1264
The study investigates the accuracy in discriminating rate of torque development (RTD) and target torque (TT) (task parameters) from electroencephalography (EEG) signals generated during imaginary motor tasks. Signals were acquired from nine healthy subjects during four imaginary isometric plantar-flexions of the right foot involving two RTDs (ballistic and moderate) and two TTs (30 and 60% of the maximal voluntary contraction torque), each repeated 60 times in random order. The single-trial EEG traces were classified with a pattern recognition approach based on wavelet coefficients as features and support vector machine (SVM) as classifier. Average misclassification rates were (mean +/- SD) 16 +/- 9% and 26 +/- 13% for discrimination of the two TTs under ballistic and moderate RTDs, respectively. RTDs could be discriminated with misclassification rates of 16 +/- 11% and 19 +/- 10% under high and low TT, respectively. These results indicate that differences in both TT and RTD can be detected from single-trial EEG traces during imaginary tasks.
Dideriksen JL, Falla D, Bækgaard M, et al., 2009, Comparison between the degree of motor unit short-term synchronization and recurrence quantification analysis of the surface EMG in two human muscles., Clin Neurophysiol, Vol: 120, Pages: 2086-2092
OBJECTIVE: To verify if non-linear recurrence analysis of the surface EMG is a suitable tool for assessing motor unit short-term synchronization. METHODS: Surface and intramuscular EMG signals were recorded from the abductor digiti minimi and vastus medialis muscles of 12 and 10 healthy men, respectively, during isometric contractions. In the abductor digiti minimi, EMG signals were additionally recorded after a contraction sustained for 1min at 50% of the maximal force. In both muscles, percent of determinism (%DET) was estimated from the surface EMG and common input strength (CIS) index was computed from motor unit recordings. RESULTS: For both muscles, CIS did not correlate with %DET (abductor digiti minimi: R(2)=0.11, P=0.12; vastus medialis: R(2)=0.04, P=0.56). Although the values of CIS for the vastus medialis were lower than those of the abductor digiti minimi (P<0.001), the %DET values did not differ between the two muscles (71.6+/-5.5% vs 66.9+/-8.7%; P=0.12). CONCLUSION: The variable %DET extracted from the surface EMG is a poor indicator of the degree of motor unit short-term synchronization. SIGNIFICANCE: The study provides a systematic evaluation of a technique previously proposed for the estimation of a clinically relevant characteristic of motor unit behavior.
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