Mónica Rojas-Martínez

High-density surface EMG maps from upper-arm and forearm muscles

BackgroundsEMG signal has been widely used in different applications in kinesiology and rehabilitation as well as in the control of human-machine interfaces. In general, the signals are recorded with bipolar electrodes located in different muscles. However, such configuration may disregard some aspects of the spatial distribution of the potentials like location of innervation zones and the manifestation of inhomogineties in the control of the muscular fibers. On the other hand, the spatial distribution of motor unit action potentials has recently been assessed with activation maps obtained from High Density EMG signals (HD-EMG), these lasts recorded with arrays of closely spaced electrodes. The main objective of this work is to analyze patterns in the activation maps, associating them with four movement directions at the elbow joint and with different strengths of those tasks. Although the activation pattern can be assessed with bipolar electrodes, HD-EMG maps could enable the extraction of features that depend on the spatial distribution of the potentials and on the load-sharing between muscles, in order to have a better differentiation between tasks and effort levels.MethodsAn experimental protocol consisting of isometric contractions at three levels of effort during flexion, extension, supination and pronation at the elbow joint was designed and HD-EMG signals were recorded with 2D electrode arrays on different upper-limb muscles. Techniques for the identification and interpolation of artifacts are explained, as well as a method for the segmentation of the activation areas. In addition, variables related to the intensity and spatial distribution of the maps were obtained, as well as variables associated to signal power of traditional single bipolar recordings. Finally, statistical tests were applied in order to assess differences between information extracted from single bipolar signals or from HD-EMG maps and to analyze differences due to type of task and effort level.ResultsSignificant differences were observed between EMG signal power obtained from single bipolar configuration and HD-EMG and better results regarding the identification of tasks and effort levels were obtained with the latter. Additionally, average maps for a population of 12 subjects were obtained and differences in the co-activation pattern of muscles were found not only from variables related to the intensity of the maps but also to their spatial distribution.ConclusionsIntensity and spatial distribution of HD-EMG maps could be useful in applications where the identification of movement intention and its strength is needed, for example in robotic-aided therapies or for devices like powered- prostheses or orthoses. Finally, additional data transformations or other features are necessary in order to improve the performance of tasks identification.

Cross-conditional entropy and coherence analysis of pharmaco-EEG changes induced by alprazolam

RationaleQuantitative analysis of electroencephalographic signals (EEG) and their interpretation constitute a helpful tool in the assessment of the bioavailability of psychoactive drugs in the brain. Furthermore, psychotropic drug groups have typical signatures which relate biochemical mechanisms with specific EEG changes.ObjectivesTo analyze the pharmacological effect of a dose of alprazolam on the connectivity of the brain during wakefulness by means of linear and nonlinear approaches.MethodsEEG signals were recorded after alprazolam administration in a placebo-controlled crossover clinical trial. Nonlinear couplings assessed by means of corrected cross-conditional entropy were compared to linear couplings measured with the classical magnitude squared coherence.ResultsLinear variables evidenced a statistically significant drug-induced decrease, whereas nonlinear variables showed significant increases. All changes were highly correlated to drug plasma concentrations. The spatial distribution of the observed connectivity changes clearly differed from a previous study: changes before and after the maximum drug effect were mainly observed over the anterior half of the scalp. Additionally, a new variable with very low computational cost was defined to evaluate nonlinear coupling. This is particularly interesting when all pairs of EEG channels are assessed as in this study.ConclusionsResults showed that alprazolam induced changes in terms of uncoupling between regions of the scalp, with opposite trends depending on the variables: decrease in linear ones and increase in nonlinear features. Maps provided consistent information about the way brain changed in terms of connectivity being definitely necessary to evaluate separately linear and nonlinear interactions.

A Novel Spatial Feature for the Identification of Motor Tasks Using High-Density Electromyography

Estimation of neuromuscular intention using electromyography (EMG) and pattern recognition is still an open problem. One of the reasons is that the pattern-recognition approach is greatly influenced by temporal changes in electromyograms caused by the variations in the conductivity of the skin and/or electrodes, or physiological changes such as muscle fatigue. This paper proposes novel features for task identification extracted from the high-density electromyographic signal (HD-EMG) by applying the mean shift channel selection algorithm evaluated using a simple and fast classifier-linear discriminant analysis. HD-EMG was recorded from eight subjects during four upper-limb isometric motor tasks (flexion/extension, supination/pronation of the forearm) at three different levels of effort. Task and effort level identification showed very high classification rates in all cases. This new feature performed remarkably well particularly in the identification at very low effort levels. This could be a step towards the natural control in everyday applications where a subject could use low levels of effort to achieve motor tasks. Furthermore, it ensures reliable identification even in the presence of myoelectric fatigue and showed robustness to temporal changes in EMG, which could make it suitable in long-term applications.

Evaluación de la función neuromuscular del antebrazo durante contracciones isométricas mediante electromiografía de superficie multicanal

An experimental protocol has been designed with specific exercises and the study of forearm muscles which are related with repetitive effort disorders (RED) and myalgia . The analysis and results obtained in a control group by multichannel surface electromyography (EMG) have validated this technique in order to be applied in patients such as diagnosis help or assessment of muscles changes during rehabilitation processes. Variables of interest from EMG signals have been defined and calculated during the protocol resulting repetitive. Multichannel surface EMG has permitted to obtain activation pattern of three extensor muscles and one flexor during fingers isometric flexion and to obtain the dependence on the pressure developed by different fingers which will be very interesting in the monitoring of myalgia in pianist musicians. Thanks to the electrodes matrices, muscle fatigue of the flexor and one extensor have been detected along endurance exercises. Finally, this non-invasive technique has been validated in exercises associates with RED and forearm muscles by detecting propagating action potentials with a good estimation of conduction velocity and, thus, permitting to obtain reliable data and information of muscle patterns.

Changes of HD-sEMG maps of the upper limb during isometric endurance contractions

Recent research in the field of surface EMG recorded with 2D electrode arrays have shown muscle adaptations as reflected on the spatial activation of motor units in response to pain, direction of movement or fatigue. The purpose of this study was to evaluate time- changes in the activation maps of upper limb muscles during endurance tasks associated with the degrees of freedom at the elbow joint. Preliminary results show time-variations in the distribution of intensity, that is, in the spatial recruitment of motor units, and that such changes may be dependent on the type of task.

Analysis of muscle coupling during isokinetic endurance contractions by means of nonlinear prediction

Isokinetic exercises have been extensively used in order to analyze muscle imbalances and changes associated with fatigue. It is known that such changes are difficult to assess from EMG signals during dynamic contractions, especially, using linear signal processing tools. The aim of this work was to use nonlinear prediction in order to analyze muscle couplings and interactions in this context and to assess the load-sharing of different muscles during fatigue. Results show promising for detecting interaction strategies between muscles and even for the interaction between muscles and the output torque during endurance tests.