Time-frequency coherence of categorized sEMG data during dynamic contractions of biceps, triceps, and brachioradialis as an approach for spasticity detection.

The assessment of muscular interactions between biceps, triceps, and brachioradialis can be used as an approach for the detection of spasticity in the upper limbs. A crucial prerequisite for the aforementioned validation of muscular interactions is the calculation of time frequencies due to the non-stationary characteristics of electromyographic (EMG) signals and thus the estimation of coherences. Adding biomechanical parameters increases the validity of the assessment process and simplifies the comparison of EMG data as a result of categorization. In this numerical-experimental study, a method will be introduced by using the smoothed pseudo Wigner-Ville distribution and a categorization algorithm to estimate and categorize coherences between biceps, triceps, and brachioradialis during dynamic contractions. The categorization will be performed according to the type of contraction, external load, joint angle, and angular velocity and will be used to assess 10 healthy subjects and 6 patients with spasticity. Generally, the introduced method shows the velocity dependence of coherence during spasticity in extension movements as well as much stronger muscular co-activation between triceps, biceps, and brachioradialis in spastic patients in comparison to healthy subjects. Furthermore, the influence of variables e.g. as joint angle, angular velocities, and type of contraction on the coherence is quantified.

Movement analysis in the early detection of newborns at risk for developing spasticity due to infantile cerebral palsy.

In order to limit the consequences of infantile cerebral palsy (ICP), physiotherapy should start as early as possible. This requires that infants at risk are detected at the earliest age possible. Today, diagnosis is based on visual observation by physicians and as such is influenced by subjective impressions. Objective methods, quantifying the pathological deviation from normal spontaneous motor activity would be preferable as they, for example, allow an inter- and intra-individual comparison of movement. In this paper we have developed a methodology that allows the 3-dimensional acquisition of unconstrained movement in newborn babies, using a motion analysis system. From the recorded movement data we have extracted 53 quantitative parameters that describe the differences between healthy and affected participants. Considered individually, each of these parameters does not permit a conclusive statement to be made as to whether or not the patient is at risk. Cluster analysis based on Euclidian distances therefore has been used to find an optimal combination of eight parameters. The optimal combination has been subsequently applied to organize the participants' movement into preferably homogeneous classes labelled "healthy" or "at risk". Classification was performed utilising quadratic discriminant analysis. The methodology presented allows a reliable discrimination between healthy and affected participants. Overall detection rate reached 73%. This value is expected to rise with increasing patient and norm collective database size.

Estimation of the muscle fibre semi-length under varying joint positions on the basis of non-invasively extracted motor unit action potentials.

Changes in muscle fibre length and surface electrode position with respect to the muscle fibres affect the amplitude and frequency characteristics of surface electromyography (SEMG) in different ways. Knowledge of changes in muscle fibre length would help towards a better interpretation of the signals. The possibility of estimating the length through SEMG during voluntary contractions was checked in this study. The fibres' semi-length was estimated from the product of the conduction velocity and conduction time during which the wave of excitation propagated from the end-plate region to the ends of the fibres. Short (10 s), moderate (30% of maximum voluntary contraction) isometric contractions were performed by 10 subjects at different elbow joint angles (80-140 degrees in steps of 20 degrees ). Monopolar signals were detected non-invasively, using a two-dimensional electrode array. High spatial resolution EMG and a decomposition technique were utilised to extract single motor unit activities for triggered averaging and to estimate conduction velocity. A significant increase with joint angle was found in conduction time and estimated fibre semi-length. Changes in conduction velocity with joint angle were found to be not significant. The methodology described allows the relative changes in fibres' semi-length to be estimated from SEMG data.

Experimental muscle pain increases trapezius muscle activity during sustained isometric contractions of arm muscles.

OBJECTIVE: In the present study, the influence of experimental muscle pain on muscle co-ordination and fatigue development during sustained isometric elbow flexion was investigated. METHODS: Conventional surface electromyography (EMG) was recorded from the biceps brachii, brachioradialis, deltoideus and trapezius muscle during isometric elbow flexion at 40% maximum force. Single motor unit (MU) conduction velocity in the biceps brachii was assessed using a high spatial resolution surface EMG technique. Measurements were performed on 15 healthy subjects before, during and after (1) injection of hypertonic (pain condition) and (2) isotonic saline (control) into the biceps brachii. The pain intensity was assessed on a 10 cm visual analogue scale. RESULTS: The experimental results showed in both experimental sessions a fatigue-related increase of the root mean square value of EMG (222+/-164% of the baseline), and a decrease of the median frequency (118+/-16% of the baseline) in all investigated muscles. A maximum pain level of in average 3.2 cm on the visual analogue scale was reached after injection of hypertonic saline during contraction. Differences between painful and control condition were seen in an increased trapezius activity (230+/-141%) during pain. The global EMG activity of the brachioradialis and biceps brachii was unaffected by experimental muscle pain in line with unaffected single MU conduction velocity in the biceps brachii. Differences in endurance time (mean 89.3 and 102.3 s, pain and control, respectively) were not significant. CONCLUSIONS/SIGNIFICANCE: The findings suggest that upper extremity pain could be a possible source for overloading the trapezius muscle and as such is an important factor in occupational settings.

Movement biomechanics goes upwards: from the leg to the arm.

The analysis of lower limb movements has been well established in biomechanics research and clinical applications for a long time. For these studies, powerful and very advanced tools have been developed to measure movement parameters and reaction forces. The main focus of interest aims towards gait movements while the understanding of the basic concepts is supported by numerous models. Definitions of physiological ranges and detection of pathological changes in movements open an increasingly valuable clinical field of application. If, however, the primary function of the upper extremities as highly variable and adaptive organ for manipulating tasks is the subject of interest, the situation becomes considerably more complex. The nature of free arm movements is completely different from being restricted, repeatable or cyclic as compared to gait. Therefore, the transfer of the knowledge and experience gained in lower extremity movement analysis to the analysis of upper extremities turns out to be difficult. A proposal for how to proceed in measurements, e.g. where to place the markers and how to calculate movements and angles of segments involved, will be discussed which results in the description of the joint movements of wrist, elbow and shoulder joint. The definition of the motion is a specific step in upper extremity motion analysis which is important in terms of repeatability and significance of the results. An example of assessing movement disorders in children with plexus lesion will illustrate the implications and the potential of upper extremity movement analysis in clinical applications.

Noninvasive approach to motor unit characterization: muscle structure, membrane dynamics and neuronal control.

The standard surface EMG reflects the compound activity of a high number of motor units which is finally due to its low spatial resolution in the detection of the potential distribution on the skin surface. Therefore, detailed information about the structural and functional characteristics of the muscle consisting of populations of motor units, like the functional anatomy, the excitation spread or the innervation pattern cannot be obtained from the standard surface EMG. A novel noninvasive EMG-procedure with high spatial resolution (HSR-EMG) allows in contrast to the standard surface EMG even the detection of the single motor unit activity. In this way, the noninvasive determination of detailed information about the muscle structure, the membrane dynamics and the neuronal control becomes possible. First applications of the HSR-EMG have shown that especially the noninvasively measured conduction velocity of the excitation is highly affected by physiological details, like the muscle temperature, the relative muscle fibre diameter or inhomogeneities in the connective tissue forming part of the volume conductor around the muscle. From the results of the HSR-EMG investigations it can be concluded that the information about the structural and functional characteristics of the muscle as well as a deeper insight in the active state of the muscle is essential for a correct interpretation of the standard surface EMG.

A marker-based measurement procedure for unconstrained wrist and elbow motions.

A protocol is proposed to obtain the joint angles of wrist and elbow from tracked triads of surface markers on each limb segment. Cuffs placed on the limb support the rigidity of the triads. Additional markers are used to mark the approximate positions of joints. Corrections of surface marker data for skin motion are derived from a priori knowledge about plausible joint motions. In addition, ill-conditioned states are trapped when the elbow is nearly fully extended. The protocol is applied to sample motions which demonstrate the use and the effect of the corrections. The results show that the model assumptions are reasonable and that accurate joint rotations can be obtained. The correction steps prove to be an essential part of upper-extremity movement analysis.

Improvement of spatial resolution in surface-EMG: a theoretical and experimental comparison of different spatial filters.

The conventional bipolar surface electromyography (EMG) technique detects, due to its low spatial resolution, the superimposed electromyographic activity of a large number of motor units (MU's). In superficial muscles the isolated action potentials of the most superficial MU's can be recorded noninvasively by means of surface electrodes, if the method of spatial filtering, in connection with electrode arrays, is used. Up to now, only filters with an anisotropic transfer function have been used. As the surface potential distribution generated by the excitation of the MU's contains spatial frequencies in the anisotropic range of those filters, it can be assumed that isotropic spatial filters detect the single MU activity more effectively. In the present study, different isotropic and anisotropic filters have been compared by means of theoretical field simulations and experiments in volunteers. A tripole model for an excited MU was used as the basis for simulating the spatial extension of the filter response for each of the investigated filters. The spatial extension is an indicative of the spatial resolution. For the experimental validation, the total number of single motor units was not directly investigated, but the signal-to-noise ratio (SNR) has been determined. Therefore, the potential distribution generated on the skin surface during maximum voluntary contraction has been simultaneous spatially filtered with each of the investigated filters. The simulations show that an isotropic spatial filtering procedure reduces the spatial extension of the filter response and improves the spatial resolution of the EMG-recording arrangement in comparison to anisotropic spatial filters up to 30%. In other words, the spatial selectivity of the arrangement is increased. This improvement in the filter performance is more pronounced for MU's located close to the skin surface than for MU's more distantly located. Additionally, this theoretical improvement in selectivity depends on the direction of the excitation spread relative to the filter alignment. However, the investigations also show that isotropic filters offer an advantage, compared to anisotropic filters, only when the investigated MU is located extremely close to the filter input. The results of the simulations can be confirmed by the experimental investigations. An improvement of 11% in the SNR, relative to anisotropic spatial filters, can be established when using an isotropic spatial filter. This experimental improvement in selectivity is less than the theoretical improvement because the experimentally investigated MU's have less portion in the anisotropic range of the filters than the simulated one at best.

From cell to movement: to what answers does EMG really contribute?

This paper aims to address some of the possibilities and limitations of EMG technologies available to date. Considerable progress has been achieved in this field during the last 30 years and EMG signals can be easily obtained on different levels beginning at the cell membrane and ending with the global EMG associated with the movement itself. Different aspects from cell to movement have been considered in this paper. Highly selective needle EMG for the detection of the processes at the membrane is discussed as well as high spatial resolution EMG which gives non-invasive access to the acquisition of the single motor unit activity. On the highest level of muscles, an expert system is introduced as a novel approach to support the interpretation of muscular co-ordination as detected by conventional surface EMG. While there is a high potential in the newly developed EMG methodologies, it is a big challenge to utilize these methodologies in order to obtain detailed, repeatable, reliable--and meaningful--results. However, the risk of over- and misinterpretation has to be carefully considered. In this paper, this risk is exemplified in situations dealing with muscle fatigue, conduction velocity and cross-talk. Despite all the new possibilities available, the authors recommend that EMG with its inherent strengths and limitations should still be diligently, but carefully, used.

Estimation of the relationship between the noninvasively detected activity of single motor units and their characteristic pathological changes by modelling.

Neuromuscular disorders are often related to specific changes in the structure of single motor units (MUs). One approach for the detection of these changes is high-spatial-resolution EMG (HSR-EMG), which allows non-invasive recording of the activity of a single MU. Early investigations with patients suffering from various neuromuscular disorders have shown that there is a distinct difference between the HSR-EMG signals of healthy volunteers, patients with muscular disorders, and patients with neuronal disorders. In this study, the relationship between typical HSR-EMG patterns and characteristic pathological changes in the structure of the MUs is considered. Therefore, a muscle model has been developed which is adapted to the physiological properties of the m. abductor pollicis brevis. The effects of the loss of single muscle fibres (muscular disorders) and the loss of entire MUs (neuronal disorders) on the HSR-EMG pattern have been simulated. These simulations show the same HSR-EMG patterns as seen in patients and healthy volunteers. As a consequence, it can be assumed that the muscle model is an appropriate tool for the simulation of HSR-EMG signals. Furthermore, the simulation results support the hypothesis that the typical changes in the HSR-EMG pattern found in patients with neuromuscular disorders can be attributed to the characteristic changes in the structure of the MUs.

Development of recommendations for SEMG sensors and sensor placement procedures.

The knowledge of surface electromyography (SEMG) and the number of applications have increased considerably during the past ten years. However, most methodological developments have taken place locally, resulting in different methodologies among the different groups of users.A specific objective of the European concerted action SENIAM (surface EMG for a non-invasive assessment of muscles) was, besides creating more collaboration among the various European groups, to develop recommendations on sensors, sensor placement, signal processing and modeling. This paper will present the process and the results of the development of the recommendations for the SEMG sensors and sensor placement procedures. Execution of the SENIAM sensor tasks, in the period 1996-1999, has been handled in a number of partly parallel and partly sequential activities. A literature scan was carried out on the use of sensors and sensor placement procedures in European laboratories. In total, 144 peer-reviewed papers were scanned on the applied SEMG sensor properties and sensor placement procedures. This showed a large variability of methodology as well as a rather insufficient description. A special workshop provided an overview on the scientific and clinical knowledge of the effects of sensor properties and sensor placement procedures on the SEMG characteristics. Based on the inventory, the results of the topical workshop and generally accepted state-of-the-art knowledge, a first proposal for sensors and sensor placement procedures was defined. Besides containing a general procedure and recommendations for sensor placement, this was worked out in detail for 27 different muscles. This proposal was evaluated in several European laboratories with respect to technical and practical aspects and also sent to all members of the SENIAM club (>100 members) together with a questionnaire to obtain their comments. Based on this evaluation the final recommendations of SENIAM were made and published (SENIAM 8: European recommendations for surface electromyography, 1999), both as a booklet and as a CD-ROM. In this way a common body of knowledge has been created on SEMG sensors and sensor placement properties as well as practical guidelines for the proper use of SEMG.

Non-invasive detection of the single motor unit action potential by averaging the spatial potential distribution triggered on a spatially filtered motor unit action potential.

For research as well as diagnostic applications the non-invasive detection of the activity of single motor units is of interest. The most direct information is expected to be found in monopolarly recorded data. But when an array of surface electrodes is used for the monopolar recordings of the potential distribution on the skin, in most cases an additional invasive needle electrode is utilized to detect the exact points in time when a certain motor unit is firing. With this supplementary information, an averaging of the monopolar EMG tracings can be performed. In this paper, a completely non-invasive methodology is presented which replaces the invasive needle by a spatial filtering procedure. The EMG signals from the m. biceps brachii are recorded monopolarly with an electrode array. Afterwards, a spatial filtering procedure, called normal double differentiating filter, is applied to the data. The EMG signals obtained are investigated by means of an amplitude threshold to distinguish the activity of different motor units. The point of the maximum amplitude of the selected peaks then is used as trigger point to average the monopolar EMG data. The time courses of the motor unit action potential signals found after applying the described procedure show similar shapes, while two different components are to be identified: corresponding to the spread of the excitation, one is referring to stationary, the other to travelling events. These results justify the possibility to replace the needle electrode to obtain a trigger event in the future by the non-invasive spatial filtering procedure.

Influence of muscle fibre shortening on estimates of conduction velocity and spectral frequencies from surface electromyographic signals.

The study of surface electromyographic (EMG) signals under dynamic contractions is becoming increasingly important. However, knowledge of the methodological issues that may affect such analysis is still limited. The aim of the study was to analyse the effect of fibre shortening on estimates of conduction velocity (CV) and mean power spectral frequency (MNF) from surface EMG signals. Single fibre action potentials were simulated, as detected by commonly used spatial filters, for different fibre lengths. No physiological modifications were included with changes in fibre length, and thus only geometrical artifacts related to fibre shortening were investigated. The simulation results showed that the dependence of CV and MNF on fibre shortening is affected by the fibre location, electrode position and the spatial filter applied. With shortening of up to 50% for a fibre of 50 mm semi-length, the variations in CV and MNF estimates with shortening in bipolar recordings were 0.5% (CV) and 0.7% (MNF) for superficial fibres, and 3.6% and 5.1% for deeper fibres. Using the longitudinal double differential filter, under the same conditions, the percent variation was 0% and 0.2%, and 24.7% and 15.8%, respectively. The main conclusions were, first, muscle fibre shortening can significantly affect estimates of CV and MNF, especially for short fibre lengths. However, for long (semi-length >50 mm) and superficial fibres, this effect is limited for shortenings of up to 50% of the initial fibre length. Secondly, CV and MNF are almost equally affected by changes in muscle length; and, thirdly, sensitivity to fibre shortening depends on the spatial filter applied for signal detection.

Single motor unit analysis from spatially filtered surface electromyogram signals. Part I: spatial selectivity.

The aim of the study was to compare experimentally, on the basis of single motor unit (MU) activities, the selectivity of different spatial filters commonly used to detect surface electromyogram (EMG) signals. Surface EMG signals were recorded from the biceps brachii and the upper trapezius muscle of five subjects using a two-dimensional (2D) electrode array consisting of 16 pin electrodes. The subjects performed isometric contractions at different elbow angles and shoulder abduction and flexion. The same monopolar surface EMG signals were filtered using longitudinal single and double differential, transverse single and double differential and normal double differential filters. From the single MU action potentials, extracted by automatic EMG decomposition, indexes of transverse (perpendicular with respect to the fibre direction) and longitudinal (along the fibre direction) selectivity were computed. The number of detected MUs was 46 for the upper trapezius, with the arms held in the sagittal plane, and 52 when the arms were held in the frontal plane; 85 MUs were identified from the biceps brachii contractions. The results showed that transverse selectivity was significantly higher for the 2D and transverse one-dimensional (1D) filters with respect to the 1D longitudinal filters, whereas longitudinal selectivity was higher (i.e. MU action potentials were shorter) for the 2D filter and the longitudinal double differential filter. In particular, the relative attenuation of potential amplitude moving 5 mm from the source was, on average (for the two muscles), 16.5% for the least selective filter in the transverse direction (longitudinal single differential) and 35.7% for the most selective one in the same direction (transverse double differential). The MU action potential duration was, on average, 13.8 ms for the most selective filter in the longitudinal direction (longitudinal double differential) and 18.7 ms for the least selective one (transverse double differential). The normal double differential filter resulted in spatial selectivity indexes that ware not statistically different in the two directions from those of the best filters in each direction.

Single motor unit analysis from spatially filtered surface electromyogram signals. Part 2: conduction velocity estimation.

The aim of the study was to compare experimentally conduction velocity (CV) estimates obtained with different estimation methods based on surface electromyogram (EMG) signals detected using five spatial filters. The filters investigated were the longitudinal single and double differential, transverse single and double differential, and normal double differential. The same surface EMG signals detected as described in Part 1 were used in this work. CV was estimated with four commonly used delay estimation techniques, i.e. from the distance between the peak values of two waveforms (with and without polynomial interpolation around the peak), and by the maximum likelihood estimate (MLE) based on two or more surface EMG channels. The average standard deviation of CV estimation (for all the MUs and the two muscles together) was 0.61 m s(-1) and 0.79 m s(-1) for the peak method, with and without interpolation, respectively, and 0.50 m s(-1) and 0.31 m s(-1) for the MLE method, from two and more surface EMG channels, respectively. Moreover, the mean of CV estimates varied by as much as 1 m s(-1) depending on the spatial filter used and the method adopted for CV estimation. Considering the dependence on the spatial filter only, the average (over all estimation methods) CV estimates obtained with the five spatial filters were 4.32 m s(-1) (normal double differential), 4.23 m s(-1) (longitudinal double differential), 4.61 m s(-1) (transverse double differential), 4.64 m s(-1) (transverse single differential) and 4.03 m s(-1) (longitudinal single differential). It was concluded that the comparison of single MU CV values obtained in different studies is critical if different spatial filters and processing techniques are used for their estimation. Higher estimates of CV were attributed to a smaller reduction in non-travelling signal components and thus were assumed to be positively biased.

Area-to-amplitude ratio of the terminal phase of the belly-tendon detected motor unit potentials could be used to recognize reinnervated motor units.

Besides the increased number of fibres, the reinnervated motor units (MUs) are characterised by an increased scattering the end-plates, greater desynchronization in the fibres' activation, greater dispersion in the diameters of the MU fibres and thus in propagation velocities along them. As a result, desynchronization in the moments, at which the excitation waves reach the fibres' ends, increases in reinnervated MUs. The possibility to recognize reinnervated MUs in short (hand) muscles on the basis of changes in duration of the terminal (second) phase of the belly-tendon detected motor unit potentials (MUPs) was examined by numerical experiments. A convolution model that took into account the finite fibre length, was used to calculate MUPs for distances typical of surface detection. It was shown that the ratio between the area of the terminal phase and its amplitude, as a measure of duration of the terminal phase, was sensitive to desynchronisation of the waves of excitation. The ratio was independent of the distance from the MU axis and of the volume conductor properties. Basing on the results obtained, we can conclude that the ratio reflects main functional compensations in reinnervated MUs and could be used for discrimination between reinnervated and normal MUs.

Surface detected potentials of normal and reinnervated motor units: a simulation study for muscles consisted of short fibres.

We aimed to check whether the characteristics used up to now in macro EMG to distinguish between normal and reinnervated motor unit potentials (MUPs), were suitable for surface detected MUPs. MUPs produced by normal and reinnervated MUs were simulated with a fast and precise convolution model. An increased number of fibres in the MU territory enhanced the amplitude, area and RMS of the MUP proportionally irrespective of the MU-electrode distance. An increased scatter of the end-plates and greater desynchronization in the fibres' activation decreased the MUP amplitude and affected the temporal characteristics of the MUP (duration of the negative phase and its area to amplitude ratio). The effects were more pronounced at shorter distances. At larger distances, the effect of the MU-electrode distance on temporal and amplitude characteristics of MUPs was much stronger than that of the parameters changed with reinnervation. We conclude that reinnervated MUs consisting of short fibres can not be distinguished from the normal ones by means of characteristics of MUP used in macro EMG. To discriminate reinnervated MUs non-invasively, the MUP amplitude should be normalized in respect of the MU-electrode distance or other MUP characteristics (independent of MU-electrode distance and sensitive to reinnervation) should be used.

The presence of unknown layer of skin and fat is an obstacle to a correct estimation of the motor unit size from surface detected potentials.

To overcome problems with a strong distance-dependence of the motor unit potentials (MUPs), different methods to estimate the MU location and size have been proposed. Distance-independence of the exponent of the power function, that describes the MUP distance decline, and homogeneity of the volume conductor, are assumed in all methods. Some of them consider the exponent value as unique, irrespective of persons, muscles and their functional state. One method estimates the current exponent value. We evaluate this method by computer simulation of MUPs in infinite and semi-infinite volume conductor. Our results show that although the first assumption is not fulfilled, it does not affect considerably the estimate of the MU location and size obtained for infinite or semi-infinite homogeneous volume conductor. The errors of the MU location can be insignificant even in inhomogeneous volume conductor with a layer of lower conductivity (skin and fat) between the muscle tissue and electrode. The accurate location of the MU electrical axis is, however, not a sufficient condition for a correct MU size estimation that depends considerably on actual parameters of the layer. Thus, the surface EMG could hardly be considered as non-invasive alternative to macro EMG for detection of the enlarged MUs.