On-line signal quality estimation of multichannel surface electromyograms.

When multichannel surface-electromyography (MCSEMG) systems are used, there is a risk of recording low-quality signals. Such signals can be confusing for analysis and interpretation and can be caused by power-line interference, motion artifacts or poor electrode-skin contact. Usually, the electrode-skin impedance is measured to estimate the quality of the contact between the electrodes and the skin. However, this is not always practical, and the contact can change over short time-scales. A fast method is described to estimate the quality of individual signals of monopolar MCSEMG recordings based on volume conduction of myo-electric signals. The characteristics of the signals were described using two descriptor variables. Outliers (extreme data points) were detected in the two-dimensional distributions of the descriptor variables using a non-parametric technique, and the quality of the signals was estimated by their outlier probabilities. The method's performance was evaluated using 1 s long signals visually classified as very poor (G 1), poor (G2) or good quality (G3). Recordings from different subjects, contraction levels and muscles were used. An optimum threshold at 0.05 outlier probability was proposed and resulted in classification accuracies of 100% and > 70% for G I and G2 signals, respectively, whereas <5% of the G3 signals were classified as poor. In conclusion, the proposed method estimated MCSEMG signal quality with high accuracy, compared with visual assessment, and is suitable for on-line implementation. The method could be applied to other multichannel sensor systems, with an arbitrary number of descriptor variables, when their distributions can be assumed to lie within a certain range.

Simultaneous estimation of muscle fibre conduction velocity and muscle fibre orientation using 2D multichannel surface electromyogram.

The paper presents a new approach for simultaneous estimation of muscle fibre conduction velocity (MFCV) and muscle fibre orientation (MFO) for motor units (MUs) in two-dimensional (2D) multichannel surface electromyography recordings. This is an important tool for detecting changes and abnormalities in muscle function and structure. In addition, simultaneous estimation of MFO and MFCV avoids the necessity of manual electrode alignment. The proposed method detected propagating MU action potentials (MUAPs) in a running time window as moving components in amplitude maps. Thereafter, estimations were obtained by fitting a three-dimensional function to these maps. The performance was evaluated using synthetic MU signals at 10 dB SNR and authentic biceps brachii measurements. Results demonstrated MFCV and MFO estimates with standard deviations of less than 0.05 m s(-1) and 1 degrees for simulated signals, and less than 0.2 m s(-1) and 4 degrees for experimental data. However, standard deviations as low as 0.12 m s(-1) and 1.6 degrees from real signals were demonstrated. It was concluded that the method performs as well as, or better than, linear array multichannel methods when individual propagating MUAPs can be identified, even if electrodes are not aligned with fibre direction.

An estimation of the influence of force decrease on the mean power spectral frequency shift of the EMG during repetitive maximum dynamic knee extensions.

Frequency analysis of myoelectric (ME) signals, using the mean power spectral frequency (MNF), has been widely used to characterize peripheral muscle fatigue during isometric contractions assuming constant force. However, during repetitive isokinetic contractions performed with maximum effort, output (force or torque) will decrease markedly during the initial 40-60 contractions, followed by a phase with little or no change. MNF shows a similar pattern. In situations where there exist a significant relationship between MNF and output, part of the decrease in MNF may per se be related to the decrease in force during dynamic contractions. This study estimated force effects on the MNF shifts during repetitive dynamic knee extensions. Twenty healthy volunteers participated in the study and both surface ME signals (from the right vastus lateralis, vastus medialis, and rectus femoris muscles) and the biomechanical signals (force, position, and velocity) of an isokinetic dynamometer were measured. Two tests were performed: (i) 100 repetitive maximum isokinetic contractions of the right knee extensors, and (ii) five gradually increasing static knee extensions before and after (i). The corresponding ME signal time-frequency representations were calculated using the continuous wavelet transform. Compensation of the MNF variables of the repetitive contractions was performed with respect to the individual MNF-force relation based on an average of five gradually increasing contractions. Whether or not compensation was necessary was based on the shape of the MNF-force relationship. A significant compensation of the MNF was found for the repetitive isokinetic contractions. In conclusion, when investigating maximum dynamic contractions, decreases in MNF can be due to mechanisms similar to those found during sustained static contractions (force-independent component of fatigue) and in some subjects due to a direct effect of the change in force (force-dependent component of fatigue). In order to compare MNF shifts during sustained static and repetitive dynamic contractions it is necessary to estimate the force-dependent component of fatigue of dynamic contractions. Our results are preliminary and have to be confirmed in larger experiments using single dynamic contractions when determining the MNF-force relationship of the unfatigued situation.

Adaptive spatial filtering of multichannel surface electromyogram signals.

Spatial filtering of surface electromyography (EMG) signals can be used to enhance single motor unit action potentials (MUAPs). Traditional spatial filters for surface EMG do not take into consideration that some electrodes could have poor skin contact. In contrast to the traditional a priori defined filters, this study introduces an adaptive spatial filtering method that adapts to the signal characteristics. The adaptive filter, the maximum kurtosis filter (MKF), was obtained by using the linear combination of surrounding channels that maximises kurtosis. The MKF and conventional filters were applied to simulated EMG signals and to real EMG signals recorded with an electrode grid to evaluate their performance in detecting single motor units. The MKF was compared with conventional spatial filtering methods. Simulated signals, with different levels of spatially correlated noise, were used for comparison. The influence of one electrode with poor skin contact was also investigated. The MKF was found to be considerably better at enhancing a single MUAP than conventional methods for all levels of spatial correlation of the noise. For a spatial correlation of 0.97 of the noise, the improvement in the signal-to-noise ratio, where a MUAP could be detected, was at least 6dB. With a simulated poor skin contact for one electrode, the improvement over the other methods was at least 19 dB.

Duration of differential activations is functionally related to fatigue prevention during low-level contractions.

The aim of this study was to investigate the importance of duration of differential activations between the heads of the biceps brachii on local fatigue during prolonged low-level contractions. Fifteen subjects carried out isometric elbow flexion at 5% of maximal voluntary contraction (MVC) for 30 min. MVCs were performed before and at the end of the prolonged contraction. Surface electromyographic (EMG) signals were recorded from both heads of the biceps brachii. Differential activation was analysed based on the difference in EMG amplitude (activation) between electrodes situated at the two heads. Differential activations were quantified by the power spectral median frequency of the difference in activation between the heads throughout the contraction. The inverse of the median frequency was used to describe the average duration of the differential activations. The relation between average duration of the differential activations and the fatigue-induced reduction in maximal force was explored by linear regression analysis. The main finding was that the average duration of differential activation was positively associated to relative maximal force at the end of the 30 min contraction (R(2)=0.5, P<0.01). The findings of this study highlight the importance of duration of differential activations for local fatigue, and support the hypothesis that long term differential activations prevent fatigue during prolonged low-level contractions.

Motor unit synchronization during fatigue: described with a novel sEMG method based on large motor unit samples.

The amount of documented increase in motor unit (MU) synchronization with fatigue and its possible relation with force tremor varies largely, possibly due to inhomogeneous muscle activation and methodological discrepancies and limitations. The aim of this study was to apply a novel surface electromyographical (EMG) descriptor for MU synchronization based on large MU populations to examine changes in MU synchronization with fatigue at different sites of a muscle and its relation to tremor. Twenty-four subjects performed an isometric elbow flexion at 25% of maximal voluntary contraction until exhaustion. Monopolar EMG signals were recorded using a grid of 130 electrodes above the biceps brachii. Changes in MU synchronization were estimated based on the sub-band skewness of EMG signals and tremor by the coefficient of variation in force. The synchronization descriptor was dependent on recording site and increased with fatigue together with tremor. There was a general association between these two parameters, but not between their fluctuations. These results are in agreement with other surface EMG studies and indicate that the novel descriptor can be used to attain information of synchronization between large MU populations during fatigue that cannot be retrieved with intra-muscular EMG.

Motor unit synchronization during fatigue: a novel quantification method.

Motor unit (MU) synchronization is the result of commonality in the pre-synaptic input to MUs. Previously proposed techniques to estimate MU synchronization based on invasive and surface electromyography (sEMG) recordings have been, respectively, limited by the analyzed MU population size and influence of changes in muscle fibre conduction velocities (MFCVs). The aim of this paper was to evaluate a novel descriptor of MU synchronization on a large MU population, and to minimize its dependency on MFCV. The method is based on the asymmetry of MU action potentials, causing synchronized MU action potentials to skew the monopolar sEMG signal distribution. The descriptor was the skewness statistic used on sub-band filtered monopolar sEMG signals (sub-band skewness). The method was evaluated using simulated signals and its performance was evaluated in terms of bias and sensitivity of the sub-band skewness quantifying the MU synchronization level. The best sensitivity was obtained using sub-band filtering at scale 5 (Mexican hat wavelet). The sensitivity was in general about 0.1units per 5% MU synchronization level. Changes in MFCV had a minimal influence, and caused at most a 5% deviant MU synchronization quantification level. A halved recruitment level had higher bias and a 20% lower sensitivity. Increased firing rate (14-34Hz) reduced the sensitivity about 50%. The sensitivity of the descriptor was robust to noise, and different volume conduction properties. It should be noted that the sub-band skewness comprises a subject-dependent component implying that only changes in MU synchronization level can be quantified.

Selective activation of neuromuscular compartments within the human trapezius muscle.

Task-dependent differences in relative activity between "functional" subdivisions within human muscles are well documented. Contrary, independent voluntary control of anatomical subdivisions, termed neuromuscular compartments is not observed in human muscles. Therefore, the main aim of this study was to investigate whether subdivisions within the human trapezius can be independently activated by voluntary command using biofeedback guidance. Bipolar electromyographical electrodes were situated on four subdivisions of the trapezius muscle. The threshold for "active" and "rest" for each subdivision was set to >12% and <1.5% of the maximal electromyographical amplitude recorded during a maximal voluntary contraction. After 1h with biofeedback from each of the four trapezius subdivisions, 11 of 15 subjects learned selective activation of at least one of the four anatomical subdivisions of the trapezius muscle. All subjects managed to voluntarily activate the lower subdivisions independently from the upper subdivisions. Half of the subjects succeeded to voluntarily activate both upper subdivisions independently from the two lower subdivisions. These findings show that anatomical subdivisions of the human trapezius muscle can be independently activated by voluntary command, indicating neuromuscular compartmentalization of the trapezius muscle. The independent activation of the upper and lower subdivisions of the trapezius is in accordance with the selective innervation by the fine cranial and main branch of the accessory nerve to the upper and lower subdivisions. These findings provide new insight into motor control characteristics, learning possibilities, and function of the clinically relevant human trapezius muscle.

Differential activation of regions within the biceps brachii muscle during fatigue.

AIM: To examine the occurrence of repeated differential activation between the heads of the biceps brachii muscle and its relation to fatigue prevention during a submaximal contraction. METHODS: Thirty-nine subjects carried out an isometric contraction of elbow flexion at 25% of maximal voluntary contraction (MVC) until exhaustion. A grid of 13 by 10 electrodes was used to record surface electromyographic signals from both heads of the biceps brachii. The root-mean-square of signals recorded from electrodes located medially and laterally was used to analyse activation differences. Differential activation was defined as periods of 33% different activation level between the two heads of the biceps brachii muscle. RESULTS: Differential muscle activation was demonstrated in 30 of 33 subjects with appropriate data quality. The frequency of differential activation increased from 4.9 to 6.6 min(-1) at the end of the contractions with no change in duration of the differential activations (about 1.4 s). Moreover, the frequency of differential activation was, in general, negatively correlated with time to exhaustion. CONCLUSION: The observed differential activation between the heads of the biceps brachii can be explained by an uneven distribution of synaptic input to the motor neurone pool. The findings of this study indicate that differential activation of regions within a muscle does not prevent fatigue at a contraction level of 25% of MVC.

A flexible measurement system for physiological signals in mobile health care.

In the nearest future a lot of post-operative treatment and health monitoring is going to be performed in people's homes instead of in hospital. The increasing number of elderly people in the developed countries and the need for more advanced medical treatment and equipment in conjunction with economical demands will force the development of more cost-effective solutions. The equipment used must be very rugged and safe for both the patient and the operator and easily configured for a number of different measurement parameters. In most cases storing data on a memory card in the equipment will be sufficient but sometimes a wireless real-time measurement system is needed. This paper presents an acquisition system flexible enough for a number of different applications, home care, mobile health care and other biomedical measurement situations. A prototype system has been tested with sufficient performance for several physiological signals.