A practice of caution: spontaneous action potentials or artifactual spikes?

BACKGROUND: High density surface electromyogram (EMG) techniques with electrode arrays have been used to record spontaneous muscle activity, which is important, both for supporting the diagnosis of neuromuscular diseases and for laboratory based neurophysiological investigations. This short report addresses a practical issue we have experienced during recording of spontaneous muscle activity using electrode arrays from subjects with major neuromuscular disorders. FINDINGS: We show that recording artifacts can appear similar to spontaneous action potential spikes. Moreover, a causal filter may induce asymmetric distortions of an artifact and thus confuse it with a real action potential spike. As a consequence, for a single channel surface EMG recording, it might be difficult to judge whether a voltage transient is a real action potential or an artifact. Further investigation of the signal distributions among other channels of the array can be used to reach a more confident judgment. CONCLUSIONS: During examination of spontaneous muscle activity using electrode arrays, caution is required for differentiation of physiological signals from artifactual spikes, which is important for accurate extraction of diagnostic or investigatory information.

Duration of observation required in detecting fasciculation potentials in amyotrophic lateral sclerosis using high-density surface EMG.

BACKGROUND: High-density surface electromyography (HD-SEMG) has recently emerged as a potentially useful tool in the evaluation of amyotrophic lateral sclerosis (ALS). This study addresses a practical constraint that arises when applying HD-SEMG for supporting the diagnosis of ALS; specifically, how long the surface EMG should be recorded before one can be confident that fasciculation potentials (FPs) are absent in a muscle being tested. METHODS: HD-SEMG recordings of 29 muscles from 11 ALS patients were analyzed. We used the distribution of intervals between FPs, and estimated the observation duration needed to record from one to five FPs with a probability approaching unity. Such an approach was previously tested by Mills with a concentric needle electrode. RESULTS: We found that the duration of recording was up to 70 s in order to record a single FP with a probability approaching unity. Increasing recording time to 2 minutes, the probability of recording five FPs approached approximately 0.95. CONCLUSIONS: HD-SEMG appears to be a suitable method for capturing FPs comparable to intramuscular needle EMG.

Motor unit innervation zone localization based on robust linear regression analysis.

With the aim of developing a flexible and reliable procedure for superficial muscle innervation zone (IZ) localization, we proposed a method to estimate IZ location using surface electromyogram (EMG) based on robust linear regression. Regression lines were used to model the bidirectional propagation pattern of a single motor unit action potential (MUAP) and visualize the trajectory of the MUAP propagation. IZ localization was performed by identifying the origin of the bidirectional MUAP propagation. Robust linear regression and MUAP peak detection, combined with propagation phase reversal identification, may provide an efficient way to estimate IZ location. Our method offers high resolution in locating IZs based on simulation studies and experimental tests. Furthermore, our method is flexible and may also be applied using a relatively small number of EMG channels. A comparative study of the proposed method with the cross-correlation method for IZ localization was conducted. The results obtained with simulated MUAPs and measured spontaneous MUAPs in the biceps brachii muscle in six subjects (four males and two females, 57 ±â€¯10 years old) with amyotrophic lateral sclerosis (ALS). Our method achieved estimation performance comparable to that obtained by using the cross-correlation method but with higher resolution. This study provides an accurate and practical method to estimate IZ location.

Innervation zones of fasciculating motor units: observations by a linear electrode array.

This study examines the innervation zone (IZ) in the biceps brachii muscle in healthy subjects and those with amyotrophic lateral sclerosis (ALS) using a 20-channel linear electromyogram (EMG) electrode array. Raster plots of individual waveform potentials were studied to estimate the motor unit IZ. While this work mainly focused on fasciculation potentials (FPs), a limited number of motor unit potentials (MUPs) from voluntary activity of 12 healthy and seven ALS subjects were also examined. Abnormal propagation of MUPs and scattered IZs were observed in fasciculating units, compared with voluntarily activated MUPs in healthy and ALS subjects. These findings can be related to muscle fiber reinnervation following motor neuron degeneration in ALS and the different origin sites of FPs compared with voluntary MUPs.

Spike sorting paradigm for classification of multi-channel recorded fasciculation potentials.

BACKGROUND: Fasciculation potentials (FPs) are important in supporting the electrodiagnosis of Amyotrophic Lateral Sclerosis (ALS). If classified by shape, FPs can also be very informative for laboratory-based neurophysiological investigations of the motor units. METHODS: This study describes a Matlab program for classification of FPs recorded by multi-channel surface electromyogram (EMG) electrodes. The program applies Principal Component Analysis on a set of features recorded from all channels. Then, it registers unsupervised and supervised classification algorithms to sort the FP samples. Qualitative and quantitative evaluation of the results is provided for the operator to assess the outcome. The algorithm facilitates manual interactive modification of the results. Classification accuracy can be improved progressively until the user is satisfied. The program makes no assumptions regarding the occurrence times of the action potentials, in keeping with the rather sporadic and irregular nature of FP firings. RESULTS: Ten sets of experimental data recorded from subjects with ALS using a 20-channel surface electrode array were tested. A total of 11891 FPs were detected and classified into a total of 235 prototype template waveforms. Evaluation and correction of classification outcome of such a dataset with over 6000 FPs can be achieved within 1-2 days. Facilitated interactive evaluation and modification could expedite the process of gaining accurate final results. CONCLUSION: The developed Matlab program is an efficient toolbox for classification of FPs.

A clinically applicable approach for detecting spontaneous action potential spikes in amyotrophic lateral sclerosis with a linear electrode array.

Examination of spontaneous muscle activity is an important part of the routine electromyogram (EMG) in assessing neuromuscular diseases. The EMG is specifically valuable as a diagnostic test in supporting the diagnosis of amyotrophic lateral sclerosis. High-density surface EMG is a relatively new technique that has until now been used in research but has the potential for clinical application. This study presents a simple high-density surface EMG method for automatic detection of spontaneous action potentials from surface electrode array recordings of patients with amyotrophic lateral sclerosis. To reduce computational complexity while maintaining useful information from the electrode array recording, the multichannel high-density surface EMG was transferred to single-dimensional data by calculating the maximum difference across all channels of the electrode array. A spike detection threshold was then set in the single-dimensional domain to identify the firing times of each spontaneous action potential spike, whereas a spike extraction threshold was used to define the onset and offset of the spontaneous spikes. These data were used to extract the spontaneous spike waveforms from the electrode array EMG. A database of detected spontaneous spikes was thus obtained, including their waveforms, on all channels along with their corresponding firing times. This newly developed method makes use of the information from different channels of the electrode array EMG recording. It also has the primary feature of being simple and fast in implementation, with convenient parameter adjustment and user-computer interaction. Hence, it has good possibilities for clinical application.

EMG-force relation in the first dorsal interosseous muscle of patients with amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: The relationship between surface electromyography (EMG) and muscle force is essential to assess muscle function and its deficits. However, few studies have explored the EMG-force relation in patients with amyotrophic lateral sclerosis (ALS). The purpose of this study was to examine the EMG-force relation in ALS subjects and its alteration in comparison with healthy control subjects. METHODS: Surface EMG and force signals were recorded while 10 ALS and 10 age-matched healthy control subjects produced isometric voluntary contractions in the first dorsal interosseous (FDI) muscle over the full range of activation. A linear fit of the EMG-force relation was evaluated through the normalized root mean square error (RMSE) between the experimental and predicted EMG amplitudes. The EMG-force relation was compared between the ALS and the healthy control subjects. RESULTS: With a linear fit, the normalized RMSE between the experimental and predicted EMG amplitudes was 9.6 ± 3.6% for the healthy control subjects and 12.3 ± 8.0% for the ALS subjects. The slope of the linear fit was 2.9 ± 2.2 µVN-1 for the ALS subjects and was significantly shallower (p < 0.05) than the control subjects (5.1 ± 1.8 µVN-1). However, after excluding the four ALS subjects who had very weak maximum force, the slope for the remaining ALS subjects was 3.5 ± 2.2 µVN-1 and was not significantly different from the control subjects (p > 0.05). CONCLUSIONS: A linear fit can be used to well describe the EMG-force relation for the FDI muscle of both ALS and healthy control subjects. A variety of processes may work together in ALS that can adversely affect the EMG-force relation.

An Examination of the Motor Unit Number Index (MUNIX) in muscles paralyzed by spinal cord injury.

The objective of this study was to assess whether there is evidence of motor unit loss in muscles paralyzed by spinal cord injury (SCI), using a measurement called motor unit number index (MUNIX). The MUNIX technique was applied in SCI (n=12) and neurologically intact (n=12) subjects. The maximum M waves and voluntary surface electromyography (EMG) signals at different muscle contraction levels were recorded from the first dorsal interosseous (FDI) muscle in each subject. The MUNIX values were estimated using a mathematical model describing the relation between the surface EMG signal and the ideal motor unit number count derived from the M wave and surface EMG measurements. We recorded a significant decrease in both maximum M wave amplitude and in estimated MUNIX values in paralyzed FDI muscles, as compared with neurologically intact muscles. Across all subjects, the maximum M wave amplitude was 8.3 ± 4.4 mV for the paralyzed muscles and 14.4 ± 2.0 mV for the neurologically intact muscles (p<0.0001). These measurements, when combined with voluntary EMG recordings, resulted in a mean MUNIX value of 112 ± 71 for the paralyzed muscles, much lower than the mean MUNIX value of 228 ± 49 for the neurologically intact muscles (p<0.00001). A motor unit size index was also calculated, using the maximum M wave recording and the MUNIX values. We found that paralyzed muscles showed a mean motor unit size index value of 80.7 ± 17.7 ìV, significantly higher than the mean value of 64.9 ± 10.1 ìV obtained from neurologically intact muscles (p<0.001). The MUNIX method used in this study offers several practical benefits compared with the traditional motor unit number estimation technique because it is noninvasive, induces minimal discomfort due to electrical nerve stimulation, and can be performed quickly. The findings from this study help understand the complicated determinants of SCI induced muscle weakness and provide further evidence of motoneuron degeneration after a spinal injury.