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Introduction/aims: Conventional F wave analysis involves a relatively uniform physiological environment induced by supramaximal stimulations. The F wave characteristics in a dynamic physiological condition, however, are rarely investigated. This study aimed to improve understanding of F wave properties in the more dynamic process by introducing a novel method to analyze F waves based on the compound muscle action potential (CMAP) scan technique., Methods: Twenty four healthy subjects participated in the study. The CMAP scan was applied to record muscle responses in the abductor pollicis brevis (APB) and abductor digiti minimi (ADM) muscles, respectively. F wave characteristics including mean F wave amplitude and latency (F-M latency), persistence and activating threshold were quantified., Results: An average of 200 F waves per muscle were obtained from the CMAP scan recording. Weak to moderate correlations between F wave amplitude and stimulating intensity were observed in most of the APB (19 muscles; r = 0.33 ± 0.14, all p < .05) and ADM (23 muscles, r = 0.46 ± 0.16, all p < .05) muscles. Significantly longer mean F latency and lower activating F-threshold were found in the ADM muscles (F-M latency: APB: 25.43 ± 2.39 ms, ADM: 26.15 ± 2.32 ms, p < .05; F-threshold: APB: 7.68 ± 8.96% CMAP, ADM: 2.35 ± 2.42% CMAP, p < .05)., Discussion: This study introduces new features of F waves using the CMAP scan technique and identifies differences of F wave characteristics between the hand muscles. The CMAP scan based F waves analysis can be combined with the motor unit number estimation to assess functional alterations in motor neurons in neurological disorders., (© 2024 The Author(s). Muscle & Nerve published by Wiley Periodicals LLC.)

No consensus criteria exist for recording and analyzing waveforms in clinical electromyography (EMG). There have been significant technical improvements in recent decades that are under-used in both routine practice and research. In current practice, disciplined techniques in acquisition and analysis of signals are required to appropriately define them. As an example, we describe such an exercise in acquisition and analysis. During a routine study, atypical spontaneous activity was encountered. High-quality digital recordings were stored for off-line analysis. These revealed waveforms that could be isolated and quantitatively defined using basic instrumentation available on most modern EMG systems: "slow" firing fibrillation potentials and a repeating fasciculation potential. Subjective analysis alone could not have identified them. To improve accuracy in identification and understanding of these waveforms, we propose criteria for data collection and signal analysis. This is critical for quality in routine practice, education, and proper reporting of electrophysiological signals., (© 2021 Wiley Periodicals LLC.)

Introduction: In contrast to needle electromyography (EMG), surface EMG recordings are painless. It is of interest to develop methods to analyze surface EMG for diagnostic purposes., Methods: Surface EMG interference pattern (SIP) recordings from the abductor pollicis brevis muscle of healthy subjects and subjects with amyotrophic lateral sclerosis (ALS) were analyzed by measuring root-mean-square (RMS) voltage, mean rectified voltage, form factor (FF), and the clustering index (CI). The FF vs SIP area plot was used for analysis., Results: The SIP FF was increased and abnormal in ALS subjects, especially when SIP area was less than 200 mVms. Power regression showed a faster FF decline with SIP area in ALS patients than in healthy subjects. The CI and FF showed a strong correlation., Discussion: FF is easy to calculate and demonstrates abnormalities in ALS patients., (© 2020 Wiley Periodicals, Inc.)

Introduction: This study proposes guidelines for motor unit number index (MUNIX) recording and analysis., Methods: MUNIX was measured in control participants and in patients with amyotrophic lateral sclerosis. Changes in MUNIX values due to E1 electrode position, number of surface electromyography interference pattern (SIP) epochs, SIP epoch duration, force of contraction, and outlier data points were investigated., Results: MUNIX depends on optimized compound muscle action potential (CMAP) amplitude. Individual muscles showed variations when the number of epochs was low or when the SIP duration was short. Longer SIP duration allowed better recognition of artifacts. MUNIX results were affected by SIP values at all force levels but was more affected when SIP area was low., Discussion: We recommend changing the E1 electrode position to maximize CMAP amplitude. Twenty or more SIP signals of 500-ms duration should be recorded by using force levels ranging from slight to maximum. Traces should be reviewed to identify and exclude signals with tremor or solitary spikes. Muscle Nerve 58: 374-380, 2018., (© 2018 Wiley Periodicals, Inc.)

Objective: Motor Unit Number Index (MUNIX) is a quantitative neurophysiological measure that provides an index of the number of lower motor neurons supplying a muscle. It reflects the loss of motor neurons in patients with Amyotrophic Lateral Sclerosis (ALS). However, it is unclear whether MUNIX also detects motor unit loss in strong, non-wasted muscles., Methods: Three centres measured MUNIX in 49 ALS patients every three months in six different muscles (abductor pollicis brevis, abductor digiti minimi, biceps brachii, tibialis anterior, extensor digitorum brevis, abductor hallucis) on the less affected side. The decline of MUNIX in initially non-wasted, clinically strong muscles (manual muscle testing, MMT grade 5) was analysed before and after onset of weakness., Results: In 49 subjects, 151 clinically strong muscles developed weakness and were included for analysis. The average monthly relative loss of MUNIX was 5.0% before and 5.6% after onset of weakness. This rate of change was significantly higher compared to ALS functional rating scale (ALSFRS-R) and compound muscle action potential (CMAP) change over 12months prior to the onset of muscle weakness (p=0.024)., Conclusion: MUNIX is an electrophysiological marker that detects lower motor neuron loss in ALS, before clinical weakness becomes apparent by manual muscle testing., Significance: This makes MUNIX a good biomarker candidate for disease progression and possibly pharmacodynamics responds., (Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

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., (Published by Elsevier Ltd.)

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.

Needle electromyogram (EMG) is routinely used in clinical neurophysiology for examination of neuromuscular diseases. This study presents a noninvasive surface EMG method for supporting diagnosis of amyotrophic lateral sclerosis (ALS). Three diagnostic markers including the clustering index, the kurtosis of EMG amplitude histogram, and the kurtosis of EMG crossing-rate expansion, were used respectively to characterize surface EMG patterns recorded during different levels of voluntary muscle contraction. We then applied a linear discriminant analysis classifier to discriminate the ALS subjects from the neurologically intact subjects, using the statistics derived from all the three markers as input feature sets to the classifier. The method was tested in 10 ALS subjects and 11 neurologically intact subjects. Combination of the three surface EMG markers achieved 90% diagnostic sensitivity and 100% diagnostic specificity, which were higher than solely using a single surface EMG marker. Given the high diagnostic yield, the proposed surface EMG analysis can be used as a supplement to needle EMG examination in supporting the diagnosis of ALS.

This study explores a novel application of multiscale entropy (MSE) analysis for characterizing different patterns of spontaneous electromyogram (EMG) signals including sporadic, tonic and repetitive spontaneous motor unit discharges, and normal surface EMG baseline. Two algorithms for MSE analysis, namely, the standard MSE and the intrinsic mode entropy (IMEn) (based on the recently developed multivariate empirical mode decomposition method), were applied to different patterns of spontaneous EMG. Significant differences were observed in multiple scales of the standard MSE and IMEn analyses (<;i>p<;/i> <; 0.001) for any two of the spontaneous EMG patterns, while such significance may not be observed from the single-scale entropy analysis. Compared to the standard MSE, the IMEn analysis facilitates usage of a relatively low scale number to discern entropy difference among various patterns of spontaneous EMG signals. The findings from this study contribute to our understanding of the nonlinear dynamic properties of different spontaneous EMG patterns, which may be related to spinal motoneuron or motor unit health.

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.

Introduction: In this study we investigated the reproducibility of motor unit number index (MUNIX) in patients with amyotrophic lateral sclerosis (ALS)., Methods: MUNIX was recorded in patients with ALS. Studies were performed in 18 thenar and 18 hypothenar muscles by two operators. The reproducibility was assessed using mean MUNIX values, linear regression, correlation coefficient, and coefficient of variation (COV) in individual studies., Results: The mean values showed no significant difference. The linear regression showed a strong correlation. Most patients had low COV. A high COV was seen when MUNIX was very low. The COV was higher in thenar than in hypothenar muscles., Conclusions: MUNIX has very good reproducibility in ALS patients. COV may exaggerate interoperator variation when MUNIX is very low. The higher variability in the thenar muscle is also due to variability in compound muscle action potential amplitude. Although both muscles show good reproducibility, the hypothenar is better suited for serial studies in individual patients., (Copyright © 2011 Wiley Periodicals, Inc.)

Objective: To investigate the intra-rater and inter-rater test-retest reliability of the Motor Unit Number Index (MUNIX) in healthy subjects in a multicentre setting., Methods: Six study centres applied the MUNIX technique in 66 healthy subjects. Five to six muscles (biceps brachii, BB; abductor digiti minimi, ADM; abductor pollicis brevis, APB; tibialis anterior, TA; extensor digitorum brevis, EDB and abductor hallucis, AH) were measured in each volunteer four times by two independent examiners., Results: The method was easy to perform and well tolerated. The intraclass correlation coefficient (ICC) varied between centres and muscles. Intra-rater reliability was greatest for the AH (ICC 0.83) and EDB (ICC 0.81). Inter-rater reliability was greatest for the AH (ICC 0.69) and ADM muscles (ICC 0.69). The most critical muscle was the APB muscle (ICC 0.52, total variability). This was mostly due to variability in the compound muscle action potential (CMAP) measurements. MUNIX values of the APB, ADM and TA fell into the same range as in other motor unit number estimation (MUNE) studies., Conclusion: MUNIX measurements in multiple muscles show good inter- and intra-rater reliability in healthy subjects. CMAP amplitude must be controlled to optimize reliability., Significance: Results suggest that MUNIX could serve as a reliable marker for motor neuron loss in diseases like amyotrophic lateral sclerosis., (Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

The surface-recorded compound muscle action potential (CMAP) and electromyographic (EMG) interference pattern is used to compute the motor unit number index (MUNIX). The MUNIX demonstrated all known changes in the number of motor units in normal subjects, and in patients with amyotrophic lateral sclerosis (ALS). In normal subjects MUNIX decreased slightly with age and showed excellent reproducibility. In many ALS patients MUNIX was reduced even when the CMAP was normal. Lower MUNIX values were seen in weaker muscles. This is a noninvasive method that requires minimal electrical stimulation. It is performed in less than 5 min. This makes it suitable for serial EMG investigations.

Introduction: Reference values (RVs) are required to separate normal from abnormal values obtained in electrodiagnostic (EDx) testing. However, it is frequently impractical to perform studies on control subjects to obtain RVs. The Extrapolated Reference Values (E-Ref) procedure extracts RVs from data obtained during clinically indicated EDx testing. We compared the E-Ref results with established RVs in several sets of EDx data.Methods: The mathematical basis for E-Ref was explored to develop an algorithm for the E-Ref procedure. To test the validity of this algorithm, it was applied to simulated and real jitter measurements from control subjects and patients with myasthenia gravis, and to nerve conduction studies from patients with various conditions referred for EDx studies.Results: There was good concordance between E-Ref and RVs for all evaluated data sets.Discussion: E-Ref is a promising method to develop RVs. Muscle Nerve 57: 90-95, 2018. [ABSTRACT FROM AUTHOR]

Background: Motor Unit Number Index (MUNIX) is a novel neurophysiological measure that provides an index of the number of functional lower motor neurons in a given muscle. So far its performance across centres in patients with amyotrophic lateral sclerosis (ALS) has not been investigated.Objective: To perform longitudinal MUNIX recordings in a set of muscles in a multicentre setting in order to evaluate its value as a marker of disease progression.Methods: Three centres applied MUNIX in 51 ALS patients over 15 months. Six different muscles (abductor pollicis brevis, abductor digiti minimi, biceps brachii, tibialis anterior, extensor dig. brevis, abductor hallucis) were measured every 3 months on the less affected side. The decline between MUNIX and ALSFRS-R was compared.Results: 31 participants reached month 12. For all participants, ALSFRS-R declined at a rate of 2.3%/month. Using the total score of all muscles, MUNIX declined significantly faster by 3.2%/month (p ≤ 0.02). MUNIX in individual muscles declined between 2.4% and 4.2%, which differed from ASLFRS-R decline starting from month 3 (p ≤ 0.05 to 0.002). Subgroups with bulbar, lower and upper limb onset showed different decline rates of ALSFRS-R between 1.9% and 2.8%/month, while MUNIX total scores showed similar decline rates over all subgroups. Mean intraclass correlation coefficient for MUNIX intra-rater reliability was 0.89 and for inter-rater reliability 0.80.Conclusion: MUNIX is a reliable electrophysiological biomarker to track lower motor neuron loss in ALS. [ABSTRACT FROM AUTHOR]

We investigated the voluntary contraction direction dependence of motor unit number index (MUNIX) for multifunctional muscles in patients with amyotrophic lateral sclerosis (ALS). The MUNIX technique was applied in nine first dorsal interosseous muscles of eight ALS subjects, using surface electromyography (EMG) signals from index finger abduction and flexion, respectively. In seven examined muscles, the MUNIX derived from the index finger abduction mode was smaller than that from the flexion mode. For the remaining two muscles, one had the same MUNIX; the other showed an abduction mode MUNIX much higher than the flexion mode MNUIX. Across all muscles, the median MUNIX was 96 for the index finger abduction mode and 161 for the flexion mode. The findings reveal the dependence of multifunctional muscle MUNIX on voluntary contraction directions in ALS patients. Based on this analysis, we further explored the concept of “multidimensional MUNIX” for an appropriate performance or interpretation of MUNIX in multifunctional muscles of ALS patients. An effort towards such a development was presented using both abduction and flexion mode surface EMG for MUNIX calculation. [ABSTRACT FROM AUTHOR]

Needle electromyogram (EMG) is routinely used in clinical neurophysiology for examination of neuromuscular diseases. This study presents a noninvasive surface EMG method for supporting diagnosis of amyotrophic lateral sclerosis (ALS). Three diagnostic markers including the clustering index, the kurtosis of EMG amplitude histogram, and the kurtosis of EMG crossing-rate expansion, were used respectively to characterize surface EMG patterns recorded during different levels of voluntary muscle contraction. We then applied a linear discriminant analysis classifier to discriminate the ALS subjects from the neurologically intact subjects, using the statistics derived from all the three markers as input feature sets to the classifier. The method was tested in 10 ALS subjects and 11 neurologically intact subjects. Combination of the three surface EMG markers achieved 90% diagnostic sensitivity and 100% diagnostic specificity, which were higher than solely using a single surface EMG marker. Given the high diagnostic yield, the proposed surface EMG analysis can be used as a supplement to needle EMG examination in supporting the diagnosis of ALS. [ABSTRACT FROM AUTHOR]