Generation of Repeater F Waves in Healthy Subjects

Application of new waveform analysis methods reflecting F-wave diversity -classification of F-wave diversity according to differences in the derived muscles

Background

The F wave waveforms show diversity according to the number and size of re-firing cells, but there is still no analytical method that reflects this feature. We previously reported that five classifications of F waves are obtained from the ulnar nerve. However, the diversity of F waves derived from the lower extremities may not be similar. We therefore compared the diversity of F waves in the upper and lower extremities in healthy subjects.

New method

F waves were measured during tibial nerve stimulation in 26 healthy subjects. The amount of amplitude decrease was calculated from the amplitude value after the additive averaging process and based on the average amplitude value of each stimulus, and the relationship between the peak latency and density was examined.

Results

The amount of amplitude decrease due to the additive averaging process was negatively correlated with the density of negative peaks. The diversity of F waves could be categorized into four class based on the histograms.

Comparison with existing method

The new method uses a novel additive average method that reflects the diversity of F waves. Furthermore, it uses a histogram to visualize the cancellation between waveforms.

Conclusion

We developed an analysis method that reflects the diversity of F waves in a novel manner, which visualizes cancellation between waveforms using a histogram.

Fully automated F-wave corridor extraction and analysis algorithm for F-wave analyses and MUNE studies

F-waves are used in motor unit number estimation (MUNE) studies, which require rapid dedicated software to perform calculations. The aim of this study is to define a mathematical method for a fully automated F-wave extraction algorithm to perform F-wave and MUNE studies while performing baseline corrections without distorting traces. Ten recordings from each class, such as healthy controls, polio patients and ALS patients, were included. Submaximal stimuli were applied to the median and ulnar nerves to record 300 traces from the abductor pollicis brevis and abductor digiti minimi muscles. The autocorrelation function and the signal of sum of all traces were used to find the location for the maximum amplitude of the F-waves. F-waves were revealed by using a cutting window. Linear line estimation was preferred for baseline corrections because it did not cause any distortion in the traces. The algorithm automatically revealed F-waves from all 30 recordings in accordance with the locations marked by a neurophysiologist. The execution of the algorithm was less than 2 (usually < 1) minutes when 300 traces were analyzed. Mean sMUP amplitudes and MUNE values are important for differentiating healthy controls from patients. Moreover, F-wave parameters belonging to polio patients on whom there was a relatively low number of studies conducted were also evaluated.

Identical late motor responses in early Guillain-Barré syndrome: A-waves and repeater F-waves

Electrodiagnostic (EDx) studies play a key role in the investigation of suspected Guillain-Barré syndrome (GBS), providing diagnostic and prognostic information. However, initial EDx findings may not fulfill the neurophysiological criteria for the disease. The aim of this study was to estimate the occurrence and characteristics of A-waves and repeaters F-waves (Freps), both late motor responses identical in latency and configuration, in early stages of GBS. We retrospectively analyzed the initial nerve conduction study (NCS) of 26 GBS patients performed within 10 days from symptom onset. The final subtype diagnosis was acute inflammatory demyelinating polyneuropathy (AIDP) in 16 patients (six met the criteria at the initial EDx study and 10 at follow-up) and acute motor axonal neuropathy (AMAN) in 10 patients (six initially). Identical late responses were commonly found in the majority of nerves (84%). A-waves were present in 59% and an increased frequency of Freps was calculated in 61% of the 105 studied nerves. A-waves morphology (single or complex) could not distinguish between AIDP and AMAN. Nerves with normal NCS had a significantly higher frequency of A-waves, either isolated or in combination with increased index total Freps, as compared to nerves with low compound muscle action potential (CMAP) amplitudes or conduction block. Our findings suggest that both late responses can be useful as early markers of conduction changes of various pathophysiology, being frequently present even prior to abnormalities of CMAP parameters.

Automatic detection of F-waves and F-MUNE in Two Types of Motor Neuron Diseases

INTRODUCTION/AIMS

Motor unit number estimation by F-waves (F-MUNE) is an uncommonly used MUNE technique. The aim of this study was to analyze the sensitivity of F-MUNE values elicited with newly developed software in motor neuron diseases.

METHODS

F-waves were recorded by 300 submaximal stimuli from abductor digiti minimi (ADM) and abductor pollicis brevis (APB) muscles of 35 patients with amyotrophic lateral sclerosis, 18 with previous poliomyelitis, and 20 controls. The software extracted the surface motor unit action potentials (sMUAP) and calculated the F-MUNE values. CMAP Scans were also recorded to obtain step% and MScanFit.

RESULTS

sMUAP amplitudes were higher and F-MUNE values were lower in both muscles of the patients than in controls. F-MUNE values were able to distinguish the patients from controls. Significant correlations were found between F-MUNE and MScanFit in patient groups.

DISCUSSION

The new F-MUNE software gave promising results in revealing motor unit loss caused by motor neuron diseases.

A new waveform analysis method reflecting the diversity of F-wave Waveforms-Waveform types in healthy subjects based on the combined use of the additive averaging method and histograms

BACKGROUND

F-waves, which are an indicator of the excitability of spinal cord anterior horn cells, are characterized by diverse waveforms. However, no analytical method has yet been development that fully reflects the diversity of such waveforms. The present study examined whether or not the change in the amplitude by the additive averaging process reflects the dispersion of the peak.

NEW METHOD

The average amplitude of each waveform and the decrease in the amplitude after the additive averaging process were determined. The correlation between the decrease in the amplitude and the density of the peak was then examined. The histogram was also used to classify the type of waveform dispersion based on the characteristics of the peak latency.

RESULTS

No correlation was found between the change in the amplitude and the peak density. However, the F-waves obtained from the ulnar nerve of healthy subjects were able to be classified into five types.

COMPARISON WITH EXISTING METHOD

The parameters of an F-wave analysis are the rise latency, the amplitude and the persistence, and many reports have examined F-waves based on the changes in these values. The present study explored new parameters focusing on the waveform of F-waves reflecting the motor unit.

CONCLUSION

The results of this study may help to establish a standard of comparison when using the F wave to evaluate spasticity due to upper motor neuron disorders.

F Wave Analyzer, a system for repeater F-waves detection: Application in patients with amyotrophic lateral sclerosis

OBJECTIVES

We assessed the clinical usefulness of repeater F-waves (Freps) analysis in amyotrophic lateral sclerosis (ALS), using an automated computerized system (F Wave Analyzer).

METHODS

Forty consecutive F-waves were recorded from the ulnar and peroneal nerve in 52 patients with ALS and 52 healthy control subjects. Data were imported into the F Wave Analyzer which identifies Freps and groups them. Parameters of Freps and non repeater F-waves (Fnonreps) were compared.

RESULTS

Total number of repeating neurons, Freps persistence (100xFreps/40stimuli) and Index Total Freps (100xFreps/total number of F-waves) were significantly higher in the ALS compared to the control group (P ≤ 0.005). There were no consistent differences of F-wave latency or amplitude measurements between Freps and Fnonreps for both studied groups, with the exception of prolonged Freps minimum latency in ALS.

CONCLUSION

In ALS, the high numbers of Freps, reduced overall F-wave persistence and increased F-wave amplitude measurements in a relatively unaffected nerve-muscle complex reflects excitability alterations of the corresponding motor neuron pool. Overall, automatic analysis facilitates accurate and fast detection of Freps and could be useful in other clinical settings.

SIGNIFICANCE

Analysis of repeater F-waves is expected to provide new insight regarding ALS pathophysiology and utilized for monitoring in clinical drug trials.

F wave, A wave, H reflex, and blink reflex

Late responses include F waves, A waves, H reflex, and the blink reflex. These responses help enhance routine nerve conduction studies. Despite the use of F waves in multiple clinical applications, their studies can technically challenge even the most experienced electromyographers. They vary in latency, amplitude, and configuration, whereas A waves show no change in latency or morphology. Electrical stimulation of the supraorbital branch of the trigeminal nerve on one side results in a reflexive activation of the facial nucleus causing contraction of the orbicularis oculi muscle, short latency R1 ipsilaterally, and long latency R2 bilaterally. F waves can help determine the presence of a polyneuropathy. A waves can reflect axonal damage. H reflexes provide nerve conduction measurements along the entire length of the nerve, demonstrating abnormalities in neuropathies and radiculopathies. Abnormalities in the blink reflex can suggest the presence of an acoustic neuroma or a demyelinating polyneuropathy, which can affect the cranial nerves. This reflex, which also needs appropriate technical expertise, helps to assess cranial nerves V and VII along with their connections in the pons and medulla. The blink reflex, the electrical version of the corneal reflex, represents a polysynaptic reflex.