The following is a summary of “Fully automated F-wave corridor extraction and analysis algorithm for F-wave analyses and MUNE studies,” published in the August 2023 issue of Neurology by Artuğ et al.
Utilized in Motor Unit Number Estimation (MUNE) research, F-waves demand swift and specialized software for expedient computation purposes. Researchers conducted a retrospective study to establish a mathematical approach for an entirely automated F-wave extraction algorithm. This method aids F-wave and MUNE studies by incorporating baseline corrections to maintain trace integrity.
They included 10 recordings from each category of healthy controls, polio patients, and ALS patients. Submaximal stimuli to the median and ulnar nerves were applied, with 300 traces from the abductor pollicis brevis and digiti minimi muscles. The autocorrelation function and the summation of all paths were employed to pinpoint the F-wave’s peak amplitude, and a cutting window technique was used to reveal F-waves while maintaining trace fidelity through linear line approximation for baseline corrections.
The results showed the algorithm autonomously F-waves in all 30 recordings, aligning with neurophysiologist-marked locations. Algorithm execution took less than 2 (typically < 1) minutes for 300 trace analysis. Mean sMUP amplitudes and MUNE values remain vital in distinguishing healthy controls from patients. Additionally, F-wave parameters for polio patients, a group with limited study representation, were assessed.
They concluded a fully automated algorithm for rapid F-wave studies extracts repeater F-waves, calculates repeater neurons, F-waves, persistence, and MUNE value in 1 minute, and evaluates accuracy and performance.