Algorithm for jitter measurement in neuromuscular junction disease

This is the authors' abstract. We don't add key points for this paper.

The objective of this work was to extend the evaluation of a recently proposed method for estimating neuromuscular jitter within motor unit potential (MUP) trains extracted from muscles suffering neuromuscular junction disease. The method detects, within the MUP duration, "single-fiber" intervals that have likely been produced by single muscle fibers. Jitter is then estimated between pairs of these "single-fiber" intervals using an algorithm which incorporates the traditional mean consecutive difference (MCD) parameter. Electromyographic (EMG) recordings from facial muscles of 15 patients with symptoms related to myasthenia gravis were obtained. MUP trains were extracted using DQEMG software and manual jitter measures were obtained using an ad-hoc graphical interface, which emulates single fiber EMG protocols. Automatic measures for two different values of an internal threshold parameter were obtained and compared to manual measures. 5 %, 25 %, 75 % and 95 % percentiles for the differences between the automatic and manual jitter measurements were [-3.74, -1.47, 1.24, 3.47 μs] and [-6.45, -2.07, 1.65, 7.16 μs], for the two threshold values, respectively. Therefore, very small statistical and clinical differences were found between the automatic and manual jitter measures, supporting the method as an accurate tool for jitter assessment or as a guiding aid for manual procedures.