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Pre-processing of Electromyography Startle Data: a Novel Semi-Automatic Method

Human facial surface EMG of the startle reflex is a very dynamic and sensitive measurement. Traditionally, each trial is visually inspected to check whether the measurement is reliable [2]. This method is a very subjective way of checking data and very time consuming. Moreover, when examining a large volume of data, errors are easily made. Visual inspection by two researchers would make it more reliable, however, this is even more timeconsuming and the classification would still be subject to subjectivity. Therefore we propose a more objective semi-automatic way of checking the reliability of the trials using the variation of the raw EMG. After rejecting unreliable measurements there is still variation in the baseline across participants, sessions and even within a session due to differences in muscle tension and noise. Therefore, a baseline correction might be important for a good peak amplitude estimation. However, there is no consensus about baseline measurement in EMG experiments [2]. Therefore, we additionally propose an automatic method for determining a baseline.