We have seen how Python can be used to process and analyse EMG signals in lessons 1, 2 and 3. When EMG signals are filtered, how does changing filter settings change the appearance of the filtered EMG signal? A low pass filter allows frequencies below the cut-off frequency to pass through (ie. higher frequencies are removed). The filtered EMG signal

In the previous lesson we learned that our EMG signal had some problems: Baseline EMG values have an offset from zero. Baseline EMG values are noisy. Also, the EMG signal possess both negative and positive values. This means if we wanted to calculate an average or mean EMG, the negative and positive values will cancel out. We can apply 3

In the previous lesson, we simulated data of two EMG ‘bursts’ during a muscle contraction. The data are shown in Figure 1. Figure 1: Simulated EMG data from 2 muscle contractions       The code to generate Figure 1 and the explanations are as follows: 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Electromyography (EMG) is an experimental and clinical technique used to study and analyse electrical signals produced by muscles. This series of tutorials will go through how Python can be used to process and analyse EMG signals. We begin with a brief overview of how muscle electrical signals are produced and detected. What is EMG? The smallest functional unit that describes