

4. Modify the variable Threshold in the sample code to the recorded maximum value, and

reload the sample code to Arduino control board.



5. Open the serial plotter of arduino IDE and the myoelectricity waveform could be seen.

In general, the waveform is a line of 0 when the muscle is relaxed, shown as below. It is

normal along with occasional peak waveform.

Obviously myoelectricity waveform could been seen in the process of making a fist, shown

as below.

Basic Application

This application explains the way to distinguish whether the EMG signal is made by

fisting counts. It can be applied to push-up counts, dumbbell curl counts. It also can be

applied to human-computer interaction, such as play Flappy Bird with EMG signal made

by fist.

Please refer to the Chapter 4: 4.1 Preparation and 4.2 Connection Diagram for

hardware connection and sensor position.

This sample code needs EMGFilters library file, please download and install the

EMGFilters Library first. https://codeload.github.com/yuyouliang/EMG_Filter/zip/master

How to install Libraries in Arduino IDE https://www.arduino.cc/en/Guide/Libraries#.UxU8mdzF9H0%7C