Developing a continuous gesture recognition application with Edge Impulse and Arm Mbed OS

Now that we have tested the model, we are ready to build the sketch in the Arduino IDE to recognize our three motion gestures. In this recipe, we will build a continuous gesture recognition application with the help of Edge Impulse, Arm Mbed OS, and an algorithm to filter out redundant or spurious classification results.

Getting ready

Our goal is to develop a continuous gesture recognition application, which means that the accelerometer data sampling and ML inference must be performed concurrently. This approach guarantees that we capture and process all the pieces of the input data stream so we don’t miss any events.

The main ingredients to accomplish this task are as follows:

• Arm Mbed OS for writing a multithreading program
• An algorithm to filter out redundant classification results

Let’s start by learning how to perform...