Martin / Tutorial: Continuous motion recognition Public

Tutorial: Continuous motion recognition

This is the finished Edge Impulse project for the tutorial 'Continuous motion recognition'. From here you can acquire new training data, design impulses and train models.

Accelerometer

About this project

Classify Your Gestures

Snake motion gif

Have you ever wondered how you can use acceleration to predict the type of input motion? Clone this project to build an embedded ML project to detect various hand gestures from your device's accelerometer!

You can also follow our tutorial to guide you through building your continuous motion recognition model, from data collection to deployment on embedded devices.

Sensor & Block Information

  • Accelerometer data (.cbor files) @ 62.5 Hz
  • Spectral Features DSP block for time-based sensor data
  • Neural Network Classifier with prediction outputs: "idle", "snake", "updown", "wave"
  • Anomaly Detection block for anomaly score output of unknown motions (gestures/motions the model was not trained on)
snake.33ihntit
wave.33ih3slk
idle.33ig394n
updown.33iibqa0
updown.33ih8akn
snake.33iherai
snake.33ij2npd
updown.33ii5005

Run this model

On any device

Dataset summary

Data collected
11m 0s
Sensors
accX, accY, accZ @ 62.5Hz
Labels
idle, snake, updown, wave

Project info

Project ID 84984
Project version 2
License No license attached
No. of views 5,355
No. of clones 9