Edge Impulse Inc. / Tutorial: Continuous motion recognition Public

Edge Impulse Inc. / 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.


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)

Download block output

Title Type Size
Spectral features training data NPY file 2554 windows
Spectral features training labels NPY file 2554 windows
Spectral features testing data NPY file 502 windows
Spectral features testing labels NPY file 502 windows
Classifier model TensorFlow Lite (float32) 6 KB
Classifier model TensorFlow Lite (int8 quantized) 3 KB
Classifier model Model evaluation metrics (JSON file) 7 KB
Classifier model TensorFlow SavedModel 12 KB
Classifier model Keras h5 model 6 KB
Anomaly detection model JSON 11 KB

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Data collected
15m 16s

Project info

Project ID 14299
Project version 14
License Apache 2.0