Welcome to Edge Impulse, the largest community of edge AI developers!
This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.
This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.
Tutorial: Continuous motion recognition - RASynBoard
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
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 from RASynBoard 200Hz 6 axis IMU
- Syntiant IMU Processing Block
- Neural Network Classifier with prediction outputs: "idle (z_openset)", "snake", "updown", "wave"
Run this model
On any device
Dataset summary
Data collected
12m 43sSensors
accX, accY, accZ, gyrX, gyrY, gyrZ @ 200HzLabels
snake, updown, wave, z_opensetProject info
| Project ID | 306343 |
| License | Apache 2.0 |
| No. of views | 13,504 |
| No. of clones | 3 |
