Continuous motion recognition
Task: Motion and Vibration Classification
License: BSD 3-Clause Clear
Dataset Screenshot
Description
This is a prebuilt dataset, collected by Edge Impulse teams, for a gesture recognition system based on continuous motion, for the Continous Motion Recognition tutorial. It contains 15 minutes of data sampled from a MEMS accelerometer at 62.5Hz over the following four classes:- Idle - board sits idly on your desk. There might be some movement detected, e.g. from typing while the board is present.
- Snake - board moves over the desk as a snake.
- Updown - board moves up and down in a continuous motion.
- Wave - board moves left and right like you’re waving to someone.
Snake
Updown
Wave
Compatible Blocks
- Feature extraction: Spectral Features (FFTs or Wavelets)
- Learning block: Classification + optionally Anomaly Detection (K-Means) or Anomaly Detection (GMM)
Dataset Details
- Total Data Items: 101
- Labeling Method: single label
- Train/Test Split: 84.16% / 15.84%
| Training Set | Testing Set | |
|---|---|---|
| Total Data Items | 85 | 16 |
| Labels | idle, snake, updown, wave | anomaly, idle, snake, updown, wave |
Usage
- Clone the public project To clone and use this project, visit the Edge Impulse Studio link, click on the Clone button on the top-right corner and follow the cloning instructions.
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Download
- Direct link
- HuggingFace - Soon
- Kaggle - Soon
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Import this dataset to your Edge Impulse project
This project uses the Edge Impulse Exporter Format (
info.labels). See this documentation page for more info. Edge Impulse also supports different data sample formats and dataset annotation formats that you can import into your project to build your edge AI models: