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ADL

uTensor enables motion recognition on microcontrollers. The model is trained with a modified Activity of Daily dataset recognizing 5 classes:

  • Walking
  • Climbing
  • Activities
  • Descending
  • Resting

The project is also a reference implementation of sequential data processing with Mbed and uTensor.

Board and grove shield and Accelerometer

For sensor setup, please refer to Train/HMP_Dataset/MANUAL.txt. The grove sensor is place flat on the back of user's right hand, with the connector socket oriented furthest away from the wrist.

Hardware requirement:

  • Mbed F413ZH board
  • Grove Sheild
  • Grove 3D digital accelerometer

Build Instruction

$ mbed import https://github.com/uTensor/ADL_demo
$ cd ADL_demo
$ mbed compile -m DISCO_F413ZH -t GCC_ARM --profile=uTensor/build_profile/release.json
  • Ensure the Grove sensor is connected
  • Locate the binary path from the terminal output, and flash it onto the board

Training

For Training Instruction, please see Train/README.md