TRON Contest 2025 Entry
This project is a wearable motion analyzer built on μT-Kernel 3.0.
It measures wrist motion with an accelerometer, records reference (MASTER) and comparison (MINIC) motions,
and provides real-time feedback via LED display and sound effects.
- Runs on μT-Kernel 3.0 with small footprint, low power, and real-time performance
- Simple operation:
- A button = record MASTER motion
- B button = record MINIC motion & compare
- Immediate feedback with LED indicators (○ / ✗) and sound
- Designed for rehabilitation support, sports education, and motion analysis
- Future expansion: multi-node configuration, AI-assisted analysis (TinyML), Web/Cloud integration
- Based on mtkernel_3 (official reference implementation)
- TRONWARE sample codes were referenced for task, handler, and synchronization control
- Added original modules:
- Motion recording & comparison
- LED animation and sound effects
- Data analysis (200-sample segmentation, Z-axis feature extraction)
- micro:bit board
- Bangle module kit (SKU 8459)
- CR2032 battery (or alternative power source, e.g. AAA×2, LiPo)
This project is part of a multi-component system:
src/
├── WearableMotionAnalyzer-uTKernel/ # Main application (this project)
│ └── build_make/ # Build directory
│ └── makefile # References lsm303agr-utkernel
├── lsm303agr-utkernel/ # Sensor calibration library
│ ├── lib/ # Built library (liblsm303agr_calib.a)
│ └── include/ # Library headers
└── wearable-motion-visualizer/ # Visualization tool (Node.js)
└── server.js # WebSocket server for real-time display
-
WearableMotionAnalyzer-uTKernel depends on lsm303agr-utkernel
- The library is automatically built when building the main project
- Library path:
../../lsm303agr-utkernel/ - See lsm303agr-utkernel README for library details
-
wearable-motion-visualizer is an independent tool for visualizing sensor data
- Connects to MCU via serial port (UART)
- See wearable-motion-visualizer README for usage
- Base code: licensed under the same terms as mtkernel_3
- Modifications & extensions: © 2025 Ryuji Mori
This project is a reference implementation primarily intended for research and educational purposes.
- Research and educational use: You are free to use, modify, and distribute under the Apache-2.0 License
- Commercial use: Commercial use is permitted, but we kindly request credit and a link
- Example: "Based on Wearable Motion Analyzer by Ryuji Mori (https://github.com/mnrj-vv-w/WearableMotionAnalyzer-uTKernel)"
This project is an entry for TRON Contest 2025.