Imported from GitHub: Open-Muscle/OpenMuscle-Band · commit c5ace4b · license CERN-OHL-S-2.0
Description
Original OpenMuscle armband with 12 sensors (legacy design)
README
OpenMuscle-Band
Status: Archived (Legacy Hardware)
License: CERN-OHL-S v2.0
Overview
The OpenMuscle-Band is the original prototype of the OpenMuscle project—a wearable forearm band equipped with 12 pressure sensors designed to detect muscle contractions and predict finger movements. This open-source hardware was developed to provide biometric data for machine learning applications in prosthetics and human-computer interaction.
Hardware Specifications
- Sensors: 12 Hall Effect Sensors (49E) arranged in 6 dual-input sensor cells
- Microcontrollers: 3 × ESP32-C3 modules
- Connectivity: Wi-Fi (UDP transmission)
- Sampling Rate: Up to 1200 samples per second
- Construction: 3D-printed enclosures with integrated springs and magnets
- Firmware: MicroPython
Repository Contents
BOM/: Bill of Materials detailing all components usedKiCad/: PCB design files for the sensor arraySTLs/: 3D-printable files for enclosures and mountsSchematics/: Electrical schematics of the system
Legacy Information
This repository serves as an archive for the original OpenMuscle-Band design. Active development has moved to the OpenMuscle GitHub Organization, where you'll find:
- OpenMuscle-FlexGrid: A modular 60-sensor wearable, successor to the OM12
- OpenMuscle-LASK5: Labeling device with joystick and buttons
- OpenMuscle-Software: MicroPython firmware, communication protocols, and ML hooks
For historical data and machine learning scripts, refer to the legacy repository.
Accolades & Media Coverage
Electromaker:
🏆 2nd Place — Electromaker of the Month, April 2024
Electromaker Winners – March 2024
Hackaday Articles Featuring OpenMuscle:
- Forearm Muscle Contraction Sensor Is Useful Component For Open Source Prosthetics
- Hackaday Prize 2023: Finger Tracking Via Muscle Sensors
- Hackaday Prize 2023: LASK4 Watches Those Finger Wiggles
Getting Started
To replicate or study the OpenMuscle-Band:
-
Hardware Assembly:
- Print the enclosures from the
STLs/directory. - Assemble the sensor cells with Hall Effect Sensors, magnets, and springs.
- Connect the sensors to the ESP32-C3 modules as per the schematics.
- Print the enclosures from the
-
Firmware Installation:
- Flash MicroPython onto each ESP32-C3 module.
- Upload the appropriate
boot.pyandmain.pyscripts to handle data acquisition and transmission.
-
Data Collection:
- Use the band to collect muscle contraction data.
- Transmit data via UDP to a host machine for processing.
-
Machine Learning (Optional):
- Utilize the scripts from the legacy repository to train models that predict finger movements based on sensor data.
Contributing
As this is an archived repository, we are not accepting contributions. For ongoing development and contributions, please visit the OpenMuscle GitHub Organization.
License
This project is licensed under the CERN Open Hardware License v2.0. See the LICENSE file for details.
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