Robotic Arm Controlled With Muscle Movement via EMG Signals (2024)

Robotic Arm Controlled With Muscle Movement via EMG Signals (1)

If you’ve dreamt of the ultimate mecha-powered future with giant robots and mecha suits controlled by the human body, you’re sure to get excited about this project from Ultimate Robots. The team has created a robotic arm that can be controlled using muscle movement thanks to their EMG signal sensor PCB, the uMyo. It also leverages one of our favorite microelectronics boards -- the Arduino.

This project was designed as a simple demonstration of what the uMyo sensor module can achieve. It’s fitted with three separate uMyo PCBs to detect movement from the wearer accurately. Each finger on the robotic arm has two tendons. These are connected to a wheel that is operated by a servo. The servo determines whether or not to curl or uncurl the fingers.

The shining gem of this creation is the uMyo sensor. It’s an open-source device designed to be worn for user input. It can transmit data wirelessly, so the wearer shouldn’t expect to be bogged down with cables tethering them to the output device. According to Ultimate Robotics, the uMyo can detect signals from various muscle groups, including arms, like in this project, legs, face muscles, and torso muscles.

Two uMyo sensors are placed at the elbow to monitor finger muscle signals. A third sensor is used at the wrist to monitor thumb muscle movement. The signals are transmitted to an Arduino, which uses an nRF24 module to receive the wireless signal. The Arduino then processes the input to send commands to the servos via a PCA9685 driver board, causing the robotic arm to move in response.

Not only is the uMyo sensor open source, but so is the software used in this robotic arm project. The team was kind enough to share everything on GitHub for anyone interested in perusing the source code.

To get a closer look at this project, check out the official uMyo breakdown uploaded by Ultimate Robotics at Hackaday. The team shared plenty of details about how it works and what goes into the PCB. You can find more information on the robotic arm on Reddit and see it in action via YouTube.

Stay On the Cutting Edge: Get the Tom's Hardware Newsletter

Get Tom's Hardware's best news and in-depth reviews, straight to your inbox.

Robotic Arm Controlled With Muscle Movement via EMG Signals (5)

Ash Hill

Freelance News and Features Writer

Ash Hill is a Freelance News and Features Writer with a wealth of experience in the hobby electronics, 3D printing and PCs. She manages the Pi projects of the month and much of our daily Raspberry Pi reporting while also finding the best coupons and deals on all tech.

Latest

Early Snapdragon X Elite benchmarks seemingly confirm the chip's incredible performance and battery life potentialCopilot+ PCs: all we know about the AI-ready laptops and exclusive Windows featuresSamsung names new CEO as company loses market share to SK hynix, hopes to retake ground as AI demand for memory increases
See more latest►

2 CommentsComment from the forums

  • punkncat

    I have been reading a bit about a similar/same tech in relation to amputees. The study had a couple of below elbow amps picking up co*ke cans and doing other simple tasks with the device. It would be super duper cool to see this technology (along with 3D printing) evolve prosthesis to a whole new level of functionality. I would absolutely love to have an articulating ankle again....

    Reply

  • edzieba

    If I had a penny every time someone stuck some myoelectric sensors on a forearm to use as an input device, I'd probably be able to buy a nice meal by now.

    Like with head-mounted EEG sensors, the major problem is the precision of electrode placement required to get repeatable results. In a lab or clinical environment where you can have trained technicians place electrodes (or employ bespoke fitted hard mounts) it can be viable, but self-donning not really. Whilst we're a few decades past the transition between "train humans to the interface" to "train the interface to user intent", it's still no good if you need to perform retraining every time the interface is donned. Think of the inconvenience as akin to your keyboard randomising key layout every time you sat down at your desk.

    Reply

Most Popular
Cooler Master introduces colored ‘AI Thermal Paste’ — CryoFuze 5 comes with nano-diamond technology
AMD unveils EPYC 4004 CPUs: AM5 gets server-grade processors
TSMC’s EUV machines are equipped with a remote self-destruct in case of an invasion
Noctua unveils its Home series products — $100 NV-FS1 desk fan is the star attraction
HP reshuffles PC naming scheme, adds AI Helix logo branding, kills some old favorites
Total Recall: the only Copilot+ AI feature that matters is a huge privacy risk
TSMC struggles to meet demand for CoWoS packaging, holding back AI and HPC chip production: report
Hands-on with Microsoft's new Surface and Surface Pro Copilot+ PCs
M4 iPad Pros with 8GB of RAM may actually have 12GB — teardowns reveal possible Apple hijinks
Asus unveils glossy 27-inch WOLED gaming monitor with a flicker-free G-Sync/FreeSync gaming experience
Intel next-generation Lunar Lake CPUs launching in Q3, Arrow Lake in Q4 — mobile chips claimed to be 1.4x faster than Qualcomm's X Elite processors
Robotic Arm Controlled With Muscle Movement via EMG Signals (2024)
Top Articles
Latest Posts
Article information

Author: Francesca Jacobs Ret

Last Updated:

Views: 6131

Rating: 4.8 / 5 (68 voted)

Reviews: 83% of readers found this page helpful

Author information

Name: Francesca Jacobs Ret

Birthday: 1996-12-09

Address: Apt. 141 1406 Mitch Summit, New Teganshire, UT 82655-0699

Phone: +2296092334654

Job: Technology Architect

Hobby: Snowboarding, Scouting, Foreign language learning, Dowsing, Baton twirling, Sculpting, Cabaret

Introduction: My name is Francesca Jacobs Ret, I am a innocent, super, beautiful, charming, lucky, gentle, clever person who loves writing and wants to share my knowledge and understanding with you.