EMG Tutorial Lets You Listen to Your Muscles

What with wearable tech, haptic feedback, implantable devices, and prosthetic limbs, the boundary between man and machine is getting harder and harder to discern. If you’re going to hack in this space, you’re going to need to know a little about electromyography, or the technique of sensing the electrical signals which make muscles fire. This handy tutorial on using an Arduino to capture EMG signals might be just the thing.

In an article written mainly as a tutorial to other physiatrists, [Dr. George Marzloff] covers some ground that will seem very basic to the seasoned hacker, but there are still valuable tidbits there. His tutorial build centers around a MyoWare Muscle Sensor and an Arduino Uno. The muscle sensor has snap connectors for three foam electrodes of the type used for electrocardiography, and outputs a rectified and integrated waveform that represents the envelope of the electrical signal traveling to a muscle. [Dr. Marzloff]’s simple sketch just reads the analog output of the sensor and lights an LED if it detects a muscle contraction, but the sky’s the limit once you have the basic EMG interface. Prosthetic limbs, wearable devices, diagnostic tools, virtual reality — the possibilities are endless.

We’ve seen a few EMG interfaces before, mainly of the homebrew type like this audio recorder recruited for EMG measurements. And be sure to check out [Bil Herd]’s in-depth discussion of digging EMG signals out of the noise.

All About Biosignals

DIY medical science is fun stuff. One can ferret out many of the electrical signals that make the body run with surprisingly accessible components and simple builds. While the medical community predictably dwells on the healthcare uses of such information, the hacker is free to do whatever he or she wants.

A good first start is to look at the relatively strong electrical signals coming off of the heart and other muscles. [Bernd Porr] has put together a simple bioamplifier circuit, and his students have made a series of videos explaining its use that’s well worth your time if you are interested in these things.
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Hackaday Prize Entry: Open-Source Myoelectric Hand Prosthesis

Hands can grab things, build things, communicate, and we control them intuitively with nothing more than a thought. To those who miss a hand, a prosthesis can be a life-changing tool for carrying out daily tasks. We are delighted to see that [Alvaro Villoslada] joined the Hackaday Prize with his contribution to advanced prosthesis technology: Dextra, the open-source myoelectric hand prosthesis.

dextra_handDextra is an advanced robotic hand, with 4 independently actuated fingers and a thumb with an additional degree of freedom. Because Dextra is designed as a self-contained unit, all actuators had to be embedded into the hand. [Alvaro] achieved the necessary level of miniaturization with five tiny winches, driven by micro gear motors. Each of them pulls a tendon that actuates the corresponding finger. Magnetic encoders on the motor shafts provide position feedback to a Teensy 3.1, which orchestrates all the fingers. The rotational axis of the thumb is actuated by a small RC servo.

mumai_boardIn addition to the robotic hand, [Alvaro] is developing his own electromyographic (EMG) interface, the Mumai, which allows a user to control a robotic prosthesis through tiny muscle contractions in the residual limb. Just like Dextra, Mumai is open-source. It consists of a pair of skin electrodes and an acquisition board. The electrodes are attached to the muscle, and the acquisition board translates the electrical activity of the muscle into an analog voltage. This raw EMG signal is then sampled and analyzed by a microcontroller, such as the ESP8266. The microcontroller then determines the intent of the user based on pattern recognition. Eventually this control data is used to control a robotic prosthesis, such as the Dextra. The current progress of both projects is impressive. You can check out a video of Dextra below.

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Hackaday Prize Entry: Biopotential Signal Library

With prosthetics, EEG, and all the other builds focused on the body and medicine for this year’s Hackaday Prize, it might be a good idea to take a look at what it takes to measure the tiny electrical signals that come from the human body. Measuring brain waves or heartbeats indoors is hard; AC power frequencies easily couple to the high impedance inputs for these measurements, and the signals themselves are very, very weak. For his entry to The Hackaday Prize, [Paul Stoffregen] is building the tools to make EEG, ECG, and EMG measurements easy with cheap tools.

If the name [Stoffregen] sounds familiar, it’s because he’s the guy behind the Teensy family of microcontroller boards and several dozen extremely popular libraries for everything from displays to real time clocks. The biopotential signal library continues in [Paul]’s tradition of building very cool stuff with just code.

The hardware used in this project is TI’s ADS1294, a 24-bit ADC with either 4 or 8 channels. This chip is marketed as a medical analog front end with a little bit of ECG thrown in for good measure. [Paul] is only using the ADS1294 initially; more analog chips can be added later. It’s a great project in its own right, and when you include the potential applications of this library – everything from prosthetics to body sensors – it makes for an awesome Hackaday Prize entry.


The 2015 Hackaday Prize is sponsored by:

An Open Hardware Platform for ECG, EEG and Other Measurements

[Eric] tipped us about the OpenHarwareExG project which goal is to build a device that allows the creation of electrophysiological signal processing applications. By the latter they mean electrocardiography (ECG, activity of the heart), electroencephalography (EEG, signals on the scalp), electromyography (EMG, skeletal muscles activity), electronystagmography and electrooculography (ENG & EOG, eye movements) monitoring projects. As you can guess these signals are particularly hard to measure due to their small amplitude and therefore susceptibility to electrical noise.

The ADS1299 8-channel 24-bit analog front end used in this platform is actually electrically isolated from the rest of the circuit so the USB connection wouldn’t perturb measurements. An Arduino-compatible ATSAM3X microcontroller is used and all the board is “DIY compatible” as all parts can be sourced in small quantities and soldered by hand. Even the case is open source, being laser cut from acrylic.

Head to the project’s website to download all the source files and see a quick video of the system in action.

Interested in measuring the body’s potential? Check out an ECG that’s nice enough to let you know you have died, or this Android based wireless setup.

 

DIY EMG uses an audio recorder

[Ericdsc] is looking to capture the electrical impulses of his muscles by using an EMG. He went through several prototypes to find the right recipe for sensors to pick up the electrical signal through his skin. Above you can see the version that worked best. Each sensor is made starting with a piece of duct tape and laying out a patch of stripped wire on it. A 5cmx1xm piece of aluminum foil then covers this, and second smaller piece of foil covers the cable’s shielding (not pictured here). This will stick to your skin to hold the sensor in place after applying a dab of sugar syrup to help make a good electrical connection.

In this case, an audio recorder is taking the measurements. [Ericdsc] had been having trouble sleeping and wanted to find out if he’s restless in bed. The audio recorder can log hours of data from the sensors which he can later analyze on the computer. Of course, it wouldn’t be hard to build your own amplifier circuit and process the signals in real-time. Maybe you want to convert that mind-controlled Pong game over to use abdominal control. You’ll have a six-pack in no time.

EMG controlled prosthesis

This prosthetic arm is the result of a student project. [Amnon Demri] and his classmates built it with below-the-elbow amputees in mind. It uses electromyography to actuate the fingers and wrist. Four stick-on sensors are placed around the elbow to sense electrical activity there. These signals are interpreted by a PIC 16f877a microcontroller which then controls the servo motors to operate the prosthetic limb. This sounds like a very economical solution and as you can see in the videos after the break, it works fairly well.

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