This DIY Wearable Assist Goes Beyond Traditional Therapy

Bodo Hoenen and his family had an incredible scare. His daughter, Lorelei, suddenly became ill and quickly went from a happy and healthy girl to one fighting just to breathe and unable to move her own body. The culprit was elevated brain and spinal pressure due to a condition called AFM. This is a rare polio-like condition which is very serious, often fatal. Fortunately, Lorelei is doing much better. But this health crisis resulted in nearly complete paralysis of her left upper arm.

Taking an active role in the health of your child is instinctual with parents. Bodo’s family worked with health professionals to develop therapies to help rehabilitate Lorelei’s arm. But researching the problem showed that success in this area is very rare. So like any good hacker he set out to see if they could go beyond the traditional to build something to increase Lorelei’s odds.

What resulted is a wearable prosthesis which assists elbow movement by detecting the weak signals from her bicep and tricep to control an actuator which moves her arm. Help came in from all over the world during the prototyping process and the project, which was the topic of Bodo Hoenen’s talk at the Hackaday SuperConference, is still ongoing. Check that out below and the join us after the break for more details.

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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: Let Your Muscles Do The Work

Electromyography is a technique used to study and record the electrical signals generated when a muscle contracts. It’s used for medical diagnosis, rehab, kinesiological studies, and is the preferred method of control for robotic prosthetics and exoskeletons. There are a few companies out there with myoelectric products, and the use case for those products is flipping the slides on a PowerPoint presentation. Lucky for us, this project in the Hackaday Prize isn’t encumbered by such trivialities. It’s an open, expandable platform to turn muscle contractions into anything.

As you would expect, reading the electrical signals from muscles requires a little more technical expertise than plugging a cable into an Arduino. This project has opamps in spades, and is more than sensitive enough to serve as a useful sensor platform. Already this project is being used to monitor bruxism – inadvertent clenching or grinding of the jaw – and the results are great.

While it’s doubtful this device will ever be used in a medical context, it is a great little board to add muscle control to a robot arm, or build a very cool suit of power armor. All in all, a very cool entry for The Hackaday Prize.

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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Control Stuff With Your Muscles

[David Nghiem] has been working with circuitry designed to read signals from muscles for many years. After some bad luck with a start-up company, he didn’t give up and kept researching his idea. He has decided to share his innovations with the hacker community in the form of a wearable suit that reads muscle signals.

It turns out that when you flex a muscle, it gives off a signal called a Surface ElectroMyographic signal, or SEMG for short. [David] is using an Arduino, digital potentiometer and a bunch of op amps to read the SEMG signals. LEDs are used to display the signal levels.

The history behind [David’s] project dates back to the late twentieth century, which he eloquently points out – “Holy crap that was a long time ago”. He worked with the MIT Aero Astro Lab and the Boston University Neuromuscular Research Center where he worked on a robotic arm for astronauts. The idea being to apply an opposing force to the arm to help prevent muscle deterioration.

Be sure to check out [David’s] extensive and well documented work, along with the several videos showing his projects at various stages of completion. If this gives you the electromyography bug, check out this guide on detecting the signals and an application of the concept for robotic prosthesis.

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Detecting muscles with electromyography

The folks at Advancer Technologies just release a muscle sensor board with a great walk through posted on Instructables describing how this board measures the flexing of muscles using electromyography.

Using the same electrode placement points as the remote controlled hand we covered earlier, the muscle is measured by sensing the voltage between the muscle and its tendon. The result is a fairly fine-grained sensing of the output – more than enough to provide some analog control for a project.

The board itself is relatively simple – an INA106 differential amp is used to sense if a muscle is flexing or not. This signal is then amplified and rectified, after which it can be connected to the analog input of your favorite microcontroller. The video demo shows the board connected to a Processing app running from an Arduino, but it wouldn’t be hard to adapt this towards remote Nerf sentry turret controlled by your biceps.

Check out the video after the break to see the muscle sensor board in action.

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