[Diego Marino] and his colleagues at the Politecnico di Torino (Polytechnic University of Turin, Italy) designed a prototype that allows for patients with motor deficits, such as spinal cord injury (SCI), to do rehabilitation via Functional Electrical Stimulation. They devised a system that records and interprets muscle signals from the physiotherapist and then stimulates specific muscles, in the patient, via an electro-stimulator.
The acquisition system is based on a BITalino board that records the Surface Electromyography (sEMG) signal from the muscles of the physiotherapist, while they perform a specific exercise designed for the patient’s rehabilitation plan. The BITalino uses Bluetooth to send the data to a PC where the data is properly crunched in Matlab in order to recognize and to isolate the muscular activity patterns.
After that, the signals are ‘replayed’ on the patient using a relay-board connected to a Globus Genesy 600 electro-stimulator. This relay board hack is mostly because the Globus Genesy is not programmable so this was a fast way for them to implement the stimulator. In their video we can see the muscle activation being replayed immediately after the ‘physiotherapist’ performs the movement. It’s clearly a prototype but it does show promising results.
Continue reading “Recording Functioning Muscles to Rehab Spinal Cord Injury Patients”
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.
Continue reading “This DIY Wearable Assist Goes Beyond Traditional Therapy”
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.
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.
Continue reading “All About Biosignals”
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 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.
In 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.
Continue reading “Hackaday Prize Entry: Open-Source Myoelectric Hand Prosthesis”
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.
[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.