Hackaday Prize Entry: Heart Failure Detection Device

Early and low-cost detection of a Heart Failure is the proposal of [Jean Pierre Le Rouzic] for his entry for the 2017 Hackaday Prize. His device is based on a low-cost Doppler device, like those fetal Doppler devices used to listen an unborn baby heart, feeding a machine learning algorithm that could differentiate between a healthy and an unhealthy heart.

The theory behind it is that a regular, healthy heart tissue has a different acoustic impedance than degenerated tissue. Based on the acoustic impedance, the device would classify the tissue as: normal, degenerated, granulated or fibrous. Each category indicates specific problems mostly in connective tissues.

There are several advantages to have a working device like the one [Rouzic] is working on. To start, it would be possible to use it at home, without the intervention of a doctor or medical staff. It seems to us that would be as easy as using a blood pressure device or a fetal Doppler. It’s also relatively cheap (estimated under 150$) and it needs no gel to work. We covered similar projects that measure different heart signals, like Open Source electrocardiography, but ECG has the downfall that it requires attaching electrodes to the body.

One interesting proposed feature is that what is learn from a single case, is sent to every devices at their next update, so the devices get ‘smarter’ as they are used. Of course, there are a lot of ways for this to go wrong, but it’s a good idea to begin with.

Measuring Walking Speed Wirelessly

There are a lot of ways to try to mathematically quantify how healthy a person is. Things like resting pulse rate, blood pressure, and blood oxygenation are all quite simple to measure and can be used to predict various clinical outcomes. However, one you may not have considered is gait velocity, or the speed at which a person walks. It turns out gait velocity is a viable way to predict the onset of a wide variety of conditions, such as congestive heart failure or chronic obtrusive pulmonary disease. It turns out, as people become sick, elderly or infirm, they tend to walk slower – just like the little riflemen in your favourite RTS when their healthbar’s way in the red. But how does one measure this? MIT’s CSAIL has stepped up, with a way to measure walking speed completely wirelessly.

You can read the paper here (PDF). The WiGate device sends out a low-power radio signal, and then measures the reflections to determine a person’s location over time. Alone, however, this is not enough – it’s important to measure the walking speed specifically, to avoid false positives being triggered by a person simply not moving while watching television, for example. Algorithms are used to separate walking activity from the data set, allowing the device to sit in the background, recording walking speed data with no user interaction required whatsoever.

This form of passive monitoring could have great applications in nursing homes, where staff often have a huge number of patients to monitor. It would allow the collection of clinically relevant data without the need for any human intervention; the device could simply alert staff when a patient’s walking pattern is indicative of a bigger problem.

We see some great health research here at Hackaday – like this open source ECG. Video after the break.

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Transcranial Electrical Stimulation With Arduino, Hot Glue

The advance of electronic technology has been closely followed by the medical community over the past 200 years. Cutting edge electronics are used in medical imaging solutions to provide ever greater bandwidth and resolution in applications such as MRI machines, and research to interface with the human nervous system continues at a breakneck pace. The cost of this technology – particuarly in research and development – is incredibly high. Combine this with the high price of the regulatory approvals necessary for devices which deal in terms of life and death, and you’ll find that even basic medical technology is prohibitively expensive. Just ask any diabetic. On the face of things, there’s a moral dilemma. Humanity has developed technologies that can improve quality of life. Yet, due to our own rules and regulations, we cannot afford to readily distribute them.

One example of this is that despite the positive results from many transcranial electrical stimulation (TCS) studies, the devices used are prohibitively expensive, as are treatment regimens for patients. Realising this, [quicksilv3rflash] decided to develop a homebrew, open source transcranial electrical stimualtion device, and published it on Instructables. Yes, that’s the world we’re now living in.

It’s important to publish a warning here: Experimenting with this sort of equipment can easily kill you, fry your brain, or have any number of other awful results. If you don’t have a rock solid understanding of the principles behind seperate grounds, or your soldering is just a little sloppy, you don’t want to go anywhere near this. In particular, this device cannot be powered safely by a wall-wart.

To be honest, we find it difficult to trust any medical device manufactured out of modules sourced from eBay. But as a learning excercise, there is serious value here. Such a project requires mastery of analog design to avoid dangerous currents being passed to the body. The instructions also highlight the importance of rigorously testing the device before ever connecting it to a human body.

The equipment is based around an Arduino Nano receiving commands from a computer over serial, fed by an application written in Python & PyGame. To think, this writer thought he was being bold when he used it to control a remote control car! The Arduino Nano interprets this data and outputs it over SPI to a DAC which outputs a signal which is then amplified and fed to the human brain courtesy of op-amps, boost converters and sponge electrodes. The output of the device is limited to +/-2.1mA by design, in accordance with suggested limits for TCS use.

It should be noted, [quicksilv3rflash] has been experimenting with homebuilt TCS devices for several years now, and has lived to tell the tale. It’s impressive to see a full suite of homebrew, opensource tools being developed in this field. [quicksilv3rflash] reports to have not suffered injuries from the device, and several devices have been shipped to redditors. We’ve only found minimal reports on people receiving these, but nothing on anyone actually using the hardware as intended. If you’ve used one, get in touch in the comments.

It goes without saying – this sort of experimentation is dangerous and the stakes for getting it wrong are ludicrously high. We’ve seen before what happens when medical devices malfunction – things get real ugly, real fast. But hackers will be hackers and if you were wondering if it was possible to build a TCS device for under $100 in parts from eBay, well, yes. Yes it is.

Pulse Oximeter is a Lot of Work

These days we are a little spoiled. There are many sensors you can grab, hook up to your favorite microcontroller, load up some simple library code, and you are in business. When [Raivis] got a MAX30100 pulse oximeter breakout board, he thought it would go like that. It didn’t. He found it takes a lot of processing to get useful results out of the device. Lucky for us he wrote it all down with Arduino code to match.

A pulse oximeter measures both your pulse and the oxygen saturation in your blood. You’ve probably had one of these on your finger or earlobe at the doctor’s office or a hospital. Traditionally, they consist of a red LED and an IR LED. A detector measures how much of each light makes it through and the ratio of those two quantities relates to the amount of oxygen in your blood. We can’t imagine how [Karl Matthes] came up with using red and green light back in 1935, and how [Takuo Aoyagi] (who, along with [Michio Kishi]) figured out the IR and red light part.

The MAX30100 manages to alternate the two LEDs, regulate their brightness, filter line noise out of the readings, and some other tasks. It stores the data in a buffer. The trick is: how do you interpret that buffer? Continue reading “Pulse Oximeter is a Lot of Work”

Recording Functioning Muscles to Rehab Spinal Cord Injury Patients

[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.

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Riding Rollercoasters with 3D Printed Kidneys, Passing Stones

Citizen science isn’t limited to the nerd community. When medical professionals get a crazy idea, their options include filling out endless paperwork for human consent forms and grant applications, or hacking something together themselves. When [David Wartinger] noticed that far too many of his patients passed kidney stones while on vacation, riding rollercoasters, he had to test it out.

Without the benefit of his own kidney stones, he did the next best thing: 3D printed a model kidney, collected some urine, and tossed a few stones that he’d collected from patients into the trap. Then he and a colleague rode Big Thunder Mountain Railroad sixty times, holding the model in a backpack at kidney height.

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Hackaday Prize Entry: Helping Millions See Clearly

Slit lamps are prohibitively expensive in the third world areas of India where they are most needed. An invention that’s been around for over a hundred years, the slit lamp is a simple-in-concept way to see and diagnose a large array of ocular issues.

Since they are relatively old by technological standards, the principles behind them have become more and more understood as time has gone on. While a nice lab version with a corneal microscope is certainly better, innovations in manufacturing have brought the theoretical minimum cost of the device way down, or at least that’s what [Kewal Chand Swami] hopes.

His design aims for portability and cost reduction. It must be able to travel to remote locations and it must be significantly cheaper than the lab versions. It uses off-the-shelf lenses in a 3D printed housing with a simple LED torch, the kind you can buy for a dollar at the check-out stand.

The assembly slides onto the user’s head and is held there with straps. The doctor can adjust where the slit the lamp shines and also look through a microscope to diagnose the issue. Hopefully devices like this will see similar community support to the prosthetic projects we’ve covered.