CPAP (Continuous Positive Airway Pressure) machines can be life-changing for people with sleep apnea. [Scott Clandinin] benefits from his CPAP machine and devised a way to improve his quality of life even further with a non-destructive modification to monitor his machine’s humidifier.

With a CPAP machine, all air the wearer breathes is air that has gone through the machine. [Scott]’s CPAP machine has a small water reservoir which is heated to humidify the air before it goes to the wearer. However, depending on conditions the water reservoir may run dry during use, leading to the user waking up dried out and uncomfortable.

To solve this in a non-invasive way that required no modifications to the machine itself, [Scott] created a two-part device. The first part is a platform upon which the CPAP machine rests. A load cell interfaced to an HX711 Load Cell Amplifier allows an Arduino Nano to measure the mass of the CPAP machine plus the integrated water reservoir. By taking regular measurements, the Arduino can detect when the reservoir is about to run dry and sound an alarm. Getting one’s sleep interrupted by an alarm isn’t a pleasant way to wake up, but it’s much more pleasant than waking up dried out and uncomfortable from breathing hot, dry air for a while.

The second part of the device is a simple button interfaced to a hanger for the mask itself. While the mask is hung up, the system is idle. When the mask is removed from the hook, the system takes measurements and goes to work. This makes activation hassle-free, not to mention also avoids spurious alarms while the user removes and fills the water reservoir.

Non-invasive modifications to medical or other health-related devices is common, and a perfect example of nondestructive interfacing is the Eyedriveomatic which won the 2015 Hackaday Prize. Also, the HX711 Load Cell Amplifier has an Arduino library that was used in this bathroom scale refurb project.

CPAP (Continuous Positive Airway Pressure) machines can be life-changing for people with sleep apnea. [Scott Clandinin] benefits from his CPAP machine and devised a way to improve his quality of life even further with a non-destructive modification to monitor his machine’s humidifier.

With a CPAP machine, all air the wearer breathes is air that has gone through the machine. [Scott]’s CPAP machine has a small water reservoir which is heated to humidify the air before it goes to the wearer. However, depending on conditions the water reservoir may run dry during use, leading to the user waking up dried out and uncomfortable.

To solve this in a non-invasive way that required no modifications to the machine itself, [Scott] created a two-part device. The first part is a platform upon which the CPAP machine rests. A load cell interfaced to an HX711 Load Cell Amplifier allows an Arduino Nano to measure the mass of the CPAP machine plus the integrated water reservoir. By taking regular measurements, the Arduino can detect when the reservoir is about to run dry and sound an alarm. Getting one’s sleep interrupted by an alarm isn’t a pleasant way to wake up, but it’s much more pleasant than waking up dried out and uncomfortable from breathing hot, dry air for a while.

The second part of the device is a simple button interfaced to a hanger for the mask itself. While the mask is hung up, the system is idle. When the mask is removed from the hook, the system takes measurements and goes to work. This makes activation hassle-free, not to mention also avoids spurious alarms while the user removes and fills the water reservoir.

Non-invasive modifications to medical or other health-related devices is common, and a perfect example of nondestructive interfacing is the Eyedriveomatic which won the 2015 Hackaday Prize. Also, the HX711 Load Cell Amplifier has an Arduino library that was used in this bathroom scale refurb project.

If you’re at all into medical hacks, you’ve doubtless noticed that the medical industry provides us with all manner of shiny toys to play with. Case in point is a heart-monitoring IC that’s so brand new, it’s not even available in all of the usual distributors yet. [Ashwin], who runs a small prototyping-supplies company, ProtoCentral, has been playing around with the new MAX30003 ECG chip, and the results look great.

The punchline is that the four-to-five dollar chip does everything for you, including analog filtering, wander removal, and even detecting the pulse rate. Using the chip is simple: you plug in two electrodes on one end, and you get the waveform data out over SPI on the other, with little or no work to do on the microprocessor side. The Arduino in the examples is just passing the SPI data straight to the laptop, with no processing going on at all.

[Ashwin] is selling these as breakout boards, but everything is open source, from the hardware to the GUI, so check it out if you’re interested in building your own. In particular, the circuit is just a voltage regulator and five volt level shifter.

Everything we know about electrocardiography projects, we learned from this presentation, and it looks like the devil is in the (many) details, so it’s nice to offload them to custom silicon whenever possible. We just think it’s awesome that we can scoop up some of the giant medical industry’s crumbs to play around with.

We so often hack for hacking’s sake, undertaking projects as a solitary pursuit simply for the challenge. So it’s nice to see hacking skills going to good use and helping someone out. Such was the case with this low-cost two-axis handheld camera gimbal intended to help a budding photographer with a motion disorder.

When [Tadej Strah] joined his school photography club, a fellow member who happens to have cerebral palsy needed help steadying cameras for clean shots. So rather than shell out a lot of money for a commercial gimbal, [Tadej] decided to build one for his friend. A few scraps of aluminum bar stock were bent into the gimbal frames and camera mount. Two hobby servos take care of the pitch and roll axes, controlled by an Arduino talking to an MPU-6050. Mounted to a handle from an angle grinder with the battery and electronics mounted below, the gimbal looks well-balanced and does a good job of keeping the camera level.

Hats off to [Tadej] for pitching in and solving a real world problem with his skills. We like to see people helping others directly, whether it’s building a gyroscopic spoon for Parkinson’s sufferers or vision enhancement for a nearly blind adventurer.

[via r/arduino]

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?

[Raivis] shows the code to take the output from the buffer, remove the DC component, pass it through a couple of software filters, and detect the heart rate. To read the oxygen reading, you have even more work to do. You can find the code for the device on GitHub.

If you want to build your own without a dedicated IC, grab a clothespin. Or try this more polished build.

Most parents would do anything to enrich their kids’ worlds and teach them what they need to know. Hacker parents often take it one step further by modifying the kid’s world to allow them to work past a disability. To wit we have an interactive game board to help a toddler learn her shapes and colors.

The toddler in question is [Becca], and her needs are special because of the progressive nature of the blindness that will result from her Usher Syndrome. [Becca] will need visual acuity testing much earlier than most toddlers, but a standard eye chart is meaningless to kids before they get their letters. This is where Lea shapes come in – a set of four shapes that are used to make visual testing a game and help practitioners assess what a child can and cannot see.

[Jake] and his wife [Beth] were advised to familiarize [Becca] with the shapes, but all she wanted to do was eat the printed sheet. In order to make the task more entertaining, [Jake] built an interactive board where brightly colored Lea shapes trigger the room lights to change to the same color as the block when it’s inserted into the correct spot on the board, as a visual reward. Reed switches, magnets, and an Arduino comprise the game logic, and the board communicates to the Philips Hue smart bulbs over an NRF24L01. The video below also shows some cool under-bed lights and a very engaged [Becca] learning her shapes and colors.

As we expected when we last covered his efforts to help [Rebecca], [Jake] has leveraged the Raspberry Pi he used as a hub for the stairwell lighting project. We’re looking forward to seeing what else he comes up with, and to see how [Becca] is thriving.

You’d think that with as many sick people as there are in the world, it wouldn’t be too difficult for a doctor in training to get practice. It’s easy to get experience treating common complaints like colds and the flu, but it might take the young doctor a while to run across a dissecting abdominal aortic aneurysm, and that won’t be the time for on the job training.

Enter the SP, or standardized patient – people trained to deliver information to medical students to simulate a particular case. There’s a problem with SPs, though. While it’s easy enough to coach someone to deliver an oral history reflecting a medical condition, the student eventually needs to examine the SP, which will reveal none of the signs and symptoms associated with the simulated case. To remedy this, [Chris Sanders] and [J Scott Christianson] from the University of Missouri developed an open-source RFID stethoscope to simulate patient findings.

This is one of those “why didn’t I think of that?” ideas. A cheap stethoscope is fitted with an Arduino, and RFID reader, and a small audio board. RFID tags are placed at diagnostic points over an SP’s chest and abdomen. When the stethoscope is placed over a tag, a specific sound file is fetched from an SD card and played over earbuds. The student doesn’t have to ask, “What am I hearing?” anymore – the actual sound of bruits or borborygmi are heard.

We can easily see expanding this system – RFID tags that trigger a faux ultrasound machine to display diagnostic images, or tiny OLED screens displaying tagged images into an otoscope. A good place to start expanding this idea might be this digital stethoscope recorder and analyzer.

[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.

It reminds us of the Myoelectric Hand, with humans instead. We featured an EMG tutorial a while back for those curious about this topic. Without taking the merit out of excellent and needed medical research, we all wait for the day that all our bio-signals can be easy read and translated to, let’s say, a huge avatar robot like METHOD-2. Right? Right?…

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.

Hard as it is to imagine, lie detectors have been sold as children’s toys for a number of years. A simple battery-operated device clipped to your fingers and would show the conductivity of your skin. The concept — which is probably not very reliable — observers that lying causes you to imperceptibly sweat which causes a sudden increase in your skin’s conductivity. These cheap toys would have a meter and you’d note the meter deflection to determine if the subject was lying.

You can debate the amusement value of interrogating your friends, perhaps, but they were pretty common and still exist (including some that shock you if they detect you are lying). Seventeen-year-old [BuildIt] has his own modern take on this classic device using — what else? — an Arduino. You can see a video of the device below.

Of interest is how he used the latest version of the Arduino IDE to visualize the data graphically (see right). This is easier than interpreting a bunch of numbers scrolling by on the serial terminal or having to import the data into a spreadsheet. You can find the graph under the Tools menu listed as Serial Plotter.

You don’t need a lot of external parts for this project, although the finger clips and the cardboard box will take a little mechanical skill to complete.

We’ve looked at galvanic skin response and other biosignal processing before. You can do a lot more if you build a little more hardware.