Sometimes the journey is as interesting as the destination, and that’s certainly the case with [Marc]’s pursuit of measuring his sleep apnea (PDF, talk slides. Video embedded below.). Sleep apnea involves periods of time when you don’t breathe or breathe shallowly for as long as a few minutes and affects 5-10% of middle-aged men (half that for women.) [Marc]’s efforts are still a work-in-progress but along the way he’s tried a multitude of things, all involving different technology and bugs to work out. It’s surprising how many ways there are to monitor breathing.

His attempts started out using a MobSenDat Kit, which includes an Arduino compatible board, and an accelerometer to see just what his sleeping positions were. That was followed by measuring blood O2 saturation using a cheap SPO2 sensor that didn’t work out, and one with Bluetooth that did work but gave results as a graph and not raw data.

Next came measuring breathing by detecting airflow from his nose using a Wind Sensor, but the tubes for getting the “wind” from his nose to the sensor were problematic, though the approach was workable. In parallel with the Wind Sensor he also tried the Zeo bedside sleep manager which involves wearing a headband that uses electrical signals from your brain to tell you what sleep state you’re in. He particularly liked this one as it gave access to the data and even offered some code.

And his last approach we know of was to monitor breathing by putting some form of band around his chest/belly to measure expansion and contraction. He tried a few bands and an Eeonyx conductive textile/yarn turned out to be the best. He did run into noise issues with the Xbee, as well as voltage regulator problems, and a diode that had to be bypassed.

But while [Marc]’s list of approaches to monitor sleep is long, he hasn’t exhausted all approaches. For example there’s monitoring a baby using lasers to detect whether or not the child is still breathing.

[Via Adafruit]

Lots of us get to take home a little e-waste from work once in a while to feed our hacking habits. But some guys have all the luck and score the really good stuff, which is how these robotic surgical tools came to be gesture controlled.

The lucky and resourceful hacker in this case is one [Julien Schuermans], who managed to take home pieces of a multi-million dollar da Vinci Si surgical robot. Before anyone cries “larcency”, [Julien] appears to have come by the hardware legitimately – the wrist units of these robots are consumable parts costing about $2500 each, and are disposed of after 10 procedures. The video below makes it clear how they interface with the robot arm, and how [Julien] brought them to life in his shop. A quartet of Arduino-controlled servos engages drive pins on the wrist and rotates pulleys that move the cables that drive the instruments. A neat trick by itself, but when coupled with the Leap Motion controller, the instruments become gesture controlled. We’re very sure we’d prefer the surgeon’s hands on a physical controller, but the virtual control is surprisingly responsive and looks like a lot of fun.

When we talk about da Vinci around here, it’s usually in reference to 3D printers or a Renaissance-style cryptex build. Unsurprisingly, we haven’t featured many surgical robot hacks – maybe it’s time we started.

[via r/arduino]

We’ve all likely watched an episode of “Star Trek” and admired the level of integration on the sick bay diagnostic bed. With its suite of wireless sensors and flat panel display, even the 1960s imagining of the future blows away the decidedly wired experience of a modern day ICU stay. But we may be getting closer to [Dr. McCoy]’s experience with this radar-based respiration detector.

[Øyvind]’s build, which takes the origin of the term “breadboard” to heart, is based on a not-inexpensive Xethru module, which appears to be purpose-built for detecting respiration. The extra-thick PC board seems to house the waveguides internally, which is a neat trick but might limit how the module can be deployed. The module requires both a USB interface and level shifter to interface the 2.8V levels of the module to the 5V Arduino Uno. In the video below, [Øyvind]’s prototype simply lights an RGB LED in response to the chest movement it detects, but there’s plenty of potential for development here. We’ve seen a laser-based baby breathing monitor before; perhaps this systems could be used to the same end without the risk of blinding your tyke. Or perhaps better diagnostics for sleep apnea patients than an intrusive night in a sleep study lab.

Clocking in at $750USD for the sensor board and USB interface, this build is not exactly for the faint of heart or the light of wallet. But as an off-the-shelf solution to a specific need that also has a fair bit of hacking potential, it may be just the thing for someone. Of course if radar is your thing, you might rather go big and build something that can see through walls.

[Myrijam Stoetzer] and her friend [Paul Foltin], 14 and 15 years old kids from Duisburg, Germany are working on a eye movement controller wheel chair. They were inspired by the Eyewriter Project which we’ve been following for a long time. Eyewriter was built for Tony Quan a.k.a Tempt1 by his friends. In 2003, Tempt1 was diagnosed with the degenerative nerve disorder ALS  and is now fully paralyzed except for his eyes, but has been able to use the EyeWriter to continue his art.

This is their first big leap moving up from Lego Mindstorms. The eye tracker part consists of a safety glass frame, a regular webcam, and IR SMD LEDs. They removed the IR blocking filter from the webcam to make it work in all lighting conditions. The image processing is handled by an Odroid U3 – a compact, low cost ARM Quad Core SBC capable of running Ubuntu, Android, and other Linux OS systems. They initially tried the Raspberry Pi which managed to do just about 3fps, compared to 13~15fps from the Odroid. The code is written in Python and uses OpenCV libraries. They are learning Python on the go. An Arduino is used to control the motor via an H-bridge controller, and also to calibrate the eye tracker. Potentiometers connected to the Arduino’s analog ports allow adjusting the tracker to individual requirements.

The web cam video stream is filtered to obtain the pupil position, and this is compared to four presets for forward, reverse, left and right. The presets can be adjusted using the potentiometers. An enable switch, manually activated at present is used to ensure the wheel chair moves only when commanded. Their plan is to later replace this switch with tongue activation or maybe cheek muscle twitch detection.

First tests were on a small mockup robotic platform. After winning a local competition, they bought a second-hand wheel chair and started all over again. This time, they tried the Raspberry Pi 2 model B, and it was able to work at about 8~9fps. Not as well as the Odroid, but at half the cost, it seemed like a workable solution since their aim is to make it as cheap as possible. They would appreciate receiving any help to improve the performance – maybe improving their code or utilising all the four cores more efficiently. For the bigger wheelchair, they used recycled car windshield wiper motors and some relays to switch them. They also used a 3D printer to print an enclosure for the camera and wheels to help turn the wheelchair. Further details are also available on [Myrijam]’s blog. They documented their build (German, pdf) and have their sights set on the German National Science Fair. The team is working on English translation of the documentation and will release all design files and source code under a CC by NC license soon.

Have you ever wanted to turn on or off your TV just by thinking about it? We love this hack mainly because it uses an old Star Wars Force Trainer game. You can still buy them for about $40-$80 USD online. This cool little toy was introduced in 2009 and uses a headset with electrodes, and an electroencephalography (EEG) chip. It transmits the EEG data to control a fan that blows air into a tube to “levitate” a ball, all the while being coached on by the voice of Yoda. (Geesh! Kids these days have the best toys!)

[Tinkernut] started by cracking open the headset, where he found the EEG chip made by a company called NeuroSky (talk about a frightening sounding company name). The PCB designer was kind enough to label the Tx/Rx pins on the board, so hooking it up to an Arduino was a snap. After scavenging an IR LED and receiver from an old VCR, the hardware was just about done. After a bit of coding, you can now control your TV by using the force! (Ok, by ‘force’ I mean brainwaves.)  Video after the break.

Note: [Tinkernut’s] blog page should have more information available soon. In the meantime if you can find his Arduino Brain Library on github.

This isn’t the first EEG to TV interface we’ve featured. Way back in 2010 we featured a project that used an Emotiv EPOC EEG headset to turn on and off a TV. But at $400 for the headset, it was a little too expensive for the average Jedi.

A handheld tricorder is as good a reason as any to start a project. The science-fiction-derived form factor provides an opportunity to work on a lot of different areas of hardware development like portable power, charging, communications between sensor and microcontroller. And of course you need a user interface so that the values being returned will have some meaning for the user.

[Marcus B] has done a great job with all of this in his first version of a medical tricorder. The current design hosts two sensors, one measures skin temperature using infrared, the other is a pulse sensor.

For us it’s not the number of sensors that makes something a “tricorder” but the ability of the device to use those sensors to make a diagnosis (or to give the user enough hints to come to their own conclusion). [Marcus] shares similar views and with that in mind has designed in a real-time clock and an SD card slot. These can be used to log sensor data over time which may then be able to suggest ailments based on a known set of common diagnosis parameters.

Looking at the image above you may be wondering which chip is the microcontroller. This build is actually a shield for an Arduino hiding underneath.

There’s a demonstration video after the break. And if you find this impressive you won’t want to miss the Open Source Science Tricorder which is one of the finalists for the 2014 Hackaday Prize.

When you think of DIY hardware, genetic research tools are not something that typically comes to mind. But [Stacey] and [Matt]‘s OpenPCR project aims to enable anyone to do polymerase chain reaction (PCR) research on the cheap.

PCR is a process that multiplies a specific piece of DNA a few million times. It can be used for many purposes, including DNA cloning and DNA fingerprinting for forensics. PCR is also used for paternity testing.

The process involves baking the DNA at specific temperatures for the right amount of time. The DNA is first denatured, to split the helix into individual strands. Next, the temperature is lowered and primers are bound to the strands. Finally, another temperature is used to allow the polymerase to duplicate the DNA. This process is repeated to multiply the DNA.

The OpenPCR uses an Arduino to control a solid state relay. This relay provides power to two large resistors that act as heaters. A MAX31855 is used to read a thermocouple over SPI and provide feedback for the system. A computer fan is used to cool the device down.

A milled aluminium sample holder houses and heats the samples during cycling. The laser cut, t-slot construction case features some helix art, and houses all of the components. It will be interesting to see what applications this $85 PCR device can perform.

Via Adafruit