Hackaday Prize Entry: Open-source Pulse Oximetry

Chances are pretty good you’ve had a glowing probe clipped to your fingertip or earlobe in some clinic or doctor’s office. If you have, then you’re familiar with pulse oximetry, a cheap and non-invasive test that’s intended to measure how much oxygen your blood is carrying, with the bonus of an accurate count of your pulse rate. You can run down to the local drug store or big box and get a fingertip pulse oximeter for about $25USD, but if you want to learn more about photoplethysmography (PPG), [Rajendra Bhatt]’s open-source pulse oximeter might be a better choice.

PPG is based on the fact that oxygenated and deoxygenated hemoglobin have different optical characteristics. A simple probe with an LED floods your fingertip with IR light, and a photodiode reads the amount of light reflected by the hemoglobin. [Rajendra]’s Easy Pulse Plugin receives and amplifies the signal from the probe and sends it to a header, suitable for Arduino consumption. What you do with the signal from there is up to you – light an LED in time with your heartbeat, plot oxygen saturation as a function of time, or drive a display to show the current pulse and saturation.

We’ve seen some pretty slick DIY pulse oximeters before, and some with a decidedly home-brew feel, but this seems like a good balance between sophisticated design and open source hackability. And don’t forget that IR LEDs can be used for other non-invasive diagnostics too.

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A Simple Circuit For Testing Infrared Remote Controls

Every now and then a remote control acts up. Maybe you are trying to change the channel on your television and it’s just not working. A quick way to determine if the remote control is still working is by using a cell phone camera to try to see if the IR LED is still lighting up. That can work sometimes but not always. [Rui] had this problem and he decided to build his own circuit to make it easier to tell if a remote control was having problems.

The circuit uses a Vishay V34836 infrared receiver to pick up the invisible signals that are sent from a remote control. A Microchip 12F683 processes the data and has two main output modes. If the remote control is receiving data continuously, then a green LED lights up to indicate that the remote is functioning properly. If some data is received but not in a continuous stream, then a yellow LED lights up instead. This indicates that the batteries on the remote need to be replaced.

The circuit also includes a red LED as a power indicator as well as RS232 output of the actual received data. The PCB was cut using a milling machine. It’s glued to the top of a dual AAA battery holder, which provides plenty of current to run the circuit.

Remote Controlled Wildlife Camera with Raspberry Pi

If you are interested in local wildlife, you may want to consider this wildlife camera project (Google cache). [Arnis] has been using his to film foxes and mice. The core components of this build are a Raspberry Pi and an infrared camera module specifically made for the Pi. The system runs on a 20,000 mAh battery, which [Arnis] claims results in around 18 hours of battery life.

[Arnis] appears to be using a passive infrared (PIR) sensor to detect motion. These sensors work by detecting sudden changes in the amount of ambient infrared radiation. Mammals are good sources of infrared radiation, so the sensor would work well to detect animals in the vicinity. The Pi is also hooked up to a secondary circuit consisting of a relay, a battery, and an infrared light. When it’s dark outside, [Arnis] can enable “night mode” which will turn on the infrared light. This provides some level of night vision for recording the furry critters in low light conditions.

[Arnis] is also using a Bluetooth dongle with the Pi in order to communicate with an Android phone. Using a custom Android app, he is able to connect back to the Pi and start the camera recording script. He can also use the app to sync the time on the Pi or download an updated image from the camera to ensure it is pointed in the right direction. Be sure to check out the demo video below.

If you like these wildlife cameras, you might want to check out some older projects that serve a similar purpose. Continue reading “Remote Controlled Wildlife Camera with Raspberry Pi”

Control Anything with an Apple Remote

If you’re like us, you probably have more than one Apple Remote kicking around in a parts drawer, and if you’re even more like us, you’re probably really annoyed at Apple’s tendency to use proprietary hardware and software at every turn (lightning connector, anyone?). But there’s hope for the Apple Remote now: [Sourcery] has completed a project that allows an Apple Remote to control anything you wish.

The idea is fairly straightforward: A device interprets the IR signals from an Apple Remote, and then outputs another IR signal that can do something useful on a non-Apple product. [Sourcery] uses an Arduino to do the IR translation, along with a set of IR emitters and detectors, and now the Apple Remote can control anything, from stereos to TVs to anything you can imagine. It also doesn’t remove the Apple Remote’s capability to control Apple products, in case you need yours to do that as well.

[Sourcery] notes that sometimes working with RAW IR signals can be a little difficult, but the information on their project and in their 25-minute video discusses how to deal with that, so make sure to check that out after the break. Don’t have an Apple Remote? You can do a similar thing with a PS3 controller.

Continue reading “Control Anything with an Apple Remote”

A Remote for CHDK Cameras Made Possible with Arduino

[AlxDroidDev] built himself a nice remote control box for CHDK-enabled cameras. If you haven’t heard of CHDK, it’s a pretty cool software modification for some Canon cameras. CHDK adds many new features to inexpensive cameras. In this case, [AlxDroidDev] is using a feature that allows the camera shutter to be activated via USB. CHDK can be run from the SD card, so no permanent modifications need to be made to the camera.

[AlxDroidDev’s] device runs off of an ATMega328p with Arduino. It operates from a 9V battery. The circuit contains an infrared receiver and also a Bluetooth module. This allows [AlxDroidDev] to control his camera using either method. The device interfaces to the camera using a standard USB connector and cable. It contains three LEDs, red, green, and blue. Each one indicates the status of a different function.

The Arduino uses Ken Shirrif’s IR Remote library to handle the infrared remote control functions. SoftwareSerial is used to connect to the Bluetooth module. The Arduino code has built-in functionality for both Canon and Nikon infrared remote controls. To control the camera via Bluetooth, [AlxDroidDev] built a custom Android application. The app can not only control the camera’s shutter, but it can also control the level of zoom.

Simple and Inexpensive Heartbeat Detector

There are many ways to detect a heartbeat electronically. One of the simpler ways is to take [Orlando’s] approach. He’s built a finger-mounted pulse detector using a few simple components and an Arduino.

This circuit uses a method known as photoplethysmography. As blood is pumped through your body, the volume of blood in your extremities increases and decreases with each heartbeat. This method uses a light source and a detector to determine changes in the amount of blood in your extremities. In this case, [Orlando] is using the finger.

[Orlando] built a finger cuff containing an infrared LED and a photodiode. These components reside on opposite sides of the finger. The IR LED shines light through the finger while the photodiode detects it on the other side. The photodiode detects changes in the amount of light as blood pumps in and out of the finger.

The sensor is hooked up to an op amp circuit in order to convert the varying current into a varying voltage. The signal is then filtered and amplified. An Arduino detects the voltage changes and transmits the information to a computer via serial. [Orlando] has written both a LabVIEW program as well as a Processing program to plot the data as a waveform. If you’d rather ditch the PC altogether, you might want to check out this standalone heartbeat sensor instead.

Reverse Engineering a Bathroom Scale for Automated Weight Tracking

[Darell] recently purchased a fancy new bathroom scale. Unlike an average bathroom scale, this one came with a wireless digital display. The user stands on the scale and the base unit transmits the weight measurement to the display using infrared signals. The idea is that you can place the display in front of your face instead of having to look down at your feet. [Darell] realized that his experience with infrared communication would likely enable him to hack this bathroom scale to automatically track his weight to a spreadsheet stored online.

[Darell] started by hooking up a 38khz infrared receiver unit to a logic analyzer. Then he recorded the one-way communication from the scale to the display. His experience told him that the scale was likely using pulse distance coding to encode the data. The scale would start each bit with a 500ms pulse. Then it would follow-up with either another 500ms pulse, or a 1000ms pulse. Each combination represented either a 1 or a 0. The problem was, [Darell] didn’t know which was which. He also wasn’t sure in which order the bits were being transmitted. He modified a software plugin for his logic analyzer to display 1’s and 0’s on top of the waveform. He then made several configurable options so he could try the various representations of the data.

Next it was time to generate some known data. He put increasing amounts of weight on the scale and recorded the resulting data along with the actual reading on the display. Then he tried various combinations of display settings until he got what appeared to be hexadecimal numbers increasing in size. Then by comparing values, he was able to determine what each of the five bytes represented. He was even able to reconstruct the checksum function used to generate the checksum byte.

Finally, [Darell] used a Raspberry Pi to hook the scale up to the cloud. He wrote a Python script to monitor an infrared receiver for the appropriate data. The script also verifies the checksum to ensure the data is not corrupted. [Darell] added a small LED light to indicate when the reading has been saved to the Google Docs spreadsheet, so he can be sure his weight is being recorded properly.