Hackaday Prize Entry: A Complete Suite Of Biomedical Sensors

The human body has a lot to tell us if we only have the instruments to listen. Unfortunately, most of the diagnostic gear used by practitioners is pricey stuff that’s out of range if you just want to take a casual look under the hood. For that task, this full-featured biomedical sensor suite might come in handy.

More of an enabling platform than a complete project, [Orlando Hoilett]’s shield design incorporates a lot of the sensors we’ve seen before. The two main modalities are photoplethysmography, which uses the MAX30101 to sense changes in blood volume and oxygen saturation by differential absorption and reflection of light, and biopotential measurements using an instrumentation amplifier built around an AD8227 to provide all the “electro-whatever-grams” you could need: electrocardiogram, electromyogram, and even an electrooculogram to record eye movements. [Orlando] has even thrown on temperature and light sensors for environmental monitoring.

[Orlando] is quick to point out that this is an educational project and not a medical instrument, and that it should only ever be used completely untethered from mains — battery power and Bluetooth only, please. Want to know why? Check out the shocking truth about transformerless power supplies.

Thanks to [fustini] for the tip.

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.

The 2015 Hackaday Prize is sponsored by:

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.