It’s a well-known fact that tech is getting cheaper, but for most people, this doesn’t mean much. It means browsing the internet and checking emails on a slimmer laptop, using fancier, simpler interfaces, and not having to know any of the workings under the hood of a computer. Don’t get me wrong, I’m not one of those snobs who look down on others because they don’t “nerd out” on the latest processor, or research the specs to get the best deal on their laptop. I have a MacBook pro, iMac, and iPhone because it’s just easy. And yes, they look nice. I want to enjoy my tech experiences. However, cheaper tech can empower the tech savvy clinician to do things they couldn’t do before via the Raspberry Pi. A cheap, single board, Linux based computer that can fit in the palm of your hand. Why is this empowering? You have a tiny computer, that has low power consumption, and can carry out a specific purpose all day, for less than £50! Here are 3 concepts that clinicians should be familiar with:
The list is pretty much endless. There are projects ranging from home servers and home sensor kits to robotic kits. If you have zero tech experience, but you’re interested in how to use these things, I recommend buying a Raspberry Pi robotics kit from Amazon [link]. Note: you will have to buy the Raspberry Pi separately. There are varying degrees and some are even aimed at kids so whatever your level, you will find a fun project that will get your hands dirty. These packs will even have step by step instructions on how to write the code for the project. The more fun and less serious the project, the better. When I’m teaching medics how to code, I always get them to make small silly projects, calculators, and games. This breaks down the learning curve into fun steps, making it easier to learn. Remember, the Raspberry Pi is a low powered computer, so there are some exciting and… imaginative projects. For instance, there is a group of guys who used a Raspberry Pi with some contact sensors on the doors of the toilets, to create an app that alerts the guys in the office when the toilet is free [link].
Ok, so I’m not going to advocate that you try and forward the field of surgical robotics with a toy kit from Amazon. However, there are areas where this can bring 21st tech concepts to medicine at a very cheap price. Straight off the bat, data-feeds. Have a particular web based data feed that you’d like to display constantly? Simply screw the raspberry pi to the back of a display, open up the data-feed/dashboard that you want, and let it run. Below is a simple domestic example of someone displaying their Google calendar:
This will cost you £50 and however much the screen is. For a low cost, you can have a specific computer dedicated to a particular task. With the ever increasing storage for a small price, simply connecting an external hard drive or a USB memory stick can upgrade the Pi to a data logging device. With this, the Pi can be a simple, cheap solution to all those none sexy issues that could benefit from a tech lift. Stock tracking, quality checks for defibs, logging for audit trails and so on. This will require a little bit of Python coding but the entry level is fairly low.
With a growing community, there are a ton of add ons and the list just keeps growing. Adafruit hats make it possible for a user to simply bolt on a gadget. A prime example is a simple touchscreen:
But for the medics, the exciting part is the medical bolt-ons! There’s an e-sensor platform for the raspberry pi [link]. The bolt-ons are not limited:
However, remember that pointless regulation reigns supreme. Although this isn’t tough tech to replicate and the math/calibration behind the standard GPS is way more complex than a pulse oximetry, big med tech companies have fought hard to keep regulation high to stop competition so they can charge really high prices for old basic tech. Use these med bolt-ons for research purposes only. A bit of simple python code and a hard drive and you’ll start doing some advanced stuff. Hell if you get your head around the pre-built machine learning library [link], you could even apply some machine learning algorithms to the data that you’re pulling from your research patients.