Medication that cant be ingested through the gastrointenstinal tract has to be injected intravenous – usually by a doctor but in chronic diseases it can also be
carried out by yourself (“home treatment”, for example, venous puncture with
medication 3 times per week).
A chronic disease which requires frequent venous puncture is hemophilia.
In the blood clotting chain, one or more essential enzymes are missing or build in a non-working way due to DNA corruption. This can cause severe bleeding into joints, muscles or inner organs and is potentially live threatening if the rest activity of the clotting factors is below a few percent. Today, most of the clotting factors can be artificially synthesized through biomedical engineering (cell cultures with a changed DNA produce them), but they still have to be administered externally – injected into the blood stream by venous puncture. Children and families often face great difficulties here.
Venous blood vessels used for medication are not always easy to recognize and if the needle is not secure in the vein, it must be punctured again at another point.
Here our project comes into play: Using NIR (near infrared) Illumination and real-time image processing, we can make the veins more visible!
We (my brother Elias, Lucie [a friend of mine] and me) submitted this project to Jugend Forscht and won first prize on Berlin’s regional level. Please keep your fingers crossed for the next level on the 21st and 22nd of March…
Our aim was to develop an assistive technology for venous puncture for diagnostic purposes (blood sampling) or for medical drug administration.
Easy reproduction and low costs are important criteria for development.
In addition to the research and review of specialist literature on methods of venous localization and optical characteristics of human skin, we carry out our own experiments:
Illumination of skin with different wavelengths, cooling the arm and using thermography to watch the surface veins warming the skin again as well as a spektrometrical analysis of arterious and venous blood samples were among them.
With the results and findings, we developed two prototypes for computer-assisted venous localization! They differ regarding to the camera system used – one works with the PiCAM, the other with a modified webcam. Both have their own pros and cons…
Usually, cameras have an infrared blocking filter, which only allows the visible range of the electromagnetic spectrum to pass, because otherwise the image representation deviates strongly from our viewing habits. For the Raspberry Pi, there is a camera, where such a filter was not build in. It can be used without further modifications. However, this camera offers only a fixed focus and cannot focus the image scene automatically.
Another possibility is the modification of a webcam. The housing has to be opened, the blocking filter removed and as an additional lighting, 1mm small infrared LEDs need to be soldered in; along with some pieces of old analog developed film (blocking visible light, passing NIR). We have been able to use such a camera from my previous research project (“eye control wheelchair”).
We use the single board computer Raspberry Pi (will work from from version 2 on), which is available at low cost worldwide and has proven itself in many projects as sufficient for image analysis and image processing. Using 3D printing, all required housings for the Raspberry Pi, the cameras the infrared illumination and the display could be designed and changed easily 🙂 And you can build your own version by just downloading the code and the cad-files from my github…
We presented our project to Dr. Klamroth, head of department of internal medicine at Vivantes Berlin Friedrichshain, who was impressed and gave us some tipps to improve the usability.
A possible future development would be the use of smartphones with an external camera that can record infrared light – but until now I haven’t had success in installing Android Studio and working with openCV yet…
You can download the full report here (in German): Veindetection_German_Report