Working off the idea that we wanted a portable device quickly led us to a consumer 3D printer allowing us to do rapid prototyping. The printer we used is an Ultimaker 2+ provided to us by Ultimaker. We wanted a device that could show a fluorescent signal so we came up with our first designs. The fluorescent molecules produced by our system are excited by UV-LED’s with a specific wavelength. The emission spectrum is visible by the naked eye and this is how we planned to read out the signal. The membrane sealed sample vials containing our bacterial system are placed in the device from the top. Initially we started off with a device which fits one sample. However, we soon realised that adding a positive and negative control makes the device more reliable. Once the button is pressed the UV-LED’s are turned on and the signal can be compared to the positive and negative control in order to determine the result. This approach was problematic since lighting conditions, background signal and observers are not a set variable. This prompted us rethink the way the device works and version 2 was on the way. Moreover, we showed this initial design to dr. Philippe Büscher, head of the Unit of Parasite Diagnostics (Institute of Tropical Medicine, Antwerp). He liked the easiness of use and the presence of a positive control. He endorsed our idea of quantifying the fluorescent signal and adding an LED-screen for a more objective read-out. Also, dr. Büscher suggested us to make the labels for the sample, positive and negative results better readable. We implemented this into the next prototype.

The first working prototype included space for 3 membrane sealed sample vials: a positive control, the sample and a negative control. In order to take out the variables of the lighting conditions, background signal and observers we wanted to use cheap and simple electronics to read out the signal. This led to the removal of the ‘windows’ in the front and a slightly bigger design to accommodate the electronics. The improved computational approach to read off the signal was based on Light Dependent Resistors (LDR). This component changes its resistance according to the amount of light that it receives. This resistance can be measured via a simple circuit (See Figure) and processed by the arduino microprocessor. Once the button is pressed the device excites the sample vials with UV light and the emission spectrum is detected by the LDRs. The signal of the sample is compared to the positive and negative control and the final result is displayed on an integrated OLED display on the front. Although this is a mayor improvement over trying to detect the signal by eye, this way of detecting the light is unreliable due to the characteristics of the components used.

To improve the measurement capability of the system, various components were exchanged. First we chose to calibrate our device using fluorescein, as this circumvents the use of recombinant bacteria in this part of the prototyping phase. The UV-LEDs were exchanged for 475nm blue Cree LED’s, which will excite fluorescein provided in the InterLab study kit. This wavelength is much safer to use as it is not harmful to the retina. Second, circuit containing LDR’s were replaced. Whilst cheap, LDR’s are not very suitable for taking precise measurements. To improve on this we chose to implement photodiodes, a semiconductor which converts light into electrical current. This signal needs amplification, for which small transimpedance amplifier (TIA) circuit containing an operational amplifier was used (figure X). Furthermore, a small piece of orange filter paper was placed in between the photodiode and the sample. The filter paper blocks much of the blue light coming from the LEDs, thereby reducing the amount of background signal. These parts were combined in a prototype setup as seen in figure X. Measurements were taken using a fluorescein dilution series, the results of which are shown in figure X.
The resulting graphs show a very nice calibration curve in the range of 0 to 2 mM of fluorescein. In order to check repeatability the whole setup was built again and the results are shown in Figure Xb. The results show the same very nice calibration curve and proves that this system is reliable and reproducible.

The students of the Quantified-Self course, as well as dr. ir. Arnold van Vliet advised us to apply GPS information to the device. The possibility of saving the diagnosing data together with the GPS data allows the Mantis diagnostic system to aid mapping and monitoring outbreaks of a certain disease. The data can easily be transferred from the SD card to a computer and uploaded to a cloud service. All the data gathered by the Mantis devices in the field will help create a global picture of all disease outbreaks. This is essential in monitoring outbreaks and preventative measures can be taken to stop epidemics from emerging. One of our final prototypes was evaluated by dr. Erwan Piriou, Laboratory advisor at MSF. He confirmed the easiness of use and believes that “people would definitely be able to use this device in the field”.