Handheld Biological Lens-less Detection Unit

Team: Nick DiFilippo, John D. Jones, Mark DiFilippo

The ultimate aim of this project was to produce a handheld device capable of detecting C-Reactive Protein from a drop of blood using a lensless CCD webcam. This project had multiple aspects that I helped work on such as the lensless detection, fluid flow control, smartphone integration, and electrical engineering of the device. My main focuses were the fluid flow control and smartphone integration as those were the topics of my Master's Thesis.

Lens-less Detection

To understand some of the choices made with the imaging, it is first important to understand how the biological assay works. First we functionalize a chip and put capture antibodies on it (1). Then when the CRP flows through, the CRP wants to stick to the capture antibodies (2). Next, detection antibodies that want to stick to the CRP flow through (3) and finally quantum dots that stick to the detection antibodies flow through (4). The quantum dots fluoresce when a UV light is shined at them and thus the more quantum dots, the more CRP and a higher signal.



To keep the cost of the unit down, it was required that the lens of the webcam be removed. By removing the lens, the image the webcam produced would be out of focus, however this was ok because we weren’t interested in the actual image the webcam produced but rather the pixel values from the light that the webcam received. By using filters over the webcam, we could choose the bandwidth of light that we wanted to capture and was emitted from the quantum dots. The webcam that we eventually chose was a Fire-I because we were able to get the raw data from the pixels and not pixel values that had been processed by the webcam.

Fluid Flow Control

We needed an automated pumping solution to get the reagents in our sequentially loaded chip over the detection area reliably. The previous method that was used was based on timing and was unreliable. A LED was placed over the detection area and the same camera that was used for detection could also be used for active control of the micropump.





Looking at the images from the CCD, it was possible to tell if liquid or air was in a detection area because of the pixel brightness. If air was in the channels, the channel was darker than if liquid was in the channels. Using this information, a Matlab algorithm was developed to look at the difference in a region of the image and determine if air or liquid was present. Since the order that the reagents were being pumped in was known in advance, the Matlab script was connected to an Arduino and the micro pump was turned on and off at the appropriate times.

Smartphone Integration

This device was also given wireless capabilities that would the user to control and monitor the device through their smartphone app. A test was performed by inputting the user information in the smartphone app and pressing start (1). Next, the microcontroller receives instructions to start the test (2). Then the Microcontroller makes connections with a main server that is running Matlab and communicates directly with the microcontroller to tell the microcontroller what to do (3). Matlab performs the analysis and the results are sent through e-mail as a PDF report and also sent back to the smartphone app.




The Arduino that was used an Arduino Nano Mega from Emartee and the WiFi Shield used was the Linksprite Cooperhead. The Copperhead shield needed to be modified because of the locations of the MOSI, MISO, SCK, and SCL. The only wires that are currently needed are to attach the CCD imager to the computer.

Design of the Device

The final device houses a TouchShield Slide (1), Wifi Shield (2), Arduino Microcontroller (3), Rechargeable Battery (4), CCD Imager (5), U.V. Laser Diode (6), CCD Driver Board (7), and 500nm Long Pass Filter (8). There is a panel that lifts up allowing the chip, containing the sample to be analyzed, to be placed in the unit.

Papers that were written from this research

Nick DiFilippo Thesis:
Smartphone Integration and Fluid Flow Control in a Hand-held Microfluidic Lab-On-Chip Biosensor

John D. Jones Dissertation:
A Handheld Microfluidic Lab On Chip Biological Detection System

Peer Reviewed Paper:
Monitoring of Sequentially Loaded Reagents to a Detection Area in a Microfluidic Chip