Summer Research Internships

Supervisor Dr. Ian Cunningham, Medical Biophysics and Robarts Research Institute

Project Description Malaria is one of the four most life-threatening infectious diseases worldwide. While treatments are often available, they must be delivered as quickly as possible after onset of symptoms. Malaria is a parasite carried by mosquitos and can be diagnosed with a microscope and blood smear. However, most infections occur in rural areas where these facilities are not available due to limited resources. We are developing a low-cost microscope that is based on recent discoveries in the field of computational optics that have the potential to change the world of microscopy imaging. Using a simple 3-D printed microscope design and Raspberry Pi camera, we use optics to capture the image as a Fourier transform and take the inverse Fourier transform to create the image. With this approach, ultra-high resolution (1 µm) images with large field of view (10 mm) can be acquired at the same time, which is ideal for microscopy. Our goal is to be the first team in the world to use this approach for malaria diagnoses.

Skills/Experience Necessary We are looking for a student with good computer programming skills, in particular Python and Matlab, an interest in physics, and a willingness to learn about optics and Fourier transform.

Supervisor Dr. David Holdsworth and Dr. Maria Drangova, Medical Biophysics and Robarts Research Institute

Project Description One of the challenges in biomedical training programs in low- and middle-income countries is the high cost of laboratory equipment that is required during training. For example, biomedical engineering programs typically require access to material testing systems, such as indentation testers to characterize low-modulus materials and soft-tissues. While these devices are commercially available, even a small unit is typically over $50,000 CAD, making it difficult or impossible to incorporate into training programs. Our group has developed a low-cost soft-tissue testing device, which is based on common-off-the-shelf mechanical components and open-source software control using a common microcontroller (Arduino Uno). The device has been developed to operate with a simple serial command-line menu, and also incorporates a Pythonbased control program that can be used to acquire and save data according to specific protocols. The challenge now is to develop additional modules that will allow the device to perform additional material testing protocols (such as compressive, tensile, and flexural), as well as cyclic testing for fatigue analysis. The ultimate goal of this project is an open-source product that can be widely distributed in low-resource settings.

Skills/Experience Necessary Completion of second year courses in Mechanical Engineering, Mechatronic Systems Engineering, Computer Engineering, or Electrical Engineering would be preferred. Students in Medical Biophysics or Physics with a background in working with microcontrollers would also be eligible. Experience with Python, C, and the Arduino IDE would be preferred.

Supervisors Dr. Keith St. Lawrence, Dr. Mamadou Diop

Project Description Near-infrared spectroscopy provides a vital tool for measuring tissue oxygenation and metabolism with a myriad of applications from assessing muscle physiology to monitoring brain health in critically ill patients. Historically, spectrometers adapted for these applications were originally developed to resolve fine spectral features. These spectrometers are typically costly and over-engineered for biomedical applications. This project will focus on developing an inexpensive alternative, taking advantage of the availability of inexpensive light sources (i.e., laser diodes and LEDs) and silicon photomultipliers (SiPMTs) for light detection. The projects focus on selecting the appropriate number and colours of sources to generate light across the near-infrared spectrum and constructing a linear array of SiPMTs with the spectral resolution to detect the broad features encountered in tissue applications. The projects also involve using a custom-made spectrometer with a variable entrance-slit to change the device’s spectral resolution and light throughput.

Skills/Experience Necessary The student should able to develop Matlab scripts for data analysis and visualization and should be interested in learning about light-tissue interaction, the use of NIR light to measure physiological parameters, and tissue-mimicking phantoms. The student will be trained in scientific communication, including oral presentation and scientific writing.