High-Fidelity Data Converters for Medical Diagnostics

Diagnostic medical devices work by translating our vital signs, such as neuron electrical activity and brain waves, into digital data that can be manipulated by a computer. High-speed computer processing improves diagnoses by presenting the physician with a numeric or graphical readout of important features extracted from the signal. Often, the ability of computer programs to extract the most diagnostically-relevant information is limited by how well the device can recognize and ignore background electrical noise common in clinical environments. Many emerging medical technologies (such as diagnosis of spinal cord injury using nerve conduction signals or automatically controlling anesthesia by detecting changes in brainwaves) could be improved if the measurement tools were more sensitive. In partnership with audio technology company ESS Technology, this project aims to design an analog-to-digital converter for recording these important yet weaker signals and allow them to explore the applications of their technologies to medical devices.

Faculty Supervisor:

Guy Dumont

Student:

Brett Hannigan

Partner:

ESS British Columbia Holdings Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

Program: