Disease detection and quantification with inertial sensors

Supervisors: Dr Thushara Perera

People with movement disorders (e.g. Parkinson’s disease and dystonia) find it challenging to perform activities of daily living (such as getting dressed, eating, and drinking) that most take for granted. Fine motor skills are stifled by tremors, movement becomes strenuous due to increased muscle stiffness, and postural instability leads to falls. Evaluating these symptoms is crucial to managing therapy, seeking new interventions via clinical trials and understanding mechanism of disease through research. Existing assessment techniques rely on subjective methods such as surveys, patient diaries, and observation-based rating scales. This project will develop a medical device that allows us to overcome several limitations associated with subjective techniques: 1) inter- and intra-rater variability; 2) bias; 3) floor and ceiling effects; 4) limited resolution on ordinal scales; and 5) intermittent measurements at single time points. The student will design and manufacture prototype wearable devices, perform bench-top evaluation, and assist with clinical trials.

The general methods to be used in this project include digital signal processing, rapid prototyping (3D printing, PCB layout and manufacture, etc.), software/firmware development, test and verification, human clinical trials, and data science.

This PhD project would ideally suit an electronics or biomedical engineer with an interest in medical device development. Previous experience with hardware design, software/firmware development, and rapid prototyping will be highly regarded. Strong communication skills are crucial as well as a willingness to work in a multidisciplinary team in a flexible environment.

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