Brain to Machine Interface Based on EEG Signals

Brain to machine interface (BMI) is a research topic aiming to develop more direct interface between a human brain and a machine. The research is primarily motivated by desire to help humans who are in need of assistance or repair of their

Tailoring Rheological Properties of RigidReclaim™ Resin Streams

The RigidReclaim™ technology under development by Entropex is an innovative process which converts a comingled, contaminated Mixed Rigid waste stream into highly pure, commercially valuable resins. The non-uniform natures of the plastic waste pose a significant challenge to satisfy the quality requirements for high-value applications. This project is a critical component of the RigidReclaim™ technology and it aims at tailoring the rheological properties of the recovered resin streams comparable to those of virgin resins with reliable novel chemical additives.

Development of novel nanomaterial in advanced lithium batteries for electric vehicles

There is an increasing demand for development of electric vehicle (EV) due to the serious energy shortages and environmental pollution. Advanced Lithium (Li) rechargeable batteries are the most promising power systems in commercial Hybrid EV. The main challenge is still the development of alternative material in terms of energy density, cycability, safety, and cost. In this proposed research, novel nanostructed material and catalysts will be developed to achieve these objectives for EV applications. This would help to make lithium batteries competitive with internal combustion engine.

Coil and Sequence Development for Metabolic Magnetic Resonance Imaging

Dynamic Nuclear Polarisation makes it possible to boost the MRI signal of 13C labelled pyruvate 10,000-fold, overcoming the low natural signal of carbon. This makes imaging of metabolic processes possible, and could provide useful insight on changes in cellular metabolism due to cancer.

Research and Development of Automated Pluripotent Stem Cell Propagation

Stem cells are at the forefront of modern medicine and are expected to revolutionize both the human and veterinary healthcare industries. Currently, a major obstacle to the field is the time-consuming and costly technical time spent growing and maintaining various stem cell populations. The degree of contamination with non-stem cells, ability of the stem cells to thrive and grow, and quality of the stem cells depends largely on the skill of the technician.

Development and validation of a mathematical model of brain activity during deep brain stimulation in Parkinson's disease

Deep brain stimulation (DBS) consists in implanting electrodes delivering electric stimuli in deep brain structures to relieve motor symptoms of Parkinson's disease (PD). Even if DBS is successful in alleviating symptoms for about 50,000 patients worldwide, it is an invasive neurosurgical technique, and its mechanisms of action remain elusive. This therapy could be greatly improved by targeting the cortex, also impacted by DBS. However, a pre-requisite is to understand how cortical activity is impacted by DBS.

Fabrication of the 3rd generation photovoltaics using TiO2 nanotubes and quantum dots

Due to depleting oil supplies and the global climate change we are compelled to seek alternative sources to supply our growing energy demand. Among green energy technologies, utilizing solar energy is the only way to address that problem, and tapping into this vast quantity of energy represents a grand challenge of scientific research and engineering. Current silicon technologies have thus far experienced limited deployment, primarily due to material costs. Developing novel methods of capturing solar energy is required.

Development of a real-time analytical tool for predicting the tissue fate in ischemic stroke

Thrombolytic therapy is the mainstay of stroke treatment. However, this treatment can be potentially harmful. A patient-specific model of expected outcome would greatly facilitate the treatment decision making process both for clinicians and patients. We propose to develop a clinical tool by incorporating the imaging and clinical dataset to predict the fate of tissue in ischemic stroke. We expect the product to enable real-time quantification of expected tissue outcomes using patient- and tissue- specific thresholds.

A Self-Balancing Omni-Delta Robot

In this project, a modified Delta parallel robot is designed in which the number of passive joints is reduced, and an active joint is added to the hardware. To the best of our knowledge, this configuration seems to be the first of its kind.

In this project, kinematic and dynamic analyses will be performed. Active compliance control and collision anticipation algorithms will also be developed for this new design. This configuration will be used as the “waist” of an omni-directional, self-balancing service robot. Methodology and novelty of approach and/or application