2015 Student Defenses
The Bloorview Research Institute is proud to celebrate our student accomplishments.
Concussion Research Centre
"Bloorview has acted as an excellent platform for my learning as a student. The Concussion Centre has supported my academic growth and encouraged my scientific interests. I have met so many intelligent people at BRI and I am constantly inspired by researchers who want to discover something new. I look forward to seeing how BRI continues to support their trainees in remaining independent and motivated to influence the scientific community."
Heart rate variability following concussion in youth athletes: An observational pilot study
Background/Rationale: Mild traumatic brain injury (mTBI), also referred to as concussion (for the sake of this thesis these two terms will be used interchangeably) is of great concern within the pediatric sport population due to its high prevalence and potential impact on neurological development. Currently, both subjective and objective measures of diagnosis and recovery are utilized to manage concussion. Nonetheless, these tools exist on a spectrum whereby the objectivity of these measures may be influenced by subjective factors, such as distraction, motivation and practice effects, and thus may limit the diagnostic value of the test. There is a need for additional inexpensive and objective measures for concussion assessment and management. Heart rate variability (HRV), an objective marker of physiological stress can be used as a measure of stress capacity and may fill this gap. To date, there is a paucity of research on HRV measures post-concussion, especially amongst youth athletes. Conclusion: Changes in HRV were associated with an increase in post-concussion symptom inventory scores. Further, days post injury and self-reported symptoms of concussion both showed a main effect on measures of HRV. These preliminary data may guide future research in determining a physiological marker of stress post-concussion in youth athletes. The results from this study will add to the current knowledge base of concussion and promote improved approaches to assessment and management of concussion in youth athletes.
"I enjoyed my time in the Bloorview Research Institute. All of the people that work here make this institute a wonderful environment to work in, not only because of the quality in work we do, but also because of their warmth that make the work so enjoyable."
Assessment of Postural Deviations Associated Errors in the Analysis of Kinematics Using Inertial and Magnetic Sensors and a Correction Technique Proposal
The MVN BIOMECH Awinda system has been used to analyze motion kinematics beyond laboratory conditions. However, it has a limitation in the rehabilitation field since it relies on a predefined posture to calibrate the sensors: the “N-Pose”, which is impossible to attain for some patient populations. The aims of this thesis are to assess the postural deviation error in gait kinematics measured with this system as well as two proposed correction approaches: the orientation correction (OC) and planar angle correction (PAC). After analyzing the crouch gait of four able-bodied participants it was found that the postural deviation error can be considered as a constant shift in kinematic values and that it can be corrected with both approaches. Digital images are explored as a means to capture the true body posture attained during the calibration.
"These past few years have been an unforgettable journey. I would like to express my deepest appreciation to my supervisor Dr. Tom Chau and the rest of the staff and students at Holland Bloorview for their help, guidance, support and wisdom."
A Neurofeedback-Based Near-Infrared Spectroscopy Brain-Computer Interface
Near-infrared spectroscopy (NIRS) brain-computer interfaces (BCIs) enable individuals to interact with their environment using only cognitive activities. This thesis investigates the development of a more user-friendly, intuitive, and easy to use NIRS-BCI through six research objectives: exploring prescribed and personalized mental task frameworks offline, using researcher-selected tasks to move beyond the binary paradigm, exploring correlations of user characteristics with accuracy, comparing user-selected personalized tasks to prescribed tasks online, weaning off mental tasks to achieve voluntary self-regulation, and applying personalized frameworks to a client case study.
Firstly, personalized tasks outperformed prescribed tasks in a five-session offline study conducted on ten able-bodied participants. Specifically, user-selected tasks resulted in significantly higher ease-of-use, while researcher-selected tasks resulted in significantly higher accuracies. The same data were used to show that researcher-selected personalized mental tasks enabled classification in some users beyond a binary BCI paradigm. Accuracy was strongly positively correlated with perceived ease of session, ease of concentration, and enjoyment, but strongly negatively correlated with verbal IQ. In a second study, when comparing two able-bodied groups online (N = 9 and N = 10), the usability of user-selected personalized mental tasks exceeded prescribed mental tasks without a decrease in accuracy. Expanding on this study, the nine able-bodied subjects who used user-selected tasks took part in an additional ten sessions and were weaned off mental tasks to achieve online voluntary self-regulatory control of a BCI using a neurofeedback-based paradigm. Participants indicated that they found self-regulation to be more intuitive and easier to use than mental tasks. Finally, user- and researcher-selected frameworks were applied to a client with undiagnosed motor impairments, unveiling a host of neuropsychological challenges to BCI control. Overall, this thesis advances the field of knowledge of NIRS-BCIs, specifically with respect to usability.
"I was very fortunate to be part of the BRI during my time as a student. The staff and trainees provided a supportive, friendly and intellectually stimulating environment."
Adaptive brain-computer interfacing through error-related potential detection
This thesis investigates possible improved brain-computer interface (BCI) performance by using the error-related potential (ErrP) to guide adaptation in two forms: first by gradually adapting the algorithms that differentiate brain activity, and second by automatically correcting mistakes when observed. Five studies were conducted, each investigating a unique aspect of incorporating ErrPs into BCIs. In study one, gradual adaptation of linear classifiers differentiating left- and right-hand motor imagery was explored in computer simulation when labels were derived from a realistic, imperfect ErrP detector. Learning from all trials was compared to reactively learning from errors, and the former more consistently improved accuracies across a wider range of learning rates. In study two, a realistic error detector was biased to several false positive rates and the risk associated with ErrP-based adaptation of several motor imagery BCIs was evaluated in light of those biases. Reweighting of a classifier ensemble had lower risk than incremental adaptation of the ensemble's base classifiers, and a unique risk profile across error detector false positive rates for each adaptation method was discovered. In study three, automatic correction of a visual P300 speller was employed using an error detector that combined the ErrP and spelling confidence. Errors were detected with an average sensitivity of 86.67% and specificity of 96.59% (n=11), and automatic correction increased selection accuracy by 13.67 percentage points. In study four, ErrP-based error detection was used for gradual adaptation of visual P300 classifiers both when the stimulus timing pattern remained constant, and when stimulation speed doubled. By retraining when stimulation speed doubled using ErrP-based labels subject to a confidence score, online spelling efficiency increased from 1.77 to 2.63 symbols per minute (n=11). No significant improvement was found for this partially supervised adaptation when stimulation speed remained constant. In study five, ErrP detection was investigated in an auditory P300 BCI. ErrPs were detected with an area under the curve of 0.946 and simulated auto-correction improved ITR by 2.3 bits/min (n=9). These studies demonstrate promise for incorporating ErrPs into BCIs, particularly auditory P300 BCIs, provided false positives are minimized and BCI confidence is considered.
Marcela Correa Villada
"It's been inspiring to be part of BRI and be able to see the hard work and the passion that everyone puts into their work. My time at BRI definitely helped me grow and motivated me to keep working towards better possibilities for individuals with disabilities."
Predicting Movement Intention in Children with and without Dyskinesia using Accelerometry