FUNCTIONAL NEAR INFRARED SPECTROSCOPY FOR THE ASSESSMENT OF MOTOR CORTEX PLASTICITY IN PEDIATRIC SUBJECTS AFFECTED BY CEREBRAL PALSY by

iii ACKNOWLEDGEMENTS I would like to thank Dr. George Alexandrakis for giving me this great opportunity in pursuing my interests in biomedical engineering. His continuous advice and support have been a great help throughout my research. I am sincerely grateful to Dr. Khosrow Behbehani for his time and advice on both my project and schoolwork. I would like to also thank Dr. Hanli Liu for her support and suggestions throughout this project. I would also like to show my gratitude to Dr. Delgado for his suggestions of the clinical applications, and for letting me use the new wireless surface EMGs. I am also grateful to Dr. Mario Romero for his advice on the statistical analysis and physiology. I would like to thank Dr. Fenghua Tian for his advice and suggestions in the technical aspects of this project. I would like to acknowledge Mr. Sameer Dhamne, Mr. Tamer Desouky, and Mr. Nayan Asanini for their help. I would like to also acknowledge Texas Scottish Rite Hospital, Mrs. Nancy Clegg, and the nursing staff for their support throughout this project. As for my family, I would like to thank my mother, Rubina Khan, for always being there and for her love and support. I would like to also thank my father, Aslam Khan, for his support and advice throughout my life. And of course, there is my brother, Hamza Khan, who never fails to make me laugh. I would like to also thank my lovely fiancé, Sana Muntajibuddin, for her love and support, and for making sure I remembered the circle of Willis. My family members are the most valuable people to me. Functional near infrared spectroscopy (fNIRS) is widely used to monitor hemodynamic changes occurring in the cerebral cortex as a result of neuronal activation. One of the current challenges in this field is that activation-related hemodynamic signals are often eclipsed by global hemodynamic fluctuations due to cardiac pulsation, respiration and Mayer waves. In this study, we demonstrate by using a combination of principal component analysis (PCA) and adaptive filtering that the global hemodynamic modulation signals can be effectively removed from the fNIRS measuring cortical hemodynamic response. While pediatric subjects were performing a finger tapping task, we concurrently recorded cardiac pulsation and respiration using a pulse oximeter and a piezo-electric transducer, respectively. The results indicate that fNIRS data quality is significantly improved, as quantified by temporal signal-to-noise ratio (SNR), contrast-to-noise ratio …