Doctor of Philosophy (PhD)
First Advisor's Name
First Advisor's Committee Title
Second Advisor's Name
Second Advisor's Committee Title
Third Advisor's Name
Third Advisor's Committee Title
Fourth Advisor's Name
Jean H. Andrian
Fourth Advisor's Committee Title
Fifth Advisor's Name
Fifth Advisor's Committee Title
Functional Near-Infrared Spectroscopy (fNIRS), Inertia measurementunit, machine learning, motion artifacts removal, vigilance during walking, sensor location optimization, sensor fusion, arx modeling
Date of Defense
Human vigilance is a cognitive function that requires sustained attention toward change in the environment. Human vigilance detection is a widely investigated topic which can be accomplished by various approaches. Most studies have focused on stationary vigilance detection due to the high effect of interference such as motion artifacts which are prominent in common movements such as walking. Functional Near-Infrared Spectroscopy is a preferred modality in vigilance detection due to the safe nature, the low cost and ease of implementation. fNIRS is not immune to motion artifact interference, and therefore human vigilance detection performance would be severely degraded when studied during locomotion. Properly treating and removing walking-induced motion artifacts from the contaminated signals is crucial to ensure accurate vigilance detection. This study compared the vigilance level detection during both stationary and walking states and confirmed that the performance of vigilance level detection during walking is significantly deteriorated (with a p
Previously Published In
 Siddiquee, M.R., Marquez, J.S., Atri, R., Ramon, R., Mayrand, R.P. and Bai, O., 2018. Movement artefact removal from NIRS signal using multi-channel IMU data. Biomedical engineering online, 17(1), pp.1-16.
 Siddiquee, M.R., Xue, T., Marquez, J.S., Atri, R., Ramon, R., Mayrand, R.P., Leung, C. and Bai, O., 2019, June. Sensor Fusion in Human Cyber Sensor System for Motion Artifact Removal from NIRS Signal. In 2019 12th International Conference on Human System Interaction (HSI) (pp. 192-196). IEEE.
 Siddiquee, M.R., Hasan, S.S., Marquez, J.S., Ramon, R.N. and Bai, O., 2020. Accurate Vigilance Detection During Gait by Using Movement Artifact Removal. IEEE Access, 8, pp.51179-51188.
SIDDIQUEE, MASUDUR R., "Detection of Human Vigilance State During Locomotion Using Wearable FNIRS" (2020). FIU Electronic Theses and Dissertations. 4395.
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).