Sara Lal
Affiliations: | School of Life Sciences | University of Technology Sydney |
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| Lees T, Chalmers T, Burton D, et al. (2023) Psychophysiology of Monotonous Driving, Fatigue and Sleepiness in Train and Non-Professional Drivers: Driver Safety Implications. Behavioral Sciences (Basel, Switzerland). 13 |
| Chalmers T, Eaves S, Lees T, et al. (2022) The relationship between neurocognitive performance and HRV parameters in nurses and non-healthcare participants. Brain and Behavior. 12: e2481 |
| Akella A, Singh AK, Leong D, et al. (2021) Classifying Multi-Level Stress Responses From Brain Cortical EEG in Nurses and Non-Health Professionals Using Machine Learning Auto Encoder. Ieee Journal of Translational Engineering in Health and Medicine. 9: 2200109 |
| Lees T, Chalmers T, Burton D, et al. (2021) Electrophysiological Brain-Cardiac Coupling in Train Drivers during Monotonous Driving. International Journal of Environmental Research and Public Health. 18 |
| Lees T, Maharaj S, Kalatzis G, et al. (2020) Electroencephalographic prediction of global and domain specific cognitive performance of clinically active Australian Nurses. Physiological Measurement. 41: 095001 |
| Chalmers T, Maharaj S, Lees T, et al. (2020) Impact of acute stress on cortical electrical activity and cardiac autonomic coupling. Journal of Integrative Neuroscience. 19: 239-248 |
| Lees T, Elliott JL, Gunning S, et al. (2019) A systematic review of the current evidence regarding interventions for anxiety, PTSD, sleepiness and fatigue in the law enforcement workplace. Industrial Health |
| Maharaj S, Lees T, Lal S. (2018) Prevalence and Risk Factors of Depression, Anxiety, and Stress in a Cohort of Australian Nurses. International Journal of Environmental Research and Public Health. 16 |
| Lees T, Chalmers T, Burton D, et al. (2018) Electroencephalography as a predictor of self-report fatigue/sleepiness during monotonous driving in train drivers. Physiological Measurement. 39: 105012 |
| Lees T, Shad-Kaneez F, Simpson AM, et al. (2018) Heart Rate Variability as a Biomarker for Predicting Stroke, Post-stroke Complications and Functionality. Biomarker Insights. 13: 1177271918786931 |