
Duval Christian
Contact information
Biography
Christian Duval is a Full Professor in the Department of Physical Activity Sciences at Université du Québec à Montréal (UQAM) and a researcher at the Centre de recherche de l’Institut universitaire de gériatrie de Montréal (CRIUGM). He holds a PhD in Neurological Sciences from McGill University and has developed a strong expertise in the study of movement disorders, especially Parkinson’s disease. He is also an active member of several research groups, including the Quebec Parkinson Network and the Groupe de recherche en activité physique adaptée (GRAPA).
Dr. Duval’s research lies at the intersection of neuroscience, human kinetics, and digital health. He is recognized for his interdisciplinary collaborations and his technological innovations using wearable sensors and smartwatches to objectively evaluate motor symptoms and mobility in both clinical and real-world settings.
Research interests
Dr. Duval investigates how involuntary movements (such as dyskinesias and tremors) affect voluntary motor function and the quality of life of individuals living with neurodegenerative disorders, particularly Parkinson’s disease. He also studies healthy aging and mobility in natural environments using digital phenotyping approaches and AI-based analysis of data from inertial sensors.
Dr. Duval has led or co-led several funded research projects supported by CIHR, NSERC, Parkinson Quebec Network, the W. Garfield Weston Foundation, Integra LifeSciences, and the Quebec Network for Research on Aging (RQRV). Notable projects include:
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Levodopa-induced dyskinesia and its impact on participation in advanced Parkinson’s (CIHR, 2023–2028);
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Ecological gait assessment using wearable technology (NSERC, 2020–2025);
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Clinical phenotyping with wearable sensors (Parkinson Québec Network);
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Improving quality of life in Parkinson’s patients with wearable sensors (Parkinson Québec);
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COVID-19 and mobility in older adults (RQRV, 2020–2021).
Dr. Duval has co-authored over 60 peer-reviewed papers on the use of inertial sensors, movement quantification, and digital symptom monitoring in neurological populations.
Keywords
Parkinson’s disease, mobility, dyskinesia, aging, inertial sensors, neuroscience, digital phenotyping, rehabilitation, physical activity, involuntary movements