What is this Study about?

Hearing loss is the third most common chronic health condition among people 65 and older and increases the risk of social isolation, depression, communication difficulties and dementia. Dementia risk may be reduced through hearing rehabilitation, and it is critical to develop tools for identifying hearing loss and its impact on communication. The Hearing and Functioning in Everyday Life Questionnaire (HFEQ) is a measure to identify hearing loss and everyday life functioning, not yet been evaluated for people with combined hearing loss and cognitive impairment. To bridge this gap, the aim is to evaluate the HFEQ for this group. The study has a cross-sectional observational study design. Adults over 60 years, with hearing loss and with and without cognitive impairment will be recruited. Data collection will include a cognitive and hearing assessment, assessment of conversation effectiveness and efficiency, hearing and general health history and five questionnaires (HFEQ, the Life-Space questionnaire, the Social Functioning in Dementia scale, and the PROMIS anxiety and depression scales).

What is this Study about?

The aim of this study is to understand how people with dementia, family/friend carers and healthcare providers experience the Driving and Dementia Roadmap website. This website contains resources to help people in the decision-making about when to stop driving and adjust to life after driving. We are also interested in knowing how the Driving and Dementia Roadmap may impact how people manage stopping to drive. The findings of this study will be used to improve and ensure that resources, like the Driving and Dementia Roadmap will continue to be available for people with dementia and those who support them. 

What is this Study about?

This study will assess if an in-vehicle Driving Monitoring System can identify differences in driving behaviours between older adults who are cognitively healthy, those with mild cognitive impairment, and those with mild dementia. 

What is this Study about?

This research aims to explore the perspectives of older adults living with dementia, providing a nuanced understanding of their experiences and challenges. Second, it seeks to investigate the role of physical activities in their lives, examining how engagement in such activities influences their cognitive function and mental well-being. Finally, this research aims to inform interventions and policies that can support older adults in maintaining their cognitive health and overall well-being.

The data will be used for the researcher’s master’s thesis, and for publishing peer-reviewed and non-peer reviewed articles, conference presentations, webinars, and presentations for professionals.

What is this Study about?

This study aims to evaluate the acceptance and usability of the GuardIO Family Care app, a mobile application designed to support community safety for individuals living with dementia or mild cognitive impairment and their care partners. The study also aims to analyze mobility patterns collected from the app to explore how mobility data can contribute to the early detection of cognitive impairment. The findings will help improve app design, inform care strategies, and support early intervention efforts for individuals living with dementia or MCI.

What is this Study about?

The aim of this study is to develop a large, ethically sources, and diverse database of voice recordings to determine whether voice has biomarkers for particular disease categories, including neurological and neurodevelopmental conditions. The data that is collected will be used to develop a full open-access database to fuel artificial intelligence research related to voice.

What is this Study about?

Our study titled "Investigating the Role of Quantitative Susceptibility Mapping and Oxygen Extraction Fraction as Advanced Neuroimaging Biomarkers in Alzheimer's Disease" aims to develop non-invasive diagnostic biomarkers for Alzheimer's Disease (AD). We focus on evaluating the potential of QSM and OEF to differentiate between AD, Mild Cognitive Impairment (MCI), and Cognitively Unimpaired populations and to predict amyloid and tau pathology, using a Systems Biology approach. Leveraging the McGill University's TRIAD cohort, the study utilizes advanced imaging and machine learning to predict amyloid and tau presence, which could transform AD diagnostics and treatment. Methodologically, it involves preprocessing neuroimaging data and employing machine learning classifiers to analyze these features. The anticipated outcomes include validating QSM and OEF as non-invasive biomarkers for AD, establishing their correlation with amyloid and tau proteins, and developing predictive models for clinical decision-making, potentially resulting in significant advancements in AD diagnostics.