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NeuraMind: Decoding brain signals for the detection of Frontotemporal Dementia and Alzheimer’s disease with non-invasive Electroencephalography and Artificial Intelligence

The development and deployment of dementia and Alzheimer's detection models can contribute significantly to promoting an active and independent life for people living with disabilities in both the short and long term.

Detection models can identify the early signs and risk factors associated with dementia and Alzheimer's disease. Early diagnosis allows for timely intervention, which can include lifestyle changes, medications, and cognitive training. These interventions can help slow down the progression of the disease and maintain cognitive function in the short term.

Detecting dementia or Alzheimer's early enables healthcare professionals to create personalized treatment plans. These plans can include medication management, therapy, and support services, all of which are crucial for managing the condition and addressing immediate needs.

Knowing the condition early on allows individuals and their families to make necessary adjustments in daily life, such as safety measures, support services, and legal and financial planning. These adaptations can improve the quality of life for both the affected individual and their caregivers.

With early detection and appropriate interventions, individuals with dementia or Alzheimer's can learn coping strategies, engage in cognitive exercises, and adapt their living environments to maximize their independence for as long as possible.

Continued use and analysis of data from detection models contribute to ongoing research into these conditions. This research can lead to the development of new treatments, interventions, and technologies that further enhance the long-term quality of life for those living with dementia and Alzheimer's.

On the long term, such systems might become an essential part of policy and healthcare planning.

Project leader: Rajkumar Saini

Funded by: Promobilia External link, opens in new window.