Early detection of Alzheimer’s dementia via smartphone

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Scientists are working on a machine learning (ML) model that could potentially enable early detection of Alzheimer’s dementia using a simple smartphone tool.

This tool would be able to distinguish Alzheimer’s patients from healthy individuals with an accuracy of 70-75%, an encouraging figure considering that more than 747,000 Canadians have Alzheimer’s or some other form of dementia.

problem

Identifying early-stage Alzheimer’s dementia can be challenging because the early symptoms are often subtle and can be mistaken for typical age-related memory impairments.

Traditionally, detecting brain changes indicative of Alzheimer’s has required expensive laboratory work and medical imaging, which are generally not done in the early stages of the disease.

Solution

The machine learning model under development could be integrated into a mobile app, providing a convenient early indicator of possible Alzheimer’s dementia.

Being able to start treatments and interventions earlier could potentially slow disease progression.

Additionally, a mobile screening tool would provide a convenient telehealth solution for those who may have geographic or language barriers in accessing healthcare services.

How it works

The model does not focus on specific words, but examines language-independent acoustic and linguistic features of language.

For example, it is believed that Alzheimer’s patients typically speak more slowly, have more pauses or interruptions, and often have reduced speech intelligibility.

The model can search for these language features, potentially crossing language boundaries and being universally applicable.

Next Steps

The user experience with the developed tool would be straightforward: a person speaks into it, analyzes the speech and predicts whether the person has Alzheimer’s or not.

The resulting information could then be relayed to a doctor for further investigation and action.

The team behind this tool, the Computational Psychiatry Research Group at the University of Alberta, has also developed similar AI models and tools to detect psychiatric disorders such as PTSD, schizophrenia, depression and bipolar disorder.

They believe that any technological advance that can help treat disease earlier and at a lower cost is beneficial.

The team’s machine learning model will be detailed in a paper to be published as part of the ICASSP 2023 Signal Processing Grand Challenge, in which the team placed first in North America and fourth globally.

If you care about the health of your brain, please read studies about it Vitamin D deficiency linked to Alzheimer’s and vascular dementiaAnd Higher magnesium intake could improve brain health.

For more information on brain health, see recent studies on it Antioxidants, which could help reduce the risk of dementiaAnd Coconut oil may help improve cognitive function in Alzheimer’s.

The study was published In ICASSP 2023–2023 IEEE International Conference on Acoustics, Speech and Signal Processing.

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