How a wrist-worn device may pick up on early signs of Alzheimer’s disease

How a wrist-worn device may pick up on early signs of Alzheimer’s disease

According to research, 22% of adults worldwide who are 50 years of age or older have Alzheimer’s disease at some point. Researchers are working to identify new markers for the early warning signs of this kind of dementia because it is anticipated that the number will rise. Alzheimer’s disease presently has no known cure, but some drugs can help delay the disease’s progression in its early stages.

Most people follow a certain pattern or routine of behaviors, including activity, every day. For instance, some people might move more in the evening and others might be more active in the morning. This is referred to as an individual’s daily activity pattern. A consistently high level of daily activity has been associated in previous research with a better cardiometabolic profile, which may help reduce an individual’s risk of cardiovascular disease. Regular daily activity patterns have also been connected by researchers to enhanced mental and physical health as well as better cognition in older adults. According to a May 2018 study, older men’s daily activity patterns may serve as predictive biomarkers for changes in sleep and cognitive function as well as clinically significant mortality outcomes. An increased mortality risk in older adults was linked to a more fragmented daily activity pattern, according to research published in October 2019.

In this investigation, scientists examined the information generated by an actigraph, a wristwatch-like gadget worn by eighty-two cognitively sound senior citizens who were a part of the long-running Baltimore Longitudinal Study of Aging. Actigraphs worn on the wrist have been the tool of choice for sleep researchers studying older adults’ sleep for decades, as stated. He pointed out that the accelerometer technology is generally the same as that found in widely used, commercial fitness trackers. My coworkers and I submitted an application for a grant from the National Institute on Aging (NIA) to investigate the relationship between Alzheimer’s disease and poor sleep, including the use of wrist actigraphs, because there is mounting evidence that sleep disturbances may raise the risk of the disease. This work is directly related to the grant that we were awarded.

There were discernible levels of the protein beta-amyloidTrusted Source in the brains of 82 research participants, whose average age was 76. Alzheimer’s disease is thought to be characterized by amyloid plaquesTrusted Source. The 25 amyloid-positive and 57 amyloid-negative participant groups differed significantly in terms of average afternoon activity and variability in activity throughout a larger time window, according to the researchers’ analysis of the actigraph device data. In the early afternoon, the scientists found that the average activity was higher in the amyloid-positive group.

Our findings are significant because, according to Dr. Spira, they demonstrated that, among individuals with cognitively normal brains, those with detectable levels of beta-amyloid exhibited distinct patterns of activity at specific times of the day compared to those without the protein. This is a new discovery. According to him, it will be crucial to monitor individuals who display activity patterns similar to those that we connected to the presence of beta-amyloid to determine whether they are more likely to experience cognitive decline in the future. It would be interesting to investigate if these 24-hour patterns can be used to predict the development of beta-amyloid in people without the condition.

In the future, I don’t see the clinical application of wearable recording technology, or “wrist actigraphy,” for the diagnosis of memory loss disorders such as Alzheimer’s dementia. It is common for people to become less active as they age, but other medical conditions like heart disease, neuropathies, or other medical issues are more concerning than dementia. Parkinson’s disease is a neurological movement disorder, and I would love to see this methodology used in its diagnosis.


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