This can catch the symptoms before it’s too late.
Studies suggest that approximately 22% of individuals aged 50 and above worldwide are afflicted by some stage of Alzheimer’s disease, a statistic that is poised to rise in the coming years. In response to this growing concern, researchers are diligently exploring novel approaches to identify early indicators of this debilitating form of dementia.
While there is currently no cure for Alzheimer’s, medications are available to mitigate its progression, particularly in its initial stages. Recent research conducted at the Johns Hopkins Bloomberg School of Public Health sheds light on a promising avenue for early detection.
Published in the journal SLEEP, the study delves into the potential of monitoring daily activity patterns through a wrist-worn device as a means of identifying early warning signs of Alzheimer’s disease. These patterns, reflective of an individual’s routine behaviors, have previously been associated with various health outcomes, including cardiovascular health and cognitive function.
Utilizing data collected from a cohort of cognitively healthy older adults, researchers examined the correlation between daily activity patterns and the presence of beta-amyloid in the brain, a hallmark of Alzheimer’s disease. Remarkably, significant disparities were observed between participants with detectable beta-amyloid and those without, particularly in terms of afternoon activity levels and daily activity variability.
Dr. Adam Spira, lead author of the study, underscored the significance of these findings, emphasizing their potential implications for identifying individuals at risk of cognitive decline. However, he cautioned against interpreting data from personal devices, emphasizing the need for further research to validate these findings and explore alternative digital biomarkers for Alzheimer’s disease.
While the prospect of utilizing mainstream fitness and activity trackers for early detection holds promise, Dr. Spira stressed the importance of rigorous scientific validation before such applications can be considered feasible. While the journey toward leveraging wearable technology for neurological disorder detection remains ongoing, it represents a promising avenue for future research and innovation in Alzheimer’s disease prevention and management.
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