A new study published in PLOS Digital Health highlights how smartphone navigation data could serve as a tool to identify individuals at risk of developing dementia. Researchers found that older adults with subjective cognitive decline—a condition linked to an increased risk of Alzheimer’s disease—exhibited distinct patterns of movement during a real-world wayfinding task. Specifically, the frequency of “orientation stops,” or pauses to reorient while navigating, effectively distinguished these individuals from cognitively healthy older adults.
Dementia, including Alzheimer’s disease, is a growing public health crisis, with cases expected to triple globally by 2050. Early diagnosis is critical for implementing interventions that could slow the disease’s progression. However, current diagnostic tools often fail to detect cognitive decline in its earliest stages, particularly when standard memory tests appear normal.
Advances in mobile technology provide a promising avenue for addressing this gap. Smartphones can collect real-world behavioral data unobtrusively, offering insights into cognitive functioning in everyday scenarios. The researchers aimed to harness these capabilities to explore whether smartphone navigation data could reveal subtle cognitive changes in individuals with subjective cognitive decline.
“We were interested in this topic because dementia prevalence is expected to increase in the future and as a result impose significant challenges on healthcare systems,” said study author Jonas Marquardt, a PhD candidate at the German Center for Neurodegenerative Diseases.
“Therefore, early detection of cognitive decline is critical for timely intervention in dementia, with Alzheimer’s disease being the most common form. We aimed to combine advances in smartphone technology to assess the earliest deficits in a real-world scenario with a spatial navigation task, one of the cognitive skills to decline first in the course of Alzheimer’s disease, thereby bridging the gap between lab-based neuropsychological assessments and the tasks of daily life.”
The study involved 72 participants divided into three groups: 24 younger adults, 25 cognitively healthy older adults, and 23 individuals with subjective cognitive decline. Participants were asked to navigate a university campus using a specially developed smartphone app called “Explore.” The app guided them to five locations by showing a map with their position and the destination marked. Once participants started walking, the map disappeared, and they relied on memory and spatial navigation skills to find their way. Participants could revisit the map if they felt lost and had to scan a QR code at each destination to confirm their arrival.
The app collected GPS data every two seconds during the task, tracking participants’ routes, time spent navigating, and any instances of pausing or rechecking the map. Researchers analyzed these data to identify patterns in movement and navigation behavior.
The researchers observed clear differences in navigation behavior across the three groups. Younger adults performed best, completing tasks more quickly and efficiently, with fewer pauses or map checks. Cognitively healthy older adults and those with subjective cognitive decline exhibited slower performance, but the latter group stood out for making significantly more orientation stops—brief pauses likely linked to cognitive challenges in processing their surroundings.
“We were a bit surprised that the strongest difference between the group of older adults with elevated dementia risk and the one without risk was found in the number of short stops, presumably taken to orient themselves,” Marquardt told PsyPost. “It is hard to completely explain what this performance measure captures, but we assume the number of short stops is indicative of navigation abilities and executive function, as we have seen associations with other tasks related to executive function as well as an increased probability of stopping at intersections, presumably to recall and plan the correct path.”
Statistical analysis confirmed that the number of orientation stops was a strong predictor of subjective cognitive decline. When used in a predictive model, this measure correctly identified individuals with subjective cognitive decline in about 67% of cases, a level of accuracy comparable to more resource-intensive virtual reality-based navigation studies.
“The key takeaway is that subtle changes in everyday behavior, such as the number of orientation stops in our task, which may go unnoticed in everyday life, can provide meaningful information about an individual’s cognitive health and dementia risk,” Marquardt explained. “Moreover, these differences might be detectable before deficits in conventional neuropsychological tests are present, thus allowing earlier diagnosis.”
Interestingly, the total distance traveled and average walking speed did not significantly differ between the older adult groups, suggesting that orientation stops specifically reflect cognitive, rather than physical, impairments. This finding aligns with prior research linking orientation difficulties to early changes in brain regions affected by Alzheimer’s disease.
“One major caveat is that we focused on a group of older adults with subjective cognitive decline, which we used as a model for higher dementia risk,” Marquardt noted. “However, subjective cognitive decline is highly heterogeneous group; while some individuals with subjective cognitive decline will progress to dementia, others may remain cognitively healthy. Using genetic markers, such as APOE status, biomarkers like tau or amyloid, or neuroimaging data, would have provided a more precise characterization of our older participants. Additionally, collection of longitudinal data instead of cross-sectional data could further strengthen our predictive capabilities.”
Despite these limitations, the research suggests that smartphone-based tasks could aid in the early detection and monitoring of cognitive decline, potentially transforming how Alzheimer’s disease is diagnosed and managed.
“Our long-term goal is to validate smartphone-based approaches using real-world data for early detection of dementia across broader populations,” Marquardt said. “We aim to develop tools that can be easily integrated into everyday life. In doing so, this would enable individuals and healthcare providers to monitor cognitive health proactively and independently. Ultimately, we hope this research will help with the earlier diagnosis of dementia and allow better deployment of intervention strategies.”
“This study was funded by an DZNE Innovation 2 Application Award (awarded to Nadine Diersch) and by a collaborative research grant (DFG, German Research Foundation – Project-ID 425899996). The collaborative research center emphasizes the value of interdisciplinary collaboration, as demonstrated in this study through the combination of neuroscience, digital health, and real-world applications. We believe such interdisciplinary approaches can revolutionize how we understand, detect, and treat neurodegenerative diseases.”
The study, “Identifying older adults at risk for dementia based on smartphone data obtained during a wayfinding task in the real world,” was authored by Jonas Marquardt, Priyanka Mohan, Myra Spiliopoulou, Wenzel Glanz, Michaela Butryn, Esther Kuehn, Stefanie Schreiber, Anne Maass, and Nadine Diersch.
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