The primary objectives are to develop and validate a classifier using multimodal passive sensor data and metrics derived from normal iPhone and Apple Watch usage to distinguish individuals with normal cognition from those with mild cognitive impairment (MCI) and to develop and validate a cognitive wellness score that tracks fluctuations in cognitive performance over time using multimodal passive sensor data and metrics derived from normal iPhone and Apple Watch usage.
Study Type
OBSERVATIONAL
Enrollment
22,720
Virtual App-Based Study
Cambridge, Massachusetts, United States
Sensitivity and Specificity of the Classifier in Distinguishing Between Individuals With and Without MCI
A classifier is a mathematical function that uses collected data to calculate the probability that an individual belongs in a given category. The reference standard for the classifier is clinical diagnosis of MCI in normal clinical care or in a research cohort.
Time frame: Up to Month 23
Correlation Between the Cognitive Wellness Score and the Neuropsychological Testing Battery Score
To develop and validate a cognitive wellness score that tracks fluctuations in cognitive performance over time using multimodal passive sensor data and metrics derived from normal iPhone and Apple Watch usage.
Time frame: Up to Month 23
Sensitivity and Specificity of the Classifier in Predicting Between Individuals Who Do and Do Not Develop MCI
A classifier is a mathematical function that uses collected data to calculate the probability that an individual belongs in a given category. The reference standard for the classifier is clinical diagnosis of MCI in normal clinical care or in a research cohort.
Time frame: Up to Month 23
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