A combined naturalistic driving, clinical, and neurobehavioral data set for investigating aging and dementia - Matthew Blake; David C. Brown; Chen Chen; Noor Al-Hammadi; Ramon Casanova; Yiqi Zhu; Ganesh M. Babulal (Scientific Data)
Abstract Alzheimer’s disease and related dementia (ADRD) are becoming increasingly prevalent and are predicted to affect up to 153 million globally by 2050. Outside of biomarkers that measure pathology, there is a lack of methods to quantify and study complex behaviors such as driving and managing finances that precede cognitive decline among older adults. The DRIVES Project at Washington University School of Medicine has developed a pipeline to measure naturalistic driving behavior of older adult drivers enrolled in longitudinal studies of aging and ADRD. This driving behavior is captured in the form of tabular data for each trip a participant takes and is processed in two formats: low-frequency driving data, comprising approximately 2.8 million trips (37 GB), and high-frequency driving data, with approximately 1.4 million trips (2.6 TB). This pipeline also captures common participant sociodemographic characteristics, clinical features, and environmental context across various weather conditions, as well as the Area Deprivation Index and the Social Vulnerability Index, to comprehensively characterize the multidimensional nature of neurodegenerative processes among older adults.