An anonymous reader quotes a report from New Atlas: A fascinating new study from a team of US researchers has used machine learning techniques to develop algorithms that can analyze naturalistic driving data and detect mild cognitive impairment and dementia in a driver. The work is still in the preliminary stages, however, the researchers claim it could be possible in the future to detect early signs of dementia using either a smartphone app or devices incorporated into car software systems. The research utilized data from a novel long-term study called LongROAD (The Longitudinal Research on Aging Drivers), which tracked nearly 3,000 older drivers for up to four years, offering a large longitudinal dataset.
Over the course of the LongROAD study, 33 subjects were diagnosed with MCI and 31 with dementia. A series of machine learning models were trained on the LongROAD data, tasked with detecting MCI and dementia from driving behaviors. “Based on variables derived from the naturalistic driving data and basic demographic characteristics, such as age, sex, race/ethnicity and education level, we could predict mild cognitive impairment and dementia with 88 percent accuracy,” says Sharon Di, lead author on the new study. Although age was the number one factor for detecting MCI or dementia, a number of driving variables closely followed. These include, “the percentage of trips traveled within 15 miles (24 km) of home … the length of trips starting and ending at home, minutes per trip, and number of hard braking events with deceleration rates 0.35 g.” Using driving variables alone, the models could still predict those MCI or dementia drivers with 66 percent accuracy. The new study was published in the journal Geriatrics.