Abstract
Postural stability, hearing, and gait function deterioration are the risk factors associated with cognitive impairment. Although no method has been reported for treating severe cognitive impairment to date, developing an early detection model based on these risk factors could aid in slowing down or even reversing the deterioration process. In this study, the association between cognitive impairment and the combined predictive ability of sensory and gait features was assessed. Fifty-seven healthy community-dwelling men over the age of sixty-five participated in cognitive, postural stability, auditory, and level walking evaluations. They were divided into two groups: healthy control group (n = 39) and lower cognition group (n = 18), based on their Montreal cognitive assessment score. During gait, the center of mass of the cognitively impaired participants was confined to a smaller volume. Furthermore, the cognitively healthy participants were found to have better postural stability. Both groups possessed similar hearing ability; however, the cognitively impaired group made a significantly higher number of errors when repeating words or sentences. A logistic regression model utilizing each of these function quantifiers exhibited a high area under the receiver operating characteristic curve, suggesting excellent predictive ability. These models can be applied to smartphone or smart home healthcare technologies to detect the possibility of cognitive impairment, thus facilitating early detection.
Funder
National Research Foundation of Korea (NRF) grant funded by the Korea government
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science