Word Repetition in Separate Conversations for Detecting Dementia:A Preliminary Evaluation on Data of Regular Monitoring Service

For detecting early signs of dementia, monitoring technology has been actively investigated due to the low diagnostic coverage as well as the requirement for early intervention. Although language features have been used for detecting the language dysfunctions resulting from dementia in neuropsychological tests, features that can be extracted by regular conversations remain unexplored. Here, we propose a feature to characterize the atypical repetition of words on different days which is observed in patients with dementia. We tested it on data obtained from a daily monitoring service for eight elderly people, including two who had been diagnosed with dementia. We found that our feature outperformed the existing linguistic features used in previous studies, such as vocabulary richness and repetitiveness, in terms of effect size and AUC score. The results suggest that the use of our proposed feature holds promise for improving detection performance in everyday situations such as regular monitoring.