# Computerized assessment of linguistic indicators of lucidity in Alzheimer's Disease dementia

> **NIH NIH R21** · UNIVERSITY OF MINNESOTA · 2020 · $442,641

## Abstract

The focus of the proposed project is to enable automated detection and analysis of episodes of unexpected
lucidity in individuals with late-stage dementia in which the individual long thought to have succumbed to
dementia and lost most of his or her cognitive abilities temporarily regains the ability to communicate in a clear
and coherent fashion. Currently, the evidence for the existence of these episodes is mostly anecdotal, stemming
from reports by caregivers and healthcare professionals. According to these reports, clear speech and language
are the most prominent features of episodes of cognitive lucidity. The very low frequency and unexpected nature
of these episodes make it challenging to capture objective evidence in the form of audio or video recordings of
these events needed to enable systematic and comprehensive investigations. Thus, it is necessary to develop
technological solutions for automated linguistic analysis that can be used for long-term continuous monitoring of
individuals in late stages of dementia. In this feasibility project, we will develop technology to address two
challenging issues: a) accurate conversion of continuous speech to text, and b) automated analysis of the text
to measure the degree of coherence. Without robust solutions for these problems, our ability to detect and fully
capture and analyze coherent speech in a long-term monitoring setting will remain limited. We will address these
problems by developing and testing a robust automatic speech recognition solution based on deep learning
technology that can operate autonomously (without sending data to external servers). We will also adapt existing
and develop new measures of semantic coherence that are able to work on imperfect transcripts resulting from
automatic speech recognition. In order to develop and validate these tools and approaches, we will use existing
datasets of spontaneous conversational speech by persons with mild and moderate dementia as well as healthy
controls available as part of the Carolina Conversations Collection and Dementia Bank.

## Key facts

- **NIH application ID:** 10093304
- **Project number:** 1R21AG069792-01
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Trevor Cohen
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $442,641
- **Award type:** 1
- **Project period:** 2020-09-15 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10093304

## Citation

> US National Institutes of Health, RePORTER application 10093304, Computerized assessment of linguistic indicators of lucidity in Alzheimer's Disease dementia (1R21AG069792-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10093304. Licensed CC0.

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