Detecting speech and language changes in early AD via automated analysis of clinical interviews. (31st December 2021)
- Record Type:
- Journal Article
- Title:
- Detecting speech and language changes in early AD via automated analysis of clinical interviews. (31st December 2021)
- Main Title:
- Detecting speech and language changes in early AD via automated analysis of clinical interviews
- Authors:
- Robin, Jessica
Xu, Mengdan
Oday, Abdi
Monteiro, Cecilia
Liu, Kai
Kahn, Laura
Hejrati, Mohsen
Amora, Rainier
Simpson, Bill
Teng, Edmond - Abstract:
- Abstract: Background: Changes to speech and language patterns in Alzheimer's disease (AD) may provide sensitive indicators of cognitive decline that could be automatically and objectively detected with speech analysis technology that incorporates natural language processing. In this study, we sought to determine whether analyses of audio recordings of open‐ended Clinical Dementia Rating (CDR) interviews collected as part of a Phase 2 clinical trial in prodromal‐to‐mild AD could identify speech and language characteristics relevant to clinical status. Method: Speech recordings from baseline CDR interviews were analyzed for 101 English‐speaking AD participants (58F/43M; 30 prodromal/71 mild; mean age = 69 years, range: 53‐80) in the semorinemab (NCT03289143) Phase 2 Tauriel study. Recordings of the CDR interview were analyzed using the Winterlight speech analysis platform, which generates >500 variables describing acoustic and linguistic features of speech. We computed Pearson correlations between the speech variables and five clinical measures (CDR, ADAS‐Cog, RBANS, MMSE, ADCS‐ADL) to identify specific features related to clinical performance. Result: CDR‐SB scores correlated more strongly with linguistic variables (e.g., types of words used, complexity of language) than acoustic variables. Participants with higher CDR‐SB scores (i.e., greater cognitive/functional impairment), used fewer past tense verbs when describing a recent event, a lower proportion of nouns compared toAbstract: Background: Changes to speech and language patterns in Alzheimer's disease (AD) may provide sensitive indicators of cognitive decline that could be automatically and objectively detected with speech analysis technology that incorporates natural language processing. In this study, we sought to determine whether analyses of audio recordings of open‐ended Clinical Dementia Rating (CDR) interviews collected as part of a Phase 2 clinical trial in prodromal‐to‐mild AD could identify speech and language characteristics relevant to clinical status. Method: Speech recordings from baseline CDR interviews were analyzed for 101 English‐speaking AD participants (58F/43M; 30 prodromal/71 mild; mean age = 69 years, range: 53‐80) in the semorinemab (NCT03289143) Phase 2 Tauriel study. Recordings of the CDR interview were analyzed using the Winterlight speech analysis platform, which generates >500 variables describing acoustic and linguistic features of speech. We computed Pearson correlations between the speech variables and five clinical measures (CDR, ADAS‐Cog, RBANS, MMSE, ADCS‐ADL) to identify specific features related to clinical performance. Result: CDR‐SB scores correlated more strongly with linguistic variables (e.g., types of words used, complexity of language) than acoustic variables. Participants with higher CDR‐SB scores (i.e., greater cognitive/functional impairment), used fewer past tense verbs when describing a recent event, a lower proportion of nouns compared to verbs, and shorter and simpler grammatical clauses (all r's > 0.3, p's < 0.05, FDR‐corrected). Similar associations were seen with other clinical assessments, and a subset of linguistic variables demonstrated significant (p < 0.05, uncorrected) correlations with all five clinical measures, including clause length, and use of prepositional phrases. Conclusion: These analyses demonstrate that clinical interviews can be analyzed using objective automatic methods to generate speech variables relevant to clinical outcomes in AD. Individuals with greater cognitive and functional impairment used simpler language and fewer content words when describing a recent experience. Future work will include multivariate analyses of speech markers versus cross‐sectional clinical indices. … (more)
- Is Part Of:
- Alzheimer's & dementia. Volume 17(2021)Supplement 6
- Journal:
- Alzheimer's & dementia
- Issue:
- Volume 17(2021)Supplement 6
- Issue Display:
- Volume 17, Issue 6 (2021)
- Year:
- 2021
- Volume:
- 17
- Issue:
- 6
- Issue Sort Value:
- 2021-0017-0006-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2021-12-31
- Subjects:
- Alzheimer's disease -- Periodicals
Alzheimer Disease -- Periodicals
Dementia -- Periodicals
Démence
Maladie d'Alzheimer
Périodique électronique (Descripteur de forme)
Ressource Internet (Descripteur de forme)
616.83 - Journal URLs:
- http://www.sciencedirect.com/science/journal/15525260 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1002/alz.052352 ↗
- Languages:
- English
- ISSNs:
- 1552-5260
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0806.255333
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