Automatic analysis of spontaneous speech for detecting Mild Cognitive Impairment: a
screening tool?
1,3#Laura Calzà, *1,4Daniela Beltrami, *2Gloria Gagliardi, 2Rema Rossini Favretti, 2#Fabio Tamburini, 4#Enrico
Ghidoni,
1CIRI-SDV, 2FICLIT and 3FaBit, University of Bologna, Bologna, Italy; 4Arcispedale S. Maria Nuova, Neurology Unit,
Reggio Emilia, Italy
Presenter: Laura Calzà,
CIRI-SDV and FaBit, University of Bologna, Bologna, Italy
Due to increased life expectancy, the prevalence of cognitive decline related to neurodegenerative diseases and to
non-neurological conditions is increasing in western countries. Thus, there is an increasing demand, from both social
and healthcare systems, for instruments and strategies to recognize cognitive decline, and possibly distinguish the
precursor of serious neurodegeneration from “benign senile forgetfulness” or the temporary consequences of
illness or trauma. Moreover, novel approaches for the identification of "preclinical “ or “pre-symptomatic”
Alzheimer’s disease and other dementia are a key issue in the field. Recent studies showed that discourse
alterations may be one of the earliest signs of the pathology, frequently measurable years before other cognitive
deficits become apparent. Traditional neuropsychological tests fail to identify these changes. In contrast, the
analysis of spoken language productions by Natural language processing (NLP) techniques can ecologically pinpoint
language modifications in potential patients. This interdisciplinary study aimed at using NLP to identify early
linguistic signs of cognitive decline in the elderly. Methods: We enrolled 96 subjects (age range 50-75): 48 healthy
controls and 48 impaired subjects: 16 subjects with single domain amnestic Mild Cognitive Impairment (a-MCI), 16
with multiple domain MCI (md-MCI) and 16 with early Dementia (eD). Each subject underwent a brief
neuropsychological screening composed by MMSE, MoCA, GPCog, CDT and verbal fluency (phonemic and semantic).
The spontaneous speech during three tasks (complex picture; a typical working day; the last remembered dream)
was then recorded, transcribed and annotated at various linguistic levels. A multidimensional parameter
computation was performed by a quantitative analysis of spoken texts, computing 67 rhythmic, acoustic, lexical,
morpho-syntactic and syntactic features. Results: Neuropsychological tests showed significant differences between
controls, md-MCI and eD subjects (p=…..), while they didn't differentiate between controls and a-MCI subjects
(p=….). In the linguistic experiments, a number of features regarding lexical (p=…), acoustic (p=…) and syntactic
aspects (p=…) were significant (using the Komolgorov-Smirnov test) in differentiating between all the considered
subject groups. Conclusions: Linguistic features of spontaneous discourse transcribed and analyzed by LNP
techniques show significant differences between controls and pathological states, and seems to be a promising
approach for the identification of preclinical stages of dementia. Long duration follow up studies are needed to
confirm this assumption.
Supported by OPLON, MIUR (L.C.); * these authors equally contributed to the study; # these authors share senior
authorship
What will the audience take away from your presentation?
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Should we screen for cognitive decline and dementia?
Should/could screening for “warning signs” of cognitive be performed in the primary care setting?
Is spontaneous language a biomarker candidate for cognitive decline?
Is this abstract connected to an organized session? If yes, please provide full session title.
No, in reply to an invitation
Biography of presenting author (about 100 words)
Laura Calzà, MD, Endocrinologist
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Professor of Embryology, Regenerative Medicine and Cognitive Sciences at University of Bologna
Director of the Health Sciences and Technologies - Interdepartmental Center for Industrial Research (HST-ICIR),
University of Bologna
President of the Scientific and Technical board of the Montecatone Rehabilitation Institute for spine and brain
injury
Scientific Advisor of the Life Science Platform, High Technology Network, Emilia Romagna Region
Scientific Director of IRET Foundation, Ozzano Emilia, Italy
Founder of TransMed Research srl, Ozzano Emilia, Italy
Scientific interests: neurobiology, with regard to neurodegenerative diseases (focus on Alzheimer disease and
multiple sclerosis) and acute injuries (stroke, spinal cord injury and peripheral nerve injury); stem cells and
nanostructured scaffolds for neural and myelin repair; stem cells for high content screening; dynamic imaging by
confocal laser scan microscopy. Biomarker discovery in neurodegenerative diseases
Scientific publication rank:
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180 papers in peer-reviewed journals
50 chapters in international books
more than 250 abstracts to international meetings
H-index: 35 (Google Scholar)
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Prof. Laura Calzà, MD
+39 335 310979
Italy
invited lecture
not established
[email protected]