Measuring neuropsychiatric symptoms in patients with early cognitive decline using speech analysis
| العنوان: | Measuring neuropsychiatric symptoms in patients with early cognitive decline using speech analysis |
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| المؤلفون: | König, Alexandra, Mallick, Elisa, Tröger, Johannes, Linz, Nicklas, Zeghari, Radia, Manera, Valeria, Robert, Philippe |
| المساهمون: | Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria), Spatio-Temporal Activity Recognition Systems (STARS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Cognition Behaviour Technology (CobTek), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre Hospitalier Universitaire de Nice (CHU Nice)-Institut Claude Pompidou [Nice] (ICP - Nice)-Université Côte d'Azur (UCA), ki:elements [Saarbrücken], ANR-15-IDEX-0001,UCA JEDI,Idex UCA JEDI(2015) |
| المصدر: | European Psychiatry European Psychiatry, Cambridge University press, 2021, 64 (1), ⟨10.1192/j.eurpsy.2021.2236⟩ European Psychiatry, 2021, 64 (1), pp.e64. ⟨10.1192/j.eurpsy.2021.2236⟩ |
| بيانات النشر: | Cambridge University Press, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Male, vocal parameters, [SCCO.NEUR]Cognitive science/Neuroscience, Apathy, speech analysis, mild neurocognitive disorders, Anxiety, Neuropsychological Tests, Machine Learning, depression, Humans, Speech, neuropsychiatric symptoms, Cognitive Dysfunction, Female, Research Article, Aged |
| الوصف: | International audience; Abstract Background Certain neuropsychiatric symptoms (NPS), namely apathy, depression, and anxiety demonstrated great value in predicting dementia progression, representing eventually an opportunity window for timely diagnosis and treatment. However, sensitive and objective markers of these symptoms are still missing. Therefore, the present study aims to investigate the association between automatically extracted speech features and NPS in patients with mild neurocognitive disorders. Methods Speech of 141 patients aged 65 or older with neurocognitive disorder was recorded while performing two short narrative speech tasks. NPS were assessed by the neuropsychiatric inventory. Paralinguistic markers relating to prosodic, formant, source, and temporal qualities of speech were automatically extracted, correlated with NPS. Machine learning experiments were carried out to validate the diagnostic power of extracted markers. Results Different speech variables are associated with specific NPS; apathy correlates with temporal aspects, and anxiety with voice quality—and this was mostly consistent between male and female after correction for cognitive impairment. Machine learning regressors are able to extract information from speech features and perform above baseline in predicting anxiety, apathy, and depression scores. Conclusions Different NPS seem to be characterized by distinct speech features, which are easily extractable automatically from short vocal tasks. These findings support the use of speech analysis for detecting subtypes of NPS in patients with cognitive impairment. This could have great implications for the design of future clinical trials as this cost-effective method could allow more continuous and even remote monitoring of symptoms. |
| اللغة: | English |
| تدمد: | 1778-3585 0924-9338 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::1dab590f56ebbf8d57cfd98a1d04d7a5Test http://europepmc.org/articles/PMC8581700Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.pmid.dedup....1dab590f56ebbf8d57cfd98a1d04d7a5 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 17783585 09249338 |
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