المؤلفون: Alexandra König, Elisa Mallick, Johannes Tröger, Nicklas Linz, Radia Zeghari, Valeria Manera, Philippe Robert

المصدر: European Psychiatry, Vol 64 (2021)

مصطلحات موضوعية: apathy, depression, mild neurocognitive disorders, neuropsychiatric symptoms, speech analysis, vocal parameters, Psychiatry, RC435-571

الوصف: 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.

وصف الملف: electronic resource

العلاقة: https://www.cambridge.org/core/product/identifier/S0924933821022367/type/journal_articleTest; https://doaj.org/toc/0924-9338Test; https://doaj.org/toc/1778-3585Test

الوصول الحر: https://doaj.org/article/fc5f4ceb4eeb4332bcf6d70161a6e643Test

المؤلفون: Alexandra, König, Radia, Zeghari, Rachid, Guerchouche, Minh, Duc Tran, François, Bremond, Nicklas, Linz, Hali, Lindsay, Kai, Langel, Inez, Ramakers, Pascale, Lemoine, Vincent, Bultingaire, Philippe, Robert

المساهمون: Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, Spatio-Temporal Activity Recognition Systems (STARS), Inria Sophia Antipolis - Méditerranée (CRISAM), 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), Deutsches Forschungszentrum für Künstliche Intelligenz GmbH = German Research Center for Artificial Intelligence (DFKI), Maastricht University [Maastricht], Centre Hospitalier de Digne Les Bains

المصدر: BMJ Open, 11(9):e047083. BMJ Publishing Group
BMJ Open, Vol 11, Iss 9 (2021)
BMJ Open
BMJ Open, 2021, 11 (9), pp.e047083. ⟨10.1136/bmjopen-2020-047083⟩

مصطلحات موضوعية: MINI-MENTAL-STATE, DIAGNOSIS, VALIDATION, [SCCO]Cognitive science, Cognition, old age psychiatry, Humans, Speech, health informatics, Aged, DECLINE, clinical trials, DEMENTIA, Reproducibility of Results, DEPRESSION, Telemedicine, ALZHEIMERS-DISEASE, Observational Studies as Topic, Mental Health, APATHY, Medicine, Feasibility Studies

الوصف: International audience; Introduction Early detection of cognitive impairments is crucial for the successful implementation of preventive strategies. However, in rural isolated areas or so-called ‘medical deserts’, access to diagnosis and care is very limited. With the current pandemic crisis, now even more than ever, remote solutions such as telemedicine platforms represent great potential and can help to overcome this barrier. Moreover, current advances made in voice and image analysis can help overcome the barrier of physical distance by providing additional information on a patients’ emotional and cognitive state. Therefore, the aim of this study is to evaluate the feasibility and reliability of a videoconference system for remote cognitive testing empowered by automatic speech and video analysis. Methods and analysis 60 participants (aged 55 and older) with and without cognitive impairment will be recruited. A complete neuropsychological assessment including a short clinical interview will be administered in two conditions, once by telemedicine and once by face-to-face. The order of administration procedure will be counterbalanced so half of the sample starts with the videoconference condition and the other half with the face-to-face condition. Acceptability and user experience will be assessed among participants and clinicians in a qualitative and quantitative manner. Speech and video features will be extracted and analysed to obtain additional information on mood and engagement levels. In a subgroup, measurements of stress indicators such as heart rate and skin conductance will be compared. Ethics and dissemination The procedures are not invasive and there are no expected risks or burdens to participants. All participants will be informed that this is an observational study and their consent taken prior to the experiment. Demonstration of the effectiveness of such technology makes it possible to diffuse its use across all rural areas (‘medical deserts’) and thus, to improve the early diagnosis of neurodegenerative pathologies, while providing data crucial for basic research. Results from this study will be published in peer-reviewed journals.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::9b25f5e9d0203121e212f085005224afTest
https://cris.maastrichtuniversity.nl/en/publications/a2e9a2b1-3a41-4424-be22-ff385ce33601Test