Measuring neuropsychiatric symptoms in early dementia patients using speech analysis
Introduction 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 st...
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2022-06-01
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| Series: | European Psychiatry |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S0924933822004618/type/journal_article |
| _version_ | 1797616537217007616 |
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| author | A. König E. Mallick N. Linz R. Zegahri V. Manera P. Robert |
| author_facet | A. König E. Mallick N. Linz R. Zegahri V. Manera P. Robert |
| author_sort | A. König |
| collection | DOAJ |
| description |
Introduction
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.
Objectives
To investigate the association between automatically extracted speech features and NPS in early-stage dementia patients.
Methods
Speech of 141 patients aged 65 or older with neurocognitive disorder was recorded while performing two short narrative speech tasks. Presence of NPS was 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 seem to be associated with specific neuropsychiatric symptoms of dementia; apathy correlates with temporal aspects, 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 in turn were easily extractable automatically from short vocal tasks. These findings support the use of speech analysis for detecting subtypes of NPS. This could have great implications for future clinical trials.
Disclosure
No significant relationships.
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| first_indexed | 2024-03-11T07:42:37Z |
| format | Article |
| id | doaj.art-e1abc50f5c38431e8793acc0f6d7eb39 |
| institution | Directory Open Access Journal |
| issn | 0924-9338 1778-3585 |
| language | English |
| last_indexed | 2024-03-11T07:42:37Z |
| publishDate | 2022-06-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | European Psychiatry |
| spelling | doaj.art-e1abc50f5c38431e8793acc0f6d7eb392023-11-17T05:08:18ZengCambridge University PressEuropean Psychiatry0924-93381778-35852022-06-0165S174S17410.1192/j.eurpsy.2022.461Measuring neuropsychiatric symptoms in early dementia patients using speech analysisA. König0E. Mallick1N. Linz2R. Zegahri3V. Manera4P. Robert5Institut national de recherche en informatique et en automatique (INRIA), Stars Team, Nice, Franceki:elements, Ug, Saarbrücken, Germanyki:elements, Ug, Saarbrücken, GermanyFRIS-University Côte d’azur, Cobtek (cognition-behaviour-technology) Lab, Nice, FranceFRIS-University Côte d’azur, Cobtek (cognition-behaviour-technology) Lab, Nice, FranceFRIS-University Côte d’azur, Cobtek (cognition-behaviour-technology) Lab, Nice, France Introduction 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. Objectives To investigate the association between automatically extracted speech features and NPS in early-stage dementia patients. Methods Speech of 141 patients aged 65 or older with neurocognitive disorder was recorded while performing two short narrative speech tasks. Presence of NPS was 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 seem to be associated with specific neuropsychiatric symptoms of dementia; apathy correlates with temporal aspects, 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 in turn were easily extractable automatically from short vocal tasks. These findings support the use of speech analysis for detecting subtypes of NPS. This could have great implications for future clinical trials. Disclosure No significant relationships. https://www.cambridge.org/core/product/identifier/S0924933822004618/type/journal_articleNeuropsychiatric symptomsDepressionapathyspeech analysis |
| spellingShingle | A. König E. Mallick N. Linz R. Zegahri V. Manera P. Robert Measuring neuropsychiatric symptoms in early dementia patients using speech analysis European Psychiatry Neuropsychiatric symptoms Depression apathy speech analysis |
| title | Measuring neuropsychiatric symptoms in early dementia patients using speech analysis |
| title_full | Measuring neuropsychiatric symptoms in early dementia patients using speech analysis |
| title_fullStr | Measuring neuropsychiatric symptoms in early dementia patients using speech analysis |
| title_full_unstemmed | Measuring neuropsychiatric symptoms in early dementia patients using speech analysis |
| title_short | Measuring neuropsychiatric symptoms in early dementia patients using speech analysis |
| title_sort | measuring neuropsychiatric symptoms in early dementia patients using speech analysis |
| topic | Neuropsychiatric symptoms Depression apathy speech analysis |
| url | https://www.cambridge.org/core/product/identifier/S0924933822004618/type/journal_article |
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