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Acoustic features from speech as markers of depressive and manic symptoms in bipolar disorder: A prospective study.

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Title: Acoustic features from speech as markers of depressive and manic symptoms in bipolar disorder: A prospective study.
Authors: Kaczmarek‐Majer, Katarzyna (AUTHOR), Dominiak, Monika (AUTHOR), Antosik, Anna Z. (AUTHOR), Hryniewicz, Olgierd (AUTHOR), Kamińska, Olga (AUTHOR), Opara, Karol (AUTHOR), Owsiński, Jan (AUTHOR), Radziszewska, Weronika (AUTHOR), Sochacka, Małgorzata (AUTHOR), Święcicki, Łukasz (AUTHOR)
Source: Acta Psychiatrica Scandinavica. Mar2025, Vol. 151 Issue 3, p358-374. 17p.
Subjects: Hamilton Depression Inventory, Voice analysis, Bipolar disorder, Physiology, Depression in men
Abstract: Introduction: Voice features could be a sensitive marker of affective state in bipolar disorder (BD). Smartphone apps offer an excellent opportunity to collect voice data in the natural setting and become a useful tool in phase prediction in BD. Aims of the Study: We investigate the relations between the symptoms of BD, evaluated by psychiatrists, and patients' voice characteristics. A smartphone app extracted acoustic parameters from the daily phone calls of n = 51 patients. We show how the prosodic, spectral, and voice quality features correlate with clinically assessed affective states and explore their usefulness in predicting the BD phase. Methods: A smartphone app (BDmon) was developed to collect the voice signal and extract its physical features. BD patients used the application on average for 208 days. Psychiatrists assessed the severity of BD symptoms using the Hamilton depression rating scale −17 and the Young Mania rating scale. We analyze the relations between acoustic features of speech and patients' mental states using linear generalized mixed‐effect models. Results: The prosodic, spectral, and voice quality parameters, are valid markers in assessing the severity of manic and depressive symptoms. The accuracy of the predictive generalized mixed‐effect model is 70.9%–71.4%. Significant differences in the effect sizes and directions are observed between female and male subgroups. The greater the severity of mania in males, the louder (β = 1.6) and higher the tone of voice (β = 0.71), more clearly (β = 1.35), and more sharply they speak (β = 0.95), and their conversations are longer (β = 1.64). For females, the observations are either exactly the opposite—the greater the severity of mania, the quieter (β = −0.27) and lower the tone of voice (β = −0.21) and less clearly (β = −0.25) they speak — or no correlations are found (length of speech). On the other hand, the greater the severity of bipolar depression in males, the quieter (β = −1.07) and less clearly they speak (β = −1.00). In females, no distinct correlations between the severity of depressive symptoms and the change in voice parameters are found. Conclusions: Speech analysis provides physiological markers of affective symptoms in BD and acoustic features extracted from speech are effective in predicting BD phases. This could personalize monitoring and care for BD patients, helping to decide whether a specialist should be consulted. [ABSTRACT FROM AUTHOR]
Copyright of Acta Psychiatrica Scandinavica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Acoustic features from speech as markers of depressive and manic symptoms in bipolar disorder: A prospective study.
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  Data: <searchLink fieldCode="AR" term="%22Kaczmarek‐Majer%2C+Katarzyna%22">Kaczmarek‐Majer, Katarzyna</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dominiak%2C+Monika%22">Dominiak, Monika</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Antosik%2C+Anna+Z%2E%22">Antosik, Anna Z.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hryniewicz%2C+Olgierd%22">Hryniewicz, Olgierd</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kamińska%2C+Olga%22">Kamińska, Olga</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Opara%2C+Karol%22">Opara, Karol</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Owsiński%2C+Jan%22">Owsiński, Jan</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Radziszewska%2C+Weronika%22">Radziszewska, Weronika</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sochacka%2C+Małgorzata%22">Sochacka, Małgorzata</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Święcicki%2C+Łukasz%22">Święcicki, Łukasz</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Acta+Psychiatrica+Scandinavica%22">Acta Psychiatrica Scandinavica</searchLink>. Mar2025, Vol. 151 Issue 3, p358-374. 17p.
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  Data: <searchLink fieldCode="DE" term="%22Hamilton+Depression+Inventory%22">Hamilton Depression Inventory</searchLink><br /><searchLink fieldCode="DE" term="%22Voice+analysis%22">Voice analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Bipolar+disorder%22">Bipolar disorder</searchLink><br /><searchLink fieldCode="DE" term="%22Physiology%22">Physiology</searchLink><br /><searchLink fieldCode="DE" term="%22Depression+in+men%22">Depression in men</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Introduction: Voice features could be a sensitive marker of affective state in bipolar disorder (BD). Smartphone apps offer an excellent opportunity to collect voice data in the natural setting and become a useful tool in phase prediction in BD. Aims of the Study: We investigate the relations between the symptoms of BD, evaluated by psychiatrists, and patients' voice characteristics. A smartphone app extracted acoustic parameters from the daily phone calls of n = 51 patients. We show how the prosodic, spectral, and voice quality features correlate with clinically assessed affective states and explore their usefulness in predicting the BD phase. Methods: A smartphone app (BDmon) was developed to collect the voice signal and extract its physical features. BD patients used the application on average for 208 days. Psychiatrists assessed the severity of BD symptoms using the Hamilton depression rating scale −17 and the Young Mania rating scale. We analyze the relations between acoustic features of speech and patients' mental states using linear generalized mixed‐effect models. Results: The prosodic, spectral, and voice quality parameters, are valid markers in assessing the severity of manic and depressive symptoms. The accuracy of the predictive generalized mixed‐effect model is 70.9%–71.4%. Significant differences in the effect sizes and directions are observed between female and male subgroups. The greater the severity of mania in males, the louder (β = 1.6) and higher the tone of voice (β = 0.71), more clearly (β = 1.35), and more sharply they speak (β = 0.95), and their conversations are longer (β = 1.64). For females, the observations are either exactly the opposite—the greater the severity of mania, the quieter (β = −0.27) and lower the tone of voice (β = −0.21) and less clearly (β = −0.25) they speak — or no correlations are found (length of speech). On the other hand, the greater the severity of bipolar depression in males, the quieter (β = −1.07) and less clearly they speak (β = −1.00). In females, no distinct correlations between the severity of depressive symptoms and the change in voice parameters are found. Conclusions: Speech analysis provides physiological markers of affective symptoms in BD and acoustic features extracted from speech are effective in predicting BD phases. This could personalize monitoring and care for BD patients, helping to decide whether a specialist should be consulted. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Acta Psychiatrica Scandinavica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/acps.13735
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        Text: English
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              Text: Mar2025
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