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Speech analysis for acute decompensated heart failure: reporting a pilot study in Germany

delete2026-08-12
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OA
AI
A
Andreas Triantafyllopoulos
W
WM Wolfgang Mayr
A
A. Batliner
L
LL Lana Lempkens
B
BW Björn W. Schuller
T
Thomas M. Berghaus
DOI:10.3389/fdgth.2026.1885715delete
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Abstract

Abstract

En 中文
Acute decompensated heart failure (ADHF) has been shown to affect breathing and speech production. We present a new German speech dataset and conduct a pilot study to show the feasibility of using speech to distinguish between decompensated and recompensated ADHF. We achieve accuracy rates of 77% for this binary classification using read speech; with the use of segmented phrases scoring at 75% and sustained vowels trailing far behind at 52%. Our feature analysis shows a reduction in breathiness and an increase in articulation stability during recompensation. Overall; our results show the promise of speech analysis in the monitoring of ADHF and demonstrate that further efforts should be invested to obtain large-scale data and replicate our results in more heterogeneous populations.
Keywords:
digital health
heart failure
personalization
feature interpretation
pathological speech

Journal

F
Frontiers in Digital Health
IF:
3.8
Papers:
2.0K
Citations:
3.1K

Organization

D
Department of Cardiology
Scholars:
4.2K
Papers: 1.4K
Citations: 8
C
chair of health informatics
Scholars:
5
Papers: 2
Citations: 0
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