Continuous Telemonitoring of Heart Failure using Personalised Speech Dynamics

• URL: http://arxiv.org/abs/2602.19674v2
• Date: Wed, 25 Feb 2026 01:57:23 GMT
• Title: Continuous Telemonitoring of Heart Failure using Personalised Speech Dynamics
• Authors: Yue Pan, Xingyao Wang, Hanyue Zhang, Liwei Liu, Changxin Li, Gang Yang, Rong Sheng, Yili Xia, Ming Chu,
• Abstract summary: We propose a Longitudinal Intra-Patient Tracking (LIPT) scheme to capture the trajectory of relative symptomatic changes within individuals.<n>Central to this framework is a Sequential Personalised (PSE) which transforms longitudinal speech recordings into context-aware latent representations.<n> Experimental results from a cohort of 225 patients demonstrate that the LIPT paradigm significantly outperforms the classic cross-sectional approaches.
• Score: 17.682803546212824
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Remote monitoring of heart failure (HF) via speech signals provides a non-invasive and cost-effective solution for long-term patient management. However, substantial inter-individual heterogeneity in vocal characteristics often limits the accuracy of traditional cross-sectional classification models. To address this, we propose a Longitudinal Intra-Patient Tracking (LIPT) scheme designed to capture the trajectory of relative symptomatic changes within individuals. Central to this framework is a Personalised Sequential Encoder (PSE), which transforms longitudinal speech recordings into context-aware latent representations. By incorporating historical data at each timestamp, the PSE facilitates a holistic assessment of the clinical trajectory rather than modelling discrete visits independently. Experimental results from a cohort of 225 patients demonstrate that the LIPT paradigm significantly outperforms the classic cross-sectional approaches, achieving a recognition accuracy of 99.7% for clinical status transitions. The model's high sensitivity was further corroborated by additional follow-up data, confirming its efficacy in predicting HF deterioration and its potential to secure patient safety in remote, home-based settings. Furthermore, this work addresses the gap in existing literature by providing a comprehensive analysis of different speech task designs and acoustic features. Taken together, the superior performance of the LIPT framework and PSE architecture validates their readiness for integration into long-term telemonitoring systems, offering a scalable solution for remote heart failure management.

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