Beyond Vital Signs: Emotion-Aware Remote Patient Monitoring

Remote Patient Monitoring systems (RPMs) are becoming increasingly important as the aging population struggles to manage chronic illnesses and secure consistent healthcare access. While these systems excel in tracking physical metrics, integrating emotion recognition can bridge the often-overlooked connection between emotional and physical well-being. By identifying emotional responses such as discomfort, distress, or contentment, RPM systems can provide immediate feedback for care adjustments and reveal long-term trends. Subtle shifts in emotional patterns may act as early indicators of mental health conditions linked to chronic diseases or transient emotional stress. Expanding RPMs to include emotion awareness makes care more adaptive and holistic. This review explores how emotion recognition can enhance RPM systems by addressing both physical and emotional health. It examines methods that leverage physiological and behavioral responses to capture emotional states, assessing the advantages, limitations, and applicability of these modalities in RPM settings. By incorporating emotion-aware tools, RPMs have the potential to deliver more comprehensive, responsive, and personalized care, revolutionizing healthcare delivery for diverse patient groups.

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Publication Details

Journal
IEEE Journal of Biomedical and Health Informatics
Published
2025-01-01
DOI
https://doi.org/10.1109/jbhi.2025.3643790
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.00
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article

Beyond Vital Signs: Emotion-Aware Remote Patient Monitoring

Dimitrios Hatzinakos, Muhammad Amjad Ali, Bilal Taha, Deepa Kundur
IEEE Journal of Biomedical and Health Informatics
Emotion and Mood Recognition
article

Beyond Vital Signs: Emotion-Aware Remote Patient Monitoring

Dimitrios Hatzinakos, Muhammad Amjad Ali, Bilal Taha, Deepa Kundur
article en

Abstract

Remote Patient Monitoring systems (RPMs) are becoming increasingly important as the aging population struggles to manage chronic illnesses and secure consistent healthcare access. While these systems excel in tracking physical metrics, integrating emotion recognition can bridge the often-overlooked connection between emotional and physical well-being. By identifying emotional responses such as discomfort, distress, or contentment, RPM systems can provide immediate feedback for care adjustments and reveal long-term trends. Subtle shifts in emotional patterns may act as early indicators of mental health conditions linked to chronic diseases or transient emotional stress. Expanding RPMs to include emotion awareness makes care more adaptive and holistic. This review explores how emotion recognition can enhance RPM systems by addressing both physical and emotional health. It examines methods that leverage physiological and behavioral responses to capture emotional states, assessing the advantages, limitations, and applicability of these modalities in RPM settings. By incorporating emotion-aware tools, RPMs have the potential to deliver more comprehensive, responsive, and personalized care, revolutionizing healthcare delivery for diverse patient groups.

IEEE Journal of Biomedical and Health InformaticsVol. PP
University of Toronto (CA)
Openalex Percentile: Top 56%
Emotion and Mood Recognition
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