OSense: Omni-Directional Heartbeat Sensing With Radio Signal

By analyzing cardiac motion modulated in body reflections, radio signals offer a novel contactless pathway for heartbeat sensing, attracting growing research attention. However, current studies overlooked the unique signal interaction when radio signals are incident at non-normal directions to the torso surface. This missing component significantly limits the effectiveness and results in unreliable performance in practical usage, where normal sensing direction cannot always be guaranteed. In this paper, we aim to answer the questions of what causes this performance degradation and how to solve it. Specifically, we analyze the signal interaction using a fine-grained thoracic motion model and reveal that non-stationary interference, caused by physiologically-driven spatial variation of the body surface, is the key to the problem. Correspondingly, we propose OSense, a framework based on a time-domain optimization method to cancel the non-stationary interference. This framework can be seamlessly integrated into various heartbeat sensing tasks. We validate OSense using a commercial Frequency Modulated Continuous Wave radar across multiple downstream tasks. The results demonstrate that our method effectively eliminates interference and enables direction-robust heartbeat sensing, highlighting its potential for practical cardiac monitoring using radio signals.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-04-08
DOI
https://doi.org/10.1109/jiot.2025.3558733
Citations
3
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
4.16
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article

OSense: Omni-Directional Heartbeat Sensing With Radio Signal

Dongheng Zhang, Yang Hu, Yan Chen, Jinbo Chen et al.
3 citations
IEEE Internet of Things Journal
ECG Monitoring and Analysis
4.16
article

OSense: Omni-Directional Heartbeat Sensing With Radio Signal

Dongheng Zhang, Yang Hu, Yan Chen, Jinbo Chen, Hanqin Gong, Juan Tong, Yadong Li, Guixin Xu
article en
3 citations

Abstract

By analyzing cardiac motion modulated in body reflections, radio signals offer a novel contactless pathway for heartbeat sensing, attracting growing research attention. However, current studies overlooked the unique signal interaction when radio signals are incident at non-normal directions to the torso surface. This missing component significantly limits the effectiveness and results in unreliable performance in practical usage, where normal sensing direction cannot always be guaranteed. In this paper, we aim to answer the questions of what causes this performance degradation and how to solve it. Specifically, we analyze the signal interaction using a fine-grained thoracic motion model and reveal that non-stationary interference, caused by physiologically-driven spatial variation of the body surface, is the key to the problem. Correspondingly, we propose OSense, a framework based on a time-domain optimization method to cancel the non-stationary interference. This framework can be seamlessly integrated into various heartbeat sensing tasks. We validate OSense using a commercial Frequency Modulated Continuous Wave radar across multiple downstream tasks. The results demonstrate that our method effectively eliminates interference and enables direction-robust heartbeat sensing, highlighting its potential for practical cardiac monitoring using radio signals.

IEEE Internet of Things JournalVol. 12(13)
University of Science and Technology of China (CN), University of Washington (US)
Openalex Percentile: Top 6%
ECG Monitoring and Analysis
4.16
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