ArticleSensors (Basel, Switzerland)2015
Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.
Article in Sensors (Basel, Switzerland), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Experimental Validation of a Compact and Versatile Bioimpedance Measurement Platform Based on the SENSIPLUS Chip.Sensors (Basel, Switzerland) · 2026Article
- Applications of bioimpedance measurement in clinical and allied fields: a comprehensive review.Biomedical engineering online · 2026Review
- Development of a wearable belt with integrated sensors for measuring multiple physiological parameters related to heart failure.Scientific reports · 2022Article
- Sensors for Context-Aware Smart Healthcare: A Security Perspective.Sensors (Basel, Switzerland) · 2021Review
- Respiration Monitoring via Forcecardiography Sensors.Sensors (Basel, Switzerland) · 2021Article
- Application of Modern Multi-Sensor Holter in Diagnosis and Treatment.Sensors (Basel, Switzerland) · 2020Review
- Human Vital Signs Detection Methods and Potential Using Radars: A Review.Sensors (Basel, Switzerland) · 2020Review
- Contact-Based Methods for Measuring Respiratory Rate.Sensors (Basel, Switzerland) · 2019Review
- Ultrasound Sensors for Diaphragm Motion Tracking: An Application in Non-Invasive Respiratory Monitoring.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method.
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Registered trials
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