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Torso shape detection to improve lung monitoring
Middlesex Univ, UK.
Middlesex Univ, UK.
Middlesex Univ, UK.
Middlesex Univ, UK.
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2018 (English)In: Physiological Measurement, ISSN 0967-3334, E-ISSN 1361-6579, Vol. 39, no 7, article id 074001Article in journal (Refereed) Published
Abstract [en]

Objective: Newborns with lung immaturity often require continuous monitoring and treatment of their lung ventilation in intensive care units, especially if born preterm. Recent studies indicate that electrical impedance tomography (EIT) is feasible in newborn infants and children, and can quantitatively identify changes in regional lung aeration and ventilation following alterations to respiratory conditions. Information on the patient-specific shape of the torso and its role in minimizing the artefacts in the reconstructed images can improve the accuracy of the clinical parameters obtained from EIT. Currently, only idealized models or those segmented from CT scans are usually adopted. Approach: This study presents and compares two methodologies that can detect the patient-specific torso shape by means of wearable devices based on (1) previously reported bend sensor technology, and (2) a novel approach based on the use of accelerometers. Main results: The reconstruction of different phantoms, taking into account anatomical asymmetries and different sizes, are produced for comparison. Significance: As a result, the accelerometers are more versatile than bend sensors, which cannot be used on bigger cross-sections. The computational study estimates the optimal number of accelerometers required in order to generate an image reconstruction comparable to the use of a CT scan as the forward model. Furthermore, since the patient position is crucial to monitoring lung ventilation, the orientation of the phantoms is automatically detected by the accelerometer-based method.

Place, publisher, year, edition, pages
Institute of Physics Publishing (IOPP), 2018. Vol. 39, no 7, article id 074001
Keywords [en]
shape detection, accelerometers, EIT, reconstruction, orientation
National Category
Biomedical Laboratory Science/Technology
Research subject
Natural Science, Physics
Identifiers
URN: urn:nbn:se:lnu:diva-77008DOI: 10.1088/1361-6579/aacc1cISI: 000437841700001PubMedID: 29894309Scopus ID: 2-s2.0-85051714099OAI: oai:DiVA.org:lnu-77008DiVA, id: diva2:1235770
Available from: 2018-07-27 Created: 2018-07-27 Last updated: 2019-08-29Bibliographically approved

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Nordebo, Sven

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CiteExportLink to record
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