Locating nidi for high-frequency chest wall oscillation smart therapy via acoustic imaging of lung airways as a spatial network

Lee, C. S., Lou, Y., Li, M., Abbasi, Q. H. and Imran, M. (2023) Locating nidi for high-frequency chest wall oscillation smart therapy via acoustic imaging of lung airways as a spatial network. IEEE Access, 11, pp. 109408-109421. (doi: 10.1109/ACCESS.2023.3317443)

Abstract

High-frequency chest wall oscillation (HFCWO) therapy is one of the techniques to facilitate the draining of a patient’s lung secretion in pathological situations, and smart therapy with HFCWO devices equipped with multiple actuators can be achieved via locating nidi in the lung. In this paper, through developing a novel acoustic lung spatial model and utilizing acoustic imaging simulation, a new and effective method for assessing lung function with acoustic imaging is presented, which links acoustic lung images with pathologic changes. The structural similarity between the acoustic reference image based on actual lung sound and our model acoustic image based on the airway impedance was achieved by an index of 0.8987, with 1 as the exact score. Simulation studies based on the model are used to analyze the practicality and the extreme design of the acoustic imaging system on the resolution of the located nidus. For instance, a practical system design with sensor numbers between 4 and 35 may recognize a lower resolution nidus length of 73 mm to a better resolution nidus length of 22 mm. On the other hand, an extreme system design with more than 1000 sensors can recognize greater nidus resolution at under 10 mm. Additionally, this research may be utilized to offer recommendations for acoustic imaging system design and assess the number of sensors and sensing diameter in current acoustic imaging systems. Furthermore, the geographic detection of nidus length allows for analyzing of HFCWO therapy results.

• Item Type: Articles
• Additional Information: Funding Agency: 10.13039/501100001446-Singapore Economic Development Board (EDB) and provides sponsorship to a PhD program in Singapore.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad and Lee, Chang Sheng and Abbasi, Professor Qammer
• Authors: Lee, C. S., Lou, Y., Li, M., Abbasi, Q. H., and Imran, M.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity; College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: IEEE Access
• Publisher: Institute of Electrical and Electronics Engineers
• ISSN: 2169-3536
• ISSN (Online): 2169-3536
• Published Online: 20 September 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in IEEE Access 11: 109408-109421
• Publisher Policy: Reproduced under a Creative Commons licence