Publication: Respiration monitoring based on frequency difference electrical impedance tomography in conditions with body movement artifacts
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Issued Date
2025-12-01
Resource Type
ISSN
02632241
Scopus ID
2-s2.0-105010139419
Journal Title
Measurement Journal of the International Measurement Confederation
Volume
256
Rights Holder(s)
SCOPUS
Bibliographic Citation
Measurement Journal of the International Measurement Confederation Vol.256 (2025)
Suggested Citation
Laor-Iam P., Phisaiphan A., Buathong P., Aramphianlert W., Sukjamsri C., Ouypornkochagorn T. Respiration monitoring based on frequency difference electrical impedance tomography in conditions with body movement artifacts. Measurement Journal of the International Measurement Confederation Vol.256 (2025). doi:10.1016/j.measurement.2025.118364 Retrieved from: https://hdl.handle.net/20.500.14740/21180
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Abstract
Electrical Impedance Tomography (EIT) is an imaging technique that provides information on conductivity change within a measurement boundary and has been used for respiration monitoring. Typically, EIT for lung applications relies on a single excitation frequency, and the reconstruction process requires the difference of two sets of signals obtained at different time points. However, in situations where movement artifacts are present, reconstruction may be affected, potentially leading to failure. In this study, frequency difference EIT (fdEIT) was employed and adapted into a time-based approach, referred to as “time–frequency difference EIT” (tfdEIT). Because fdEIT relies on signal difference at the same time point, it can reduce the impact of movement artifacts. Phantom and human experiments were conducted with six participants. In the human experiments, movement artifacts were intentionally introduced by asking the participants to ride a training bicycle while measurements were taken before and during riding. The results showed that both traditional EIT and tfdEIT could successfully image respiration activity before riding. However, during riding, traditional EIT achieved only 33–66 %, whereas tfdEIT reached 100 %. Furthermore, the total conductivity obtained from tfdEIT reflected the change, and when compared with respiration signals, the correlation coefficient improved by 12–25 % over tdEIT (r > 0.82). Additionally, a masking method using an fdEIT image of the full inhalation period is proposed to overlay images providing extra information on lung regions.