Identification and analysis of stable breathing periods in electrical impedance tomography recordings

Abstract

Objective. In this paper, an automated stable tidal breathing period (STBP) identification method based on processing electrical impedance tomography (EIT) waveforms is proposed and the possibility of detecting and identifying such periods using EIT waveforms is analyzed. In wearable chest EIT, patients breathe spontaneously, and therefore, their breathing pattern might not be stable. Since most of the EIT feature extraction methods are applied to STBPs, this renders their automatic identification of central importance. Approach. The EIT frame sequence is reconstructed from the raw EIT recordings and the raw global impedance waveform (GIW) is computed. Next, the respiratory component of the raw GIW is extracted and processed for the automatic respiratory cycle (breath) extraction and their subsequent grouping into STBPs. Main results. We suggest three criteria for the identification of STBPs, namely, the coefficient of variation of (i) breath tidal volume, (ii) breath duration and (iii) end-expiratory impedance. The total number of true STBPs identified by the proposed method was 294 out of 318 identified by the expert corresponding to accuracy over 90%. Specific activities such as speaking, eating and arm elevation are identified as sources of false positives and their discrimination is discussed. Significance. Simple and computationally efficient STBP detection and identification is a highly desirable component in the EIT processing pipeline. Our study implies that it is feasible, however, the determination of its limits is necessary in order to consider the implementation of more advanced and computationally demanding approaches such as deep learning and fusion with data from other wearable sensors such as accelerometers and microphones.

Distribution of regional lung function in upright healthy subjects determined by electrical impedance tomography in two chest examination planes

“…This finding has some practical implications regarding the interpretation of the EIT studies performed in the past and the planning of EIT applications in the future. In most of the EIT studies carried out in upright human subjects so far, the EIT electrodes were located below the nipples (Coulombe et al 2005, Zhao et al et al 2013, Vogt et al 2019, Milne et al 2019, Haris et al 2021, i.e. in a plane rather corresponding to the caudal plane in the present study.…”

Sex differences in chest electrical impedance tomography findings

“…This is relevant with regard to both the past and future studies involving humans. A very large portion of older chest EIT studies used to place the EIT electrodes below the breasts (Coulombe et al 2005, Zhao et al 2013, Vogt et al 2016, Milne et al 2019, Haris et al 2021, approximately at the same chest section as in our study, but sex-specific EIT data analyses were typically not performed. If similar placement of EIT electrodes is still considered in future technological developments, as is the case in almost all recently proposed wearable EIT devices (Zouari et al 2022, Frerichs et al 2023, then sex-specific interpretations of findings are also required.…”

Respiratory rate monitoring in ICU patients and healthy volunteers using electrical impedance tomography: a validation study

“…Data processing was performed in Matlab R2022a (Mathworks, Natick, USA). To find STBP in the EIT signal, a method proposed by Haris et al was used for identification and analysis of stable breathing period in EIT recordings (Haris et al 2021). Three criteria were used for identification of STBPs, namely the coefficient of variation of tidal volume (CV EIT_tidal-volume ), breath duration (CV EIT_breath-duration ) and end-expiratory lung impedance (CV EIT_EELI ).…”