The study aimed to verify the inter- and intra-examiner reliability of an interactive and personalized MATLAB® application for the bio-photogrammetric analysis of thoracoabdominal mobility in NB. As result, the model proposed in the present study exhibited excellent inter- and intra-examiner reliability (ICC 0.84–0.99 and ICC 0.81–0.96, respectively), which is essential to confirm instrument validity [21]. In addition, the study also proposed to compare the results of three evaluators and assess the validation of automatic RR measurement in relation to its manual counterpart, showing excellent correlation between manual and automatic models for measuring RR (r > 0.95, p < 0.001).
Bio-photogrammetric models have been tested in a number of studies [22–24], demonstrating good to excellent reliability levels in body kinematics evaluation, particularly postural analysis, as in the study by Paes et al. (2017) [22],who used Postural Assessment Software (SAPO) to analyze anteriorization and head inclination angles in the anterior and lateral views of the sitting and standing positions. Reliable results can be obtained when the evaluation is carried out by different examiners or by the same examiner on different days. Despite differing from our investigation in terms of the objectives and populations studied, these findings also demonstrate the importance and reliability of alternative bio-photogrammetric models for the analysis of body kinematics.
Sarro et al. (2018) [25] set out to investigate the intra and inter-rater reliability and minimal detectable change (MDC) of thoracoabdominal mobility measures using photogrammetry in young adults. In this study, 17 healthy participants were evaluated based on photographs taken during apnea at maximal inspiration and expiration. This strategy was adopted to calculate the latero-lateral and anteroposterior diameters of the chest (at the axillary and xiphoid level) and abdomen for analysis using Postural Evaluation Software (SAPO, version 0.68, São Paulo, SP, Brazil). The experienced examiner obtained good reliability (mean intraclass correlation coefficient (ICC): 0.98; mean MDC: 0.3) and inter-observer agreement (mean ICC: 0.97; mean MDC: 0.35) for all measures [25]. Despite being obtained using a different population from ours, these findings corroborate those of the present study, demonstrating excellent inter and intra-examiner reliability in the investigation of thoracoabdominal kinematic measurements using photogrammetry.
From this perspective, bio-photogrammetry has also been applied to evaluate respiratory function by analyzing thoracoabdominal kinematics and synchrony [8, 17, 18]. However, it is important to underscore that the vast majority of current studies were carried out in adolescents or adults, as in the study by Sarro et al. (2018) [25]. As such, this analytical resource should be used to evaluate different age groups, particularly in neonatology, as demonstrated in our study.
Ripka et al. (2014) [18] compared bio-photogrammetry with spirometry in healthy adolescents to test a model capable of predicting lung volumes and capacities and found a high correlation with the spirometric measurements forced vital capacity (0.812), forced expiratory volume in one second (FEV1–0.708), and peak expiratory flow (PEF − 0.762), showing the importance of including thoracoabdominal mobility variation in predictive equations for total lung capacity [18]. Thus, the findings of the present study justify the use of this assessment method, previously applied in other populations, given its reliability in evaluating the neonatal thoracoabdominal complex, as demonstrated here.
In a study by Caruso et al. (2020) [26] that investigated intra-examiner reliability using photogrammetry in young adult asthmatic patients and healthy controls, the results show moderate reliability for axillary, xiphoid and umbilical mobility (mean ICC of 0.68, 0.55 and 0.73, respectively) in the asthmatic group, while controls exhibited moderate reliability for axillary mobility (average of 0.68) and good reliability for xiphoid and umbilical mobility (average of 0.81 and 0.70 respectively). These findings demonstrate that photogrammetric analysis of thoracoabdominal kinematics is a reliable method and can be included in clinical practice, corroborating our study.
In the present study, image processing using a custom-made MATLAB® routine enabled easy, automatic and fast analysis. Guerra et al. (2017) [7] also conducted thoracoabdominal assessment in NB, applying bio-photogrammetry with AutoCAD® software, reporting difficulties with the instrument because it requires frame-by-frame analysis, prolonging evaluation of each subject [7]. Moreover, the total number of frames analyzed by AutoCAD® is much lower than that achieved by MATLAB® [20], and may produce less reliable results. Oliveira et al. (2016) [20] found that the latter program was superior [20], since it was considered effective in differentiating changes in the delimitation of the thoracoabdominal region. They considered it a useful tool in assessing patients who cannot voluntarily control RR and the synergy of muscle activity during breathing. In addition, the authors underscored that although AutoCAD ® is an effective method, it is time consuming, since each frame takes 10 to 25 minutes to process.
Bio-photogrammetry analysis in the hospital environment using the MATLAB® App to investigate the kinematics of breathing in NB allows the examiner to infer aspects related to thoracic and abdominal kinematics in a practical and reproducible way. This could contribute to bedside clinical analysis of different health conditions, using the compartmental area for thoracoabdominal kinematics.
In addition to MATLAB’s automation and speed, the software offers several pre-applied functions, as well as the freedom to create other routines [27]. This enables extrapolation to other analyses and populations, suggesting further studies. Bio-photogrammetry analysis through the proposed MATLAB® App is a noninvasive resource, with rapid data processing and flexibility in terms of where it can be applied.
Studies using noninvasive lung function tests, which can be easily performed in non-sedated infants at bedside are of particular interest [28]. Some authors have pointed out the variability of breathing as an important functional marker for early investigation of childhood respiratory morbidity [28–30]. The excellent reliability of the present algorithm allows a range of possibilities, since it monitors the respiration cycle breath by breath. On the other hand, MATLAB® is more costly than other processors, such as the conventional C or Fortran compiler, but this is offset by its advantages [31]. Another limitation is that some of the adhesive markers became detached during filming, precluding the use of these videos. Additionally, the need to keep the baby in a specific position and the possible issue of marker occlusion common to all optical methods are also limitations.