Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia.
Vukov Centar Os-Ossis, 21000 Novi Sad, Serbia.
Sensors (Basel). 2024 Aug 28;24(17):5575. doi: 10.3390/s24175575.
This study introduced a depth-sensing-based approach with robust algorithms for tracking relative morphological changes in the chests of patients undergoing physical therapy. The problem that was addressed was the periodic change in morphological parameters induced by breathing, and since the recording was continuous, the parameters were extracted for the moments of maximum and minimum volumes of the chest (inspiration and expiration moments), and analyzed. The parameters were derived from morphological transverse cross-sections (CSs), which were extracted for the moments of maximal and minimal depth variations, and the reliability of the results was expressed through the coefficient of variation (CV) of the resulting curves. Across all subjects and levels of observed anatomy, the mean CV for CS depth values was smaller than 2%, and the mean CV of the CS area was smaller than 1%. To prove the reproducibility of measurements (extraction of morphological parameters), 10 subjects were recorded in two consecutive sessions with a short interval (2 weeks) where no changes in the monitored parameters were expected and statistical methods show that there was no statistically significant difference between the sessions, which confirms the reproducibility hypothesis. Additionally, based on the representative CSs for inspiration and expirations moments, chest mobility in quiet breathing was examined, and the statistical test showed no difference between the two sessions. The findings justify the proposed algorithm as a valuable tool for evaluating the impact of rehabilitation exercises on chest morphology.
本研究提出了一种基于深度感应的方法，结合稳健的算法，用于跟踪接受物理治疗的患者胸部的相对形态变化。所解决的问题是呼吸引起的形态参数周期性变化，由于记录是连续的，因此提取了胸部最大和最小容积时刻（吸气和呼气时刻）的参数，并进行了分析。参数来自形态横切（CS），这些 CS 是在最大和最小深度变化时刻提取的，结果曲线的变异系数（CV）表示了结果的可靠性。在所有受试者和观察到的解剖结构水平上，CS 深度值的平均 CV 小于 2%，CS 面积的平均 CV 小于 1%。为了证明测量（形态参数提取）的可重复性，10 名受试者在两次连续记录中进行了两次记录，两次记录之间的间隔很短（2 周），预计监测参数不会发生变化，统计方法表明两次记录之间没有统计学上的显著差异，这证实了可重复性假设。此外，基于吸气和呼气时刻的代表性 CS，检查了安静呼吸时的胸部活动度，统计检验显示两次记录之间没有差异。这些发现证明了所提出的算法是评估康复运动对胸部形态影响的有价值工具。
