AUTHOR=Zhang Yan , Li Danye , Zhang Fengyao , Wang Zongyu , Xue Lei , Nan Xiaolu , Li Nianming , Tan Xilai , Guo Weidong , Zhang Yuru , Zhao Hongmei , Ge Qinggang , Wang Dangxiao TITLE=Evaluation and modeling of diaphragm displacement using ultrasound imaging for wearable respiratory assistive robot JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=12 YEAR=2024 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2024.1436702 DOI=10.3389/fbioe.2024.1436702 ISSN=2296-4185 ABSTRACT=Introduction

Assessing the influence of respiratory assistive devices on the diaphragm mobility is essential for advancing patient care and improving treatment outcomes. Existing respiratory assistive robots have not yet effectively assessed their impact on diaphragm mobility. In this study, we introduce for the first time a non-invasive, real-time clinically feasible ultrasound method to evaluate the impact of soft wearable robots on diaphragm displacement.

Methods

We measured and compared diaphragm displacement and lung volume in eight participants during both spontaneous and robotic-assisted respiration. Building on these measurements, we proposed a human-robot coupled two-compartment respiratory mechanics model that elucidates the underlying mechanism by which our extracorporeal wearable robots augments respiration. Specifically, the soft robot applies external compression to the abdominal wall muscles, inducing their inward movement, which consequently pushes the diaphragm upward and enhances respiratory function. Finally, we investigated the level and shape of various robotic assistive forces on diaphragm motion.

Results

This robotic intervention leads to a significant increase in average diaphragm displacement by 1.95 times and in lung volume by 2.14 times compared to spontaneous respiration. Furthermore, the accuracy of the proposed respiratory mechanics model is confirmed by the experimental results, with less than 7% error in measurements of both diaphragm displacement and lung volume. Finally, the magnitude of robotic assistive forces positively correlates with diaphragm movement, while the shape of the forces shows no significant relationship with diaphragm activity.

Conclusion

Our experimental findings validate the effective assistance mechanism of the proposed robot, which enhances diaphragm mobility and assists in ventilation through extracorporeal robotic intervention. This robotic system can assist with ventilation while increasing diaphragm mobility, potentially resolving the issue of diaphragm atrophy. Additionally, this work paves the way for improved robotic designs and personalized assistance, tailored to the dynamics of the diaphragm in respiratory rehabilitation.