首页|China-Japan Friendship Hospital Reports Findings in Robotics (Evaluation and mod eling of diaphragm displacement using ultrasound imaging for wearable respirator y assistive robot)
China-Japan Friendship Hospital Reports Findings in Robotics (Evaluation and mod eling of diaphragm displacement using ultrasound imaging for wearable respirator y assistive robot)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subjec t of a report. According to news reporting originating from Beijing, People’s Re public of China, by NewsRx correspondents, research stated, “Assessing the influ ence of respiratory assistive devices on the diaphragm mobility is essential for advancing patient care and improving treatment outcomes. Existing respiratory a ssistive robots have not yet effectively assessed their impact on diaphragm mobi lity.” Financial support for this research came from National Natural Science Foundatio n of China. Our news editors obtained a quote from the research from China-Japan Friendship Hospital, “In this study, we introduce for the first time a non-invasive, real-t ime clinically feasible ultrasound method to evaluate the impact of soft wearabl e robots on diaphragm displacement. We measured and compared diaphragm displacem ent and lung volume in eight participants during both spontaneous and robotic-as sisted respiration. Building on these measurements, we proposed a human-robot co upled two-compartment respiratory mechanics model that elucidates the underlying mechanism by which our extracorporeal wearable robots augments respiration. Spe cifically, the soft robot applies external compression to the abdominal wall mus cles, inducing their inward movement, which consequently pushes the diaphragm up ward and enhances respiratory function. Finally, we investigated the level and s hape of various robotic assistive forces on diaphragm motion. This robotic inter vention leads to a significant increase in average diaphragm displacement by 1.9 5 times and in lung volume by 2.14 times compared to spontaneous respiration. Fu rthermore, the accuracy of the proposed respiratory mechanics model is confirmed by the experimental results, with less than 7% error in measureme nts of both diaphragm displacement and lung volume. Finally, the magnitude of ro botic assistive forces positively correlates with diaphragm movement, while the shape of the forces shows no significant relationship with diaphragm activity. O ur experimental findings validate the effective assistance mechanism of the prop osed robot, which enhances diaphragm mobility and assists in ventilation through extracorporeal robotic intervention. This robotic system can assist with ventil ation while increasing diaphragm mobility, potentially resolving the issue of di aphragm atrophy.”
BeijingPeople’s Republic of ChinaAsi aEmerging TechnologiesMachine LearningNano-robotRobotRoboticsRobots
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