首页|Researchers at Tianjin University Report New Data on Robotics and Automation (Es timating Wrist Joint Angle Based On M-mode Ultrasound Signals)

Researchers at Tianjin University Report New Data on Robotics and Automation (Es timating Wrist Joint Angle Based On M-mode Ultrasound Signals)

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Data detailed on Robotics -Robotics a nd Automation have been presented. According to news reporting out of Tianjin, P eople's Republic of China, by NewsRx editors, research stated, "Ultrasound sensi ng-based human-machine interface (HMI) is promising with the precise detection o f the morphological changes of contracting muscles. M-mode ultrasound, a type of signal modulated through movement, has not yet been fully explored for HMI." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news journalists obtained a quote from the research from Tianjin University, "This letter aimed to evaluate the capability of M-mode ultrasound for the cont inuous movement estimation of wrist joint. A commercial medical ultrasound syste m was employed to collect M-mode and B-mode ultrasound images simultaneously. Si x able-bodied subjects were recruited for the wrist joint angle prediction. A fe ature extraction method of M-mode ultrasound was proposed. A strong linear relat ionship was found between the extracted features and the wrist joint angle. A li near regression model was adopted to compare the performance of two ultrasound m odes under two different training strategies. The model was trained with trainin g sets of different scales and complexity levels. For different training strateg ies, the M-mode ultrasound consistently kept the correlation coefficient (r) of over 0.9 and the normalized root mean square error (NRMSE) of below 0.15. Moreov er, the M-mode ultrasound significantly outperformed B-mode ultrasound in the tw o training strategies."

TianjinPeople's Republic of ChinaAsiaRobotics and AutomationRoboticsTianjin University

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Oct.7)