首页|Study Results from Zhengzhou University Provide New Insights into Androids (A Tr ansformer-based Gesture Prediction Model Via Semg Sensor for Human-robot Interac tion)
Study Results from Zhengzhou University Provide New Insights into Androids (A Tr ansformer-based Gesture Prediction Model Via Semg Sensor for Human-robot Interac tion)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ro botics - Androids. According to news reportingout of Henan, People’s Republic o f China, by NewsRx editors, research stated, “As one of themost direct and pivo tal modes of human-computer interaction (HCI), the application of surface electromyography (sEMG) signals in the domain of gesture prediction has emerged as a p rominent area ofresearch. To enhance the performance of gesture prediction syst em based on multichannel sEMG signals,a novel gesture prediction framework is p roposed that: 1) conversion of original biological signals frommultichannel sEM G into 2-D time-frequency maps is achieved through the incorporation of continuo uswavelet transform (CWT) and 2) for 2-D time-frequency map inputs, a Transform er-based classificationnetwork that effectively learns local and global context information is proposed, named DIFT-Net, withthe goal of implementing sEMG-bas ed gesture prediction for robot interaction.”
HenanPeople’s Republic of ChinaAsiaAndroidsEmerging TechnologiesHuman-Robot InteractionMachine LearningRob otRoboticsZhengzhou University
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