Robotics & Machine Learning Daily News2024,Issue(Oct.16) :68-69.

Studies from Sun Yat-sen University Update Current Data on Fatigue (An Electromy ographic-based Control Using Gaussian Mixture Model On an Upper-limb Cable-drive n Rehabilitation Robot)

Robotics & Machine Learning Daily News2024,Issue(Oct.16) :68-69.

Studies from Sun Yat-sen University Update Current Data on Fatigue (An Electromy ographic-based Control Using Gaussian Mixture Model On an Upper-limb Cable-drive n Rehabilitation Robot)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Fa tigue. According to news reporting originating from Shenzhen, People’s Republic of China, by NewsRx correspondents, research stated, “Electromyographic (EMG)-ba sed admittance control by arm force can provide continuous motion control in rob ot-assisted rehabilitation. Natural and complex physical human-robot interaction s utilizing intelligent EMG-based interfaces require a computational estimation model for 3D voluntary forces.”

Key words

Shenzhen/People’s Republic of China/As ia/Emerging Technologies/Fatigue/Health and Medicine/Human-Robot Interaction/Machine Learning/Robot/Robotics/Sun Yat-sen University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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