首页|New Machine Learning Study Findings Have Been Reported from University of Waterloo (Robust Machine Learning Mapping of Semg Signals To Future Actuator Commands In Biomechatronic Devices)
New Machine Learning Study Findings Have Been Reported from University of Waterloo (Robust Machine Learning Mapping of Semg Signals To Future Actuator Commands In Biomechatronic Devices)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reporting outof Waterloo, Canada, by NewsRx editors, research stated, “A machine learning model for regression of interrupted Surface Electromyography (sEMG) signals to future control-oriented signals (e.g., robot’s jointangle and assistive torque) of an active biomechatronic device for high-level myoelectric-based hierarchicalcontrol is proposed. A Recurrent Neural Network (RNN) was trained using output data, initially obtainedfrom offline optimization of the biomechatronic (human-robot) device and shifted by the prediction horizon.”
WaterlooCanadaNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningRobotRoboticsUniversity of Waterloo
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