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Machine Learning for the Control of Prosthetic Arms: Using Electromyographic Signals for Improved Performance.

, , , and . IEEE Signal Process. Mag., 38 (4): 46-53 (2021)

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A Cost-Effective Inertial Measurement System for Tracking Movement and Triggering Kinesthetic Feedback in Lower-Limb Prosthesis Users., , , , and . Sensors, 21 (5): 1844 (2021)A Case Series in Position-Aware Myoelectric Prosthesis Control Using Recurrent Convolutional Neural Network Classification with Transfer Learning., , , and . ICORR, page 1-6. IEEE, (2023)Machine Learning for the Control of Prosthetic Arms: Using Electromyographic Signals for Improved Performance., , , and . IEEE Signal Process. Mag., 38 (4): 46-53 (2021)Skin Stretch Enhances Illusory Movement in Persons with Lower-Limb Amputation., , , , , and . ICORR, page 1233-1238. IEEE, (2019)The effect of myoelectric prosthesis control strategies and feedback level on adaptation rate for a target acquisition task., , and . ICORR, page 200-204. IEEE, (2017)Joint Action is a Framework for Understanding Partnerships Between Humans and Upper Limb Prostheses., , , , , , and . CoRR, (2022)Neurorobotic fusion of prosthetic touch, kinesthesia, and movement in bionic upper limbs promotes intrinsic brain behaviors., , , , , , , and . Sci. Robotics, (2021)Conventional analysis of trial-by-trial adaptation is biased: Empirical and theoretical support using a Bayesian estimator., , , and . PLoS Comput. Biol., (2018)Composite Recurrent Convolutional Neural Networks Offer a Position-Aware Prosthesis Control Alternative While Balancing Predictive Accuracy with Training Burden., , , , and . ICORR, page 1-6. IEEE, (2022)Preliminary Evaluation of the Effect of Mechanotactile Feedback Location on Myoelectric Prosthesis Performance Using a Sensorized Prosthetic Hand., , , , and . Sensors, 22 (10): 3892 (2022)