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Virtual Grasping: Closed-Loop Force Control Using Electrotactile Feedback.

, , , , and . Comput. Math. Methods Medicine, (2014)

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Biomedical Signal Compression With Optimized Wavelets., , , , and . ICASSP (2), page 1044-1047. IEEE, (2006)Linear predictive coding of myoelectric signals., , , and . ICASSP (5), page 629-632. IEEE, (2005)Extending mode switching to multiple degrees of freedom in hand prosthesis control is not efficient., , , and . EMBC, page 658-661. IEEE, (2014)Power spectrum of the rectified EMG: Influence of motor unit action potential shapes., , and . EMBC, page 2193-2196. IEEE, (2014)Simulations of high-density surface electromyograms in dynamic muscle contractions., , and . EMBC, page 3453-3456. IEEE, (2017)Theoretical Model and Experimental Validation of the estimated proportions of common and independent input to motor neurons., , and . EMBC, page 254-257. IEEE, (2015)The Interaction Between Feedback Type and Learning in Routine Grasping With Myoelectric Prostheses., , , , and . IEEE Trans. Haptics, 13 (3): 645-654 (2020)Multi-Attention Feature Fusion Network for Accurate Estimation of Finger Kinematics From Surface Electromyographic Signals., , , , , , and . IEEE Trans. Hum. Mach. Syst., 53 (3): 512-519 (2023)Control of Spinal Motoneurons by Feedback From a Non-Invasive Real-Time Interface., , , and . IEEE Trans. Biomed. Eng., 68 (3): 926-935 (2021)Detection of Attention alteration of BCI Users based on EEG Analysis., , , , and . GBCIC, Verlag der Technischen Universitaet Graz, (2017)