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Real-time classification of multi-modal sensory data for prosthetic hand control.

, , , , and . BioRob, page 536-541. IEEE, (2016)

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CMOS Magnetic Sensors for Wearable Magnetomyography., , , and . EMBC, page 2116-2119. IEEE, (2018)Beyond Within-Subject Performance: A Multi-Dataset Study of Fine-Tuning in the EEG Domain., , , , , , and . SMC, page 4429-4435. IEEE, (2023)Generalizability of EMG decoding using local field potentials., , , , and . EMBC, page 1630-1633. IEEE, (2014)Spatio-Temporal Inertial Measurements Feature Extraction Improves Hand Movement Pattern Recognition without Electromyography., , , and . EMBC, page 2108-2111. IEEE, (2018)Towards low-dimensionsal proportional myoelectric control., , and . EMBC, page 7155-7158. IEEE, (2015)Evaluation of regression methods for the continuous decoding of finger movement from surface EMG and accelerometry., , and . NER, page 631-634. IEEE, (2015)Recalibration of myoelectric control with active learning., , and . Frontiers Neurorobotics, (September 2022)Use of regularized discriminant analysis improves myoelectric hand movement classification., , and . NER, page 395-398. IEEE, (2017)DENVIS: Scalable and High-Throughput Virtual Screening Using Graph Neural Networks with Atomic and Surface Protein Pocket Features., , , and . J. Chem. Inf. Model., 62 (19): 4642-4659 (2022)Real-time classification of multi-modal sensory data for prosthetic hand control., , , , and . BioRob, page 536-541. IEEE, (2016)