Offline Evaluation Matters: Investigation of the Influence of Offline Performance on Real-Time Operation of Electromyography-Based Neural-Machine Interfaces

There has been a debate on the most appropriate way to evaluate electromyography (EMG)-based neural-machine interfaces (NMIs). Accordingly, this study examined whether a relationship between offline kinematic predictive accuracy (R2) and user real-time task performance while using the interface coul...

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Veröffentlicht in:	IEEE transactions on neural systems and rehabilitation engineering Jg. 31; S. 680 - 689
Hauptverfasser:	Hinson, Robert M., Berman, Joseph, Filer, William, Kamper, Derek, Hu, Xiaogang, Huang, He
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Completion time Decoding Electromyography Interfaces Kinematics machine learning Matching Measurement Motion capture Myoelectric control Myoelectricity Neural networks neural–machine interface offline analysis Performance evaluation Performance measurement Posture Real time operation real-time performance Real-time systems Task analysis Wrist
ISSN:	1534-4320, 1558-0210, 1558-0210
Online-Zugang:	Volltext
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