Assessing workload in using electromyography (EMG)-based prostheses

Using prosthetic devices requires a substantial cognitive workload. This study investigated classification models for assessing cognitive workload in electromyography (EMG)-based prosthetic devices with various types of input features including eye-tracking measures, task performance, and cognitive...

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Veröffentlicht in:	Ergonomics 2024-02, Vol.67 (2), p.257-273
Hauptverfasser:	Park, Junho, Berman, Joseph, Dodson, Albert, Liu, Yunmei, Armstrong, Matthew, Huang, He, Kaber, David, Ruiz, Jaime, Zahabi, Maryam
Format:	Artikel
Sprache:	eng
Schlagworte:	Abbreviations Algorithms Artificial neural networks Classification Cognitive ability Cognitive tasks Degrees of freedom Devices Discriminant analysis EEG Electroencephalography Electromyography Eye movements Feature selection Learning algorithms Machine learning Mental workload Model accuracy Motor task performance Neural networks Pattern recognition Prostheses prosthesis Prosthetics Pupil size Pupillometry Relocation Taskload Workload Workloads
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