Name
Title | ||
|---|---|---|
Abstract myoelectric control with EMG drive estimated using linear, kurtosis and Bayesian filtering |
Abstract | ||
|---|---|---|
Three muscle activation estimators: a linear mean-absolute value filter, a recursive Bayesian method, and a kurtosis filter were compared as control approaches for an abstract myoelectric-controlled interface. The linear filter outperformed both the Bayesian and kurtosis methods with respect to participants' overall scores. Despite significantly less efficient trajectories, the Bayesian filter showed a reduction in the time required to reach individual targets. Results demonstrate both that linear methods can outperform more complex filtering techniques, and that real-time kurtosis may be used as an activation estimator. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/NER.2017.8008290 | 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER) |
Keywords | Field | DocType |
abstract myoelectric control,EMG signal,linear filtering,kurtosis filtering,Bayesian filtering,muscle activation estimators,linear mean-absolute value filter,complex filtering techniques | Linear filter,Computer science,Filter (signal processing),Feature extraction,Artificial intelligence,Bayesian filtering,Trajectory,Kurtosis,Machine learning,Bayesian probability,Estimator | Conference |
ISSN | ISBN | Citations |
1948-3546 | 978-1-5090-4604-1 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthew Dyson | 1 | 0 | 2.70 |
| Jessica Barnes | 2 | 0 | 0.68 |
| Kianoush Nazarpour | 3 | 75 | 19.08 |