Automatic Leg Gesture Recognition Based on Portable Electromyography Readers
| Autor: | Efraín A. Mejía-González, Jessica Estrada-Lechuga, Josue Aaron Lopez-Leyva, Raul I. Ramos-Garcia |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
medicine.diagnostic_test
Computer science business.industry 0206 medical engineering Confusion matrix Pattern recognition 02 engineering and technology Electromyography Linear discriminant analysis 020601 biomedical engineering ComputingMethodologies_PATTERNRECOGNITION Gesture recognition 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Artificial intelligence business Classifier (UML) Gesture |
| Zdroj: | 2019 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE). |
| DOI: | 10.1109/icmeae.2019.00008 |
| Popis: | In this paper, recognition of leg gestures is performed using Linear Discriminant Analysis in order to propose a real application for prosthetic leg considering transfemoral amputee. As results, the confusion matrix shows the performance of the algorithm, where the Class #1 and #3 were the best classes classified (sensitivity is 100%), and Class #2 was the worst classified (sensitivity is 67%). In addition, the probability that the classifier ranks a randomly chosen positive instance higher than a randomly chosen negative for Class #2 and #4 is the same, AUC =0.94, and AUC =1 for Class #1 and #3. Although the hardware and algorithm used have adequate performance, the optimization and improve the real testing conditions are important requirements for real human applications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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