Name
Title | ||
|---|---|---|
Electromyography-controlled car: A proof of concept based on surface electromyography, Extreme Learning Machines and low-cost open hardware. |
Abstract | ||
|---|---|---|
•Proof of concept of a Human–Machine interface based on surface electromyography and machine learning using low-cost hardware. Electromyographic gesture signals are acquired using eight low-cost electrodes. We used ten different hand gestures.•Electromyographic signals were simulated using an open myographic database and transmitted via radio to a low-cost system able to perform real-time classification.•The recognition system uses Extreme Learning Machines and reaches reasonable accuracies.•Results were compared for five different ELM configurations, reaching an accuracy greater than 85% for 200 hidden neurons.•150 ms samples are transmitted and classified in less than 3 s, but results can be improved in real applications, in which signal simulation is not necessary. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.compeleceng.2018.11.012 | Computers & Electrical Engineering |
Keywords | Field | DocType |
Electromyographic control,Human machine interface,Social innovation,Machine learning,Extreme Learning Machines,Car functionalities | Distraction,Gesture,Computer science,Electromyography,Proof of concept,Signal classification,Computer hardware,Automotive industry | Journal |
Volume | ISSN | Citations |
73 | 0045-7906 | 0 |
PageRank | References | Authors |
0.34 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rafaela Covello de Freitas | 1 | 0 | 0.68 |
| Rodrigo Alves | 2 | 0 | 0.34 |
| Abel G. Filho | 3 | 1 | 1.73 |
| Ricardo Emmanuel de Souza | 4 | 14 | 4.53 |
| Byron L. D. Bezerra | 5 | 0 | 0.34 |
| Wellington P. dos Santos | 6 | 36 | 11.00 |