| Autor: |
López-Delis, Alberto, Miosso, Cristiano J., Carvalho, João L. A., da Rocha, Adson F., Borges, Geovany A. |
| Předmět: |
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| Zdroj: |
Advances in Data Science & Adaptive Analysis; 2018, Vol. 10 Issue 2, pN.PAG-N.PAG, 30p |
| Abstrakt: |
Information extracted from the surface electromyographic (sEMG) signals can allow for the detection of movement intention in transfemoral prostheses. The sEMG can help estimate the angle between the femur and the tibia in the sagittal plane. However, algorithms based exclusively on sEMG information can lead to inaccurate results. Data captured by inertial-sensors can improve this estimate. We propose three myoelectric algorithms that extract data from sEMG and inertial sensors using Kalman-filters. The proposed fusion-based algorithms showed improved performance compared to methods based exclusively on sEMG data, generating improvements in the accuracy of knee joint angle estimation and reducing estimation artifacts. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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