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• W2804498196 abstract "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." @default.
• W2804498196 created "2018-06-01" @default.
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• W2804498196 date "2018-04-01" @default.
• W2804498196 modified "2023-09-26" @default.
• W2804498196 title "Continuous Estimation Prediction of Knee Joint Angles Using Fusion of Electromyographic and Inertial Sensors for Active Transfemoral Leg Prostheses" @default.
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• W2804498196 doi "https://doi.org/10.1142/s2424922x18400089" @default.
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