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Using the frequency signature to detect muscular activity in weak and noisy myoelectric signals.

, , , and . Biomed. Signal Process. Control., (2019)

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Using the frequency signature to detect muscular activity in weak and noisy myoelectric signals., , , and . Biomed. Signal Process. Control., (2019)Can a Visual Biofeedback system based on predictive information improve postural performance?, , , , , and . EMBC, page 6951-6954. IEEE, (2015)A neural approach to extract foreground from human movement images., , , and . Comput. Methods Programs Biomed., 82 (1): 73-80 (2006)A neural-based remote eye gaze tracker under natural head motion., , , and . Comput. Methods Programs Biomed., 92 (1): 66-78 (2008)Optimal estimation of power spectral density by means of a time-varying autoregressive approach., and . Signal Process., 72 (1): 1-14 (1999)SVM versus MAP on Accelerometer Data to Distinguish among Locomotor Activities Executed at Different Speeds., , , , , , , and . Comput. Math. Methods Medicine, (2013)Quantitative color analysis for capillaroscopy image segmentation., , , , , and . Medical Biol. Eng. Comput., 50 (6): 567-574 (2012)A Neural Network Embedded System for Real-time Estimation of Muscle Forces., , , , and . ICCS, volume 51 of Procedia Computer Science, page 60-69. Elsevier, (2015)A novel Sensitivity Index from the Flow Velocity Variation in Quality Control for PW Doppler: a preliminary study., , , , , , and . MeMeA, page 1-6. IEEE, (2021)Mr Image Processing to Predict Complete Responders by Evaluating the Tumor Regression Grade: A Sensitivity Analysis., , , , , , and . EUVIP, page 222-227. IEEE, (2019)