https://survivinsignaling.com/....index.php/markov-dec
Joint perspectives had been computed utilizing IMUs that were positioned on the hand, forearm, upper arm, and torso. Different device learning designs had been created with different algorithms and train-test splits. Random woodland models with flattened kinematic data as an element had the greatest precision (98.6%). Using triaxial joint range of flexibility since the feature set resulted in decreased accuracy (91.9%) with quicker speeds. Accuracy would not decrease be
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