Augmenting the human-machine interface: improving manual accuracy
- 22 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 4, 3546-3550
- https://doi.org/10.1109/robot.1997.606884
Abstract
We present a novel application of a neural network to augment manual precision by cancelling involuntary motion. This method may be applied in microsurgery, using either a telerobotic approach or active compensation in a handheld instrument. A feedforward neural network is trained to input the measured trajectory of a handheld tool tip and output the intended trajectory. Use of the neural network decreases rms error in recordings from four subjects by an average of 43.9%.Keywords
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