Augmenting the human-machine interface: improving manual accuracy
نویسندگان
چکیده
We present a novel application of a neural network to augment manual precision by canceling 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%.
منابع مشابه
Error assessment in man-machine systems using the CREAM method and human-in-the-loop fault tree analysis
Background and Objectives: Despite contribution to catastrophic accidents, human errors have been generally ignored in the design of human-machine (HM) systems and the determination of the level of automation (LOA). This paper aims to develop a method to estimate the level of automation in the early stage of the design phase considering both human and machine performance. Methods: A quantita...
متن کاملQuantative Evaluation of the Efficiency of Facial Bio-potential Signals Based on Forehead Three-Channel Electrode Placement For Facial Gesture Recognition Applicable in a Human-Machine Interface
Introduction: Today, facial bio-potential signals are employed in many human-machine interface applications for enhancing and empowering the rehabilitation process. The main point to achieve that goal is to record appropriate bioelectric signals from the human face by placing and configuring electrodes over it in the right way. In this paper, heuristic geometrical position and configuration of ...
متن کاملSteering a Tractor by Means of an EMG-Based Human-Machine Interface
An electromiographic (EMG)-based human-machine interface (HMI) is a communication pathway between a human and a machine that operates by means of the acquisition and processing of EMG signals. This article explores the use of EMG-based HMIs in the steering of farm tractors. An EPOC, a low-cost human-computer interface (HCI) from the Emotiv Company, was employed. This device, by means of 14 sali...
متن کاملLinguistically Inspired Language Model Augmentation for MT
The present article reports on efforts to improve the translation accuracy of a corpus–based Machine Translation (MT) system. In order to achieve that, an error analysis performed on past translation outputs has indicated the likelihood of improving the translation accuracy by augmenting the coverage of the Target-Language (TL) side language model. The method adopted for improving the language ...
متن کاملBonsai: Interactive Supervision for Machine Learning
We introduce Bonsai, a visual system developed for statistical machine learning researchers, to explore and interact with the model building process and to compare between different models over the same data set. The system is especially valuable for classification problems arising from large and high dimensional data sets, where manual inspection or construction of classification models can be...
متن کامل