A human-machine interface using electrical impedance tomography for hand prosthesis control
Article
Wu, Yu, Jiang, Dai, Liu, Xiao, Bayford, Richard and Demosthenous, Andreas 2018. A human-machine interface using electrical impedance tomography for hand prosthesis control. IEEE Transactions on Biomedical Circuits and Systems. 12 (6), pp. 1322-1333. https://doi.org/10.1109/TBCAS.2018.2878395
Type | Article |
---|---|
Title | A human-machine interface using electrical impedance tomography for hand prosthesis control |
Authors | Wu, Yu, Jiang, Dai, Liu, Xiao, Bayford, Richard and Demosthenous, Andreas |
Abstract | This paper presents a human-machine interface that establishes a link between the user and a hand prosthesis. It successfully uses electrical impedance tomography, a conventional bio-impedance imaging technique, using an array of electrodes contained in a wristband on the user's forearm. Using a high-performance analog front-end application specific integrated circuit (ASIC), the user's forearm inner bio-impedance redistribution is accurately assessed. These bio-signatures are strongly related to hand motions and using artificial neural networks, they can be learned so as to recognize the user's intention in real time for prosthesis operation. In this work, eleven hand motions are designed for prosthesis operation with a gesture switching enabled sub-grouping method. Experiments with five subjects show that the system can achieve 98.5% accuracy with a grouping of three gestures and an accuracy of 94.4% with two sets of five gestures. The ASIC comprises a current driver with common-mode reduction capability and a current feedback instrumentation amplifier (that occupy an area of 0.07 mm 2 ). The ASIC operates from ±1.65 V power supplies and has a minimum bio-impedance sensitivity of 12.7 mΩp-p. |
Keywords | Current driver; electrical impedance tomography; human-machine interface; hand prosthesis control; instrumentation amplifier |
Publisher | IEEE |
Journal | IEEE Transactions on Biomedical Circuits and Systems |
ISSN | 1932-4545 |
Electronic | 1940-9990 |
Publication dates | |
Dec 2018 | |
Publication process dates | |
Deposited | 24 Aug 2023 |
Output status | Published |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TBCAS.2018.2878395 |
Web of Science identifier | WOS:000455190000012 |
https://repository.mdx.ac.uk/item/8zv1v
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