TY - JOUR TI - A Human-Machine Interface Using Electrical Impedance Tomography for Hand Prosthesis Control AV - public Y1 - 2018/12// EP - 1333 N2 - 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. The ASIC operates from <formula><tex>$\pm$</tex></formula>1.65 V power supplies, occupies an area of 0.07 mm2, and has a minimum bio-impedance sensitivity of 12.7 mΩp-p. ID - discovery10061153 KW - Voltage measurement KW - Electrodes KW - Prosthetics KW - Tomography KW - Current measurement KW - Muscles KW - Impedance KW - Current driver KW - electrical impedance tomography KW - human machine interface KW - hand prosthesis control KW - instrumentation amplifier SP - 1322 VL - 12 IS - 6 N1 - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions. UR - https://doi.org/10.1109/TBCAS.2018.2878395 SN - 1932-4545 JF - IEEE Transactions on Biomedical Circuits and Systems A1 - Wu, Y A1 - Jiang, D A1 - Liu, X A1 - Bayford, R A1 - Demosthenous, A ER -