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Performance of an implantable impedance spectroscopy monitor using ZigBee
This paper presents the characterization measurements of an implantable bioimpedance monitor with ZigBee. Such measurements are done over RC networks, performing short and long-term measurements, with and without mismatch in electrodes and varying the temperature and the RF range. The bioimpedance m...
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Published in: | Journal of physics. Conference series 2010-04, Vol.224 (1), p.012163 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This paper presents the characterization measurements of an implantable bioimpedance monitor with ZigBee. Such measurements are done over RC networks, performing short and long-term measurements, with and without mismatch in electrodes and varying the temperature and the RF range. The bioimpedance monitor will be used in organ monitoring through electrical impedance spectroscopy in the 100 Hz – 200 kHz range. The specific application is the study of the viability and evolution of engineered tissue in cardiac regeneration in an experimental protocol with pig models. The bioimpedance monitor includes a ZigBee transceiver to transmit the measured data outside the animal chest. The bioimpedance monitor is based in the 12 Bit Impedance Converter and Network Analyzer AD5933, improved with an analog front-end that implements a 4-electrode measurement structure and allows to measure small impedances. In the debugging prototype, the system autonomy exceeds 1 month when a 14 frequencies impedance spectrum is acquired every 5 minutes. The receiver side consists of a ZigBee transceiver connected to a PC to process the received data. In the current implementation, the effective range of the RF link was of a few centimeters, then needing a range extender placed close to the animal. We have increased it by using an antenna with higher gain. Basic errors in the phantom circuit parameters estimation after model fitting are below 1%. |
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ISSN: | 1742-6596 1742-6588 1742-6596 |
DOI: | 10.1088/1742-6596/224/1/012163 |