An energy-efficient wireless data link for implantable electronics
Author(s)
Kumar, Daniel Prashanth
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Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Rahul Sarpeshkar.
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Low-power wireless links are important for the development of long-term implantable neural prostheses. Furthermore, in implanted systems with many neural recording electrodes, the data rate of the wireless link will need to be quite high since each recording electrode can produce about 120 kbps of data. For low-power operation, inductively-coupled near-field wireless links have shown great promise and were used to develop a power-efficient data link for biomedical implants. A prototype bi-directional, half-duplex wireless link based on inductive coupling was designed in a 0.18 [mu]m process. The uplink (i.e. data transmission from the internal transceiver) was designed to use an impedance modulation strategy. Since this technique only requires a single local oscillator (LO) in the external transceiver, the energy expenditure of the implanted transceiver is minimized. Simulated uplink data transfer rates of up to 10 Mbps has been shown. A PWM based ASK coding strategy was used for the downlink (i.e. data transmission to the implanted device). The downlink is able to achieve a data transfer rate of up to 1.5 Mbps. A technique to reduce BER of inductive coupling links due to pulse-width distortion effects by pre-distorting the transmitted data is also presented. A calibration technique to reduce the resonant frequency mismatch between the two magnetically coupled resonators is also shown.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. Cataloged from PDF version of thesis. Includes bibliographical references (p. 101-103).
Date issued
2009Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.