Online proceedings - EDA Publishing Association

11-13
May 2011, Aix-en-Provence, France
especially fully implantable systems have a rather rigid
design in terms of system architecture and therefore
functionality. Actually the presented digital system tries to
combine key advantages of the measurement systems listed
in the first chapter: our digital system incorporates the
flexibility of the Hermes-system, the aim of a fully
implantation similar to the NRM - but without the cranial
unit and therefore without the percranial cable - and the
high degree of integration similar to the INI-chip, at least
Fig. 9. Waveform view of recorded sine waves from the prototype [6]. for the digital system planned to included in an ASIC.
After the target is met, the system still keeps its flexibility
for future applications without any modifications necessary.
If for some reasons a rigid system in terms of performance
is needed, it is also possible to adapt the system on
hardware base with a relative low effort, since all
performance parameters are already known from the
evaluation process.
Due to the serial data handling and the fact that undesired
measurement data and a lot of protocol overhead is removed
in an early stage regarding signal propagation, the system
has an increased performance with a low hardware
complexity and therefore a reduced power demand.
The flexibility of the system allows the user to fill the
limited transceiver bandwidth with the best fitting product
of resolution, number of channels and sample frequency,
with respect to the particular application.
A. Future Work
Future work will concentrate on the ongoing increase in
integration of all electrical components in order to achieve
the goal of a fully implantable neural measurement micro
system.
The final goal is a single chip solution incorporating the
whole signal path starting from the passive electrode/needle
ending at the RF-Transceiver interface. To satisfy the
demand in higher numbers of electrodes and thereby an
increase in neural data, one has to think about sophisticated
ways of data reduction without losing any neural
information. A reduction in data rate through data
compression also reduces the power consumption of the
measurement system.
Besides the flexibility in performance, it is also desirable
to have a certain degree of redundancy if some parts of the
system are malfunctioning. This redundancy has a direct
influence on the system reliability, which is crucial for a
non-removable fully implantable medical device. So the
“perfect” system consists of several measurement units,
each totally autonomous in terms of power supply and data
link, carrying all the flexibility described in this paper.
In this manner one gets a measurement system where
each electrode is connected to at least two-subsystems, so
there is a fairly high chance that each electrode is at least
represented once in the overall system, able to propagate its
neural data through the neural measurement system.
B. Compared to Other Work
Compared to other work, the work presented in this
paper has a significant degree of flexibility. Other systems,
ACKNOWLEDGMENT
The authors would like to thank the German Federal
Ministry of Education and Research (BMBF) for
subsidizing this work within the KALOMED-project. Also
the authors would like to thank Mr. Opel for his valuable
support in technical implementation of the FPGA-based
prototype.
REFERENCES
[1] Y.-K. Song, D. A. Borton, S. Park, W. R. Patterson, C. W. Bull, F.
Laiwalla et al, “Active Microelectronic Neurosensor Arrays for
Implantable Brain Communication Interfaces,” in IEEE Trans. on
Neural Systems and Rehabilitation Engineering, vol. 17, no. 4,
August 2009, pp. 339-345.
[2] Henrique Miranda, Vikash Gilja, Cindy A. Chestek, Krishna V.
Shenoy and Teresa H. Meng, “HermesD: A High-Rate Long-
Range Wireless Transmission System for Simultaneous
Multichannel Neural Recording Applications,” in IEEE Trans. on
Biomedical Circuits and Systems, vol. 4, no. 3, June 2010, pp. 181-
191.
[3] Reid R. Harrison, Ryan J. Kier, Cynthia A. Chestek, Vikash Gilja,
Stephen Ryu, Bradley Greger et al, “Wireless Neural Recording
with Single Low-Power Integrated Circuit,” in IEEE Trans. on
Neural Systems and Rehabilitation Engineering, vol. 17, no. 4,
August 2009, pp. 322-329.
[4] “RHA2116 – Fully Intergated 16-Channel Biopotential Amplifier
Array”, intan Technologies, LLC, Datasheet, 19 May 2010.
[5] Generated with the assistance of cadence-SimVision ©.
[6] Generated with the assistance of LabView 2010 from National
Instruments©.
Contact: Jonas Pistor, Institute of Electrodynamics and
Microelectronics (ITEM.me) University of Bremen, Otto-
Hahn-Allee, NW1, 28359, Bremen, Germany, +49 421 218-
62539 Email: pistor@me.uni-bremen.de
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