Ultra-low-power circuits and systems for wearable and implantable medical devices
暂无分享,去创建一个
Advances in circuits, sensors, and energy storage
elements have opened up many new possibilities in the health
industry. In the area of wearable devices, the miniaturization of
electronics has spurred the rapid development of wearable vital
signs, activity, and fitness monitors. Maximizing the time between
battery recharge places stringent requirements on power consumption
by the device. For implantable devices, the situation is
exacerbated by the fact that energy storage capacity is limited by
volume constraints, and frequent battery replacement via surgery is
undesirable. In this case, the design of energy-efficient circuits
and systems becomes even more crucial. This thesis explores the
design of energy-efficient circuits and systems for two medical
applications. The first half of the thesis focuses on the design
and implementation of an ultra-low-power, mixed-signal front-end
for a wearable ECG monitor in a 0.18pm CMOS process. A mixed-signal
architecture together with analog circuit optimizations enable
ultra-low-voltage operation at 0.6V which provides power savings
through voltage scaling, and ensures compatibility with
state-of-the-art DSPs. The fully-integrated front-end consumes just
2.9[mu]W, which is two orders of magnitude lower than commercially
available parts. The second half of this thesis focuses on
ultra-low-power system design and energy-efficient neural
stimulation for a proof-of-concept fully-implantable cochlear
implant. First, implantable acoustic sensing is demonstrated by
sensing the motion of a human cadaveric middle ear with a
piezoelectric sensor. Second, alternate energy-efficient electrical
stimulation waveforms are investigated to reduce neural stimulation
power when compared to the conventional rectangular waveform. The
energy-optimal waveform is analyzed using a computational nerve
fiber model, and validated with in-vivo ECAP recordings in the
auditory nerve of two cats and with psychophysical tests in two
human cochlear implant users. Preliminary human subject testing
shows that charge and energy savings of 20-30% and 15-35%
respectively are possible with alternative waveforms. A
system-on-chip comprising the sensor interface, reconfigurable
sound processor, and arbitrary-waveform neural stimulator is
implemented in a 0.18[mu]m high-voltage CMOS process to demonstrate
the feasibility of this system. The sensor interface and sound
processor consume just 12[mu]W of power, representing just 2% of
the overall system power which is dominated by stimulation. As a
result, the energy savings from using alternative stimulation
waveforms transfer directly to the system.