In the field of electronics design, designing a “best in
class” product with a competitive roadmap for the future is vital. For medical
designs, in particular, it is especially important to use the highest quality
components to ensure longevity, as these products go through long approval and
use cycles. To accomplish this, system designers need to design the “right
system.” But what does that mean?
I (Gene) have spent a good part of my career helping system
designers find the right digital signal processor (DSP) for their system. I
remember talking to a designer several years ago who was trying to cost reduce
a personal medical device. It was a relatively simple product to help an
individual remember to take their medicine. Their design used one of our DSPs,
probably a TMS320C5x. They were hoping to reduce the BoM cost to less than
$25.00. When we reviewed the options and their specific needs, we realized that
a DSP was not the best solution. At that time, we already had the MSP430
microcontrollers (MCU) and our speech product line in Texas Instruments’ portfolio. Our suggestion to
eliminate the DSP and all the necessary memory and analog to make it work and
replace it with an MSP430 and speech synthesis device reduced the BoM far
beyond the customer’s expectation. We walked away having designed out one of
our DSPs and the associated necessary circuits in favor of one of our much
lower cost MCUs. So we reduced the net revenue to us from about $20 per system
to less than $10 per system.
The reason I tell this story is to point out a very
important concept. That is, no matter what the tradeoffs are, a technology
vendors’ job is to make sure that the system designer is using the most
suitable parts for designing their system. Specifically, that means using the
right software running on the right embedded processor interfaced to the right
analog signal chain parts with the right power management.
This is not as easy as it sounds from a component point of
view. My goal at TI is to sell TI devices. But, it is my goal as a systems
expert to help the customer choose the best components for their system. That
means my job is to make sure that the system designer is using the best fit I
can find (i.e., within my portfolio of devices) and my portfolio consists of
the very broad range of parts that TI offers, including analog, embedded
processing, ASIC, RF, and power management. This full range of products allows
us to comfortably meet the needs of any specific system constraint with best-in-class
components. And as an added advantage, the ability to optimally integrate the
system’s chip set to fewer numbers with an end goal of one package (SiP) if not
one device (SoC). This is an ability not possible when using multiple vendors
or when using a vendor with a narrow product portfolio.
Choices
In any system design, there are always choices to be made. These choices begin
with the list of features and capabilities the system needs to have. For
example, when we think of medical products, we are actually thinking of a very
broad category of systems. Each end-equipment (system) has a different set of
features the end user needs. Table 1 is one way of looking at the broad market
of medical and breaking it down into four categories, each with similar high
level features and needs.
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Table 1
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Obviously, these are not the complete set of features for a
specific end-equipment but the table gives a flavor of what is important for
each of the segments. For example, it is important for a system to be ultra low
power in order to be successful as an implantable. Whereas, in a diagnostic
imaging system such as MRI or ultrasound, the primary need is performance. Underlying
these high-level features is a set of characteristics that distinguish each
segment from the others. The specific needs range from ultra low power to ultra
high performance in one aspect. Then the needs range from high reliability and
accuracy to relatively low accuracy and reliability. The cost of the components
is generally a small part of the overall system cost. What this means is that
there is no one solution that fits all medical applications. A wide range of
product offerings makes the task to assembling the right set of components
possible but, at the same time, difficult to do.
One way to begin the task of putting the right set of
components together is to start with a set of components that best fit the high
level needs of a specific end product. One way to go about that is to look at
interactive system block diagrams on vendors’ websites and check related
collateral with selection tables. But these are only starting points and need
to be refined into a specific set of right components for the application. The
process of finding the right parts may also require some consulting with the
application staff at the vendor or by a consultant. Additional resources, such
as user groups, customer support lines, and local application engineers can
make the process much easier than it first appears.
Example: Designing the ‘Right’
Ultrasound System
Ultrasound systems are a perfect example where the right
combination of embedded, analog, and power management components can enable
designs that surpass real-time image processing needs and power constraints.
Key criteria, including clinical purpose, size, function, power, and
time-to-market, drive the choices and trade-offs the designer makes when
choosing components for the ultrasound system. For instance, in high-end, cart-based
systems, image quality and performance are paramount, while in ultraportable
systems, power, cost, and size drive the design.
Image acquisition in ultrasound begins when a high-voltage
pulser and multiplexer excite a transducer of multiple piezoelectric elements
with high frequency, time-delayed pulses. As a result, the transducer transmits
acoustic waves that propagate through structures of varying densities and
acoustic impedances in the target (e.g. heart, liver). The difference in
impedance at structural boundaries dictates the intensity of waves
reflected/further transmitted. Through a transmit-and-receive switch like TI’s
TX810, the transducer is toggled into receive mode and converts the acoustic
energy into an analog signal.
Clinical end-use and form factor are key considerations in
transducer design. The number of elements in systems today typically varies
from eight to 512, with more channels translating to higher image quality but
also higher power consumption. Portable systems trade channel density for
greater battery life. The transducer’s center frequency varies in the 1 to 15
MHz range where higher frequency waves achieve higher resolution images but
trade-off penetration depth, since acoustic waves attenuate at about 1 dB/cm/MHz.
Lower operating frequencies are therefore more pertinent for applications like
abdominal imaging, while a transducer at, for example, 10 MHz is useful for
imaging superficial areas. The clinical application also influences the shape
of the transducer, where a curved transducer allows better resolution and a
broader field of view in applications like abdominal imaging, a sector
transducer is good for cardiac imaging and a linear transducer useful for
shallow depth imaging.
Next in the signal chain is the analog front end (AFE) which
improves sensitivity and dynamic range, performs time gain compensation to
account for signal attenuation, enhances the signal-to-noise ratio (SNR) and
converts the signal into the digital domain. To achieve this, the AFE typically
incorporates a low-noise amplifier, voltage controlled attenuator, programmable
gain amplifier, anti-aliasing filter and analog-to-digital converter. For
example, TI offers a broad range of fully integrated AFEs like the AFE58xx
range of pin-to-pin compatible devices that offer system developers various
feature sets to choose from, including tradeoffs between SNR and power
consumption.
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Once in the digital domain, the received echoes from the
transducer elements are delayed and summed based on the time delays used during
acquisition along a given line of sight or scan line. This process is known as
beamforming, with multiple scan lines forming an entire image frame. B-mode
data is interpreted to create a grayscale image that displays structural
details. For color flow data, which is associated with blood flow, each color
line is formed as a result of a number of pulses, also known as the ensemble
length. Next, beamformed data undergoes IQ demodulation, where it is down
converted to baseband through downmixing, is low pass filtered to eliminate
side lobes and then decimated. The decimated B-mode data additionally undergoes
envelope detection and logarithmic compression. The decimated color flow data
undergoes ensemble aggregation, followed by wall filter processing where a
high-pass filter reduces high-amplitude, low-velocity echoes from vessel walls,
and then color flow estimation that calculates the velocity, direction,
turbulence and power. Finally, the processed data is used to construct an image
through scan conversion, which interpolates data from the acquiring co-ordinate
system to Cartesian co-ordinate system corresponding to the display size on an
LCD screen.
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Deterministic execution, reliability, and low latency play a
key role in guaranteeing real-time processing, which is essential in any
ultrasound system design. In addition, software programmability allows
designers to reuse code through their portable to high-end product range. The
availability of specific peripherals and interfaces can also influence processor
choices. For example, a direct memory access can be very useful to perform data
movement between external memory/interfaces and internal memory, thus allowing
the CPU to focus on processing tasks.
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Table 2 Monitoring OMAP35x TLV320IAC3254 TPS CC2541 Imaging/ C6455 DDC118/232/264 TPS |
Ultrasound system designers look for the right balance
between performance, power, and cost based on product requirements like form
factor, data sizes, and functionality. Along with these considerations, it is
essential that ultrasound system designers bring their products quickly to
market and have the right set of tools and software components to evaluate
platforms and kick start development. Availability of software libraries, a
comprehensive software framework that allows easy plug-and-play of algorithms,
key APIs for tasks like inter-processor communication, and a real-time operating
system, ensure that ultrasound system designers spend most of their time
innovating and developing their secret sauce and less time in addressing
system-level issues. In addition, software libraries and system implementation
examples can provide a quick way for developers to evaluate the performance of
ultrasound-specific algorithms on various platforms and can also eliminate the
need to code these common building blocks.
Conclusion
Understanding the need, defining the product specifications based on this need,
and then choosing and integrating the right set of hardware and software
components are key steps in designing medical products. As the ultrasound
example illustrates, technology vendors can offer technical expertise,
collateral, knowledge, and a broad portfolio of solutions in analog, power, and
embedded processing with long lifetimes that can be leveraged to design
systems, from portable to high-end. System designers have a thorough
understanding of their application domain and the need they are trying to meet.
Working together, designers and their partners can find the “right” pieces of
the puzzle that form the “right” system that solves the “right” clinical needs.
References
D. Pradhan, “Multicore Processors bring Innovation to Medical Imaging,” White
Paper slyy024, Texas Instruments Inc, June 2010.
M. Ali, D. Magee and U. Dasgupta, “Signal Processing Overview of Ultrasound
Systems for Medical Imaging,” White Paper sprab12, Texas Instruments Inc, November
2009.
R. Pailoor and D. Pradhan, “Digital Signal Processor (DSP) for Portable
Ultrasound,” Appl. Note sprab18a, Texas Instruments Inc, December 2008.
U. Dasgupta, “Efficient Implementation of Ultrasound Color Doppler Algorithms
on Texas Instruments’ C64x Platforms,” Appl. Note sprab11, Texas Instruments
Inc, November 2008.
X. Li, “Ultrasound Scan Conversion on TI’s C64x+ DSPs,” Appl. Note sprab32,
Texas Instruments Inc, March 2009.
U.Gurnani and R. Pailoor, “Implementing Real-time Multidimensional Signal
Processing in a Multicore DSP Environment,” XV Simposio De Tratamiento De
Señales, Imágenes Y Visión Artificial STSIVA, September 2010.
V. Marques and M. Nadeski, “Designing Portable Ultrasound Devices,” Medical
Design Magazine, October 2009.
Texas
Instruments Embedded Processors Wiki, “Medical Imaging Demo Application
Starter,” Texas Instruments Inc, 2011. [Online]. Available: http://processors.wiki.ti.com/index.php/Medical_Imaging_Demo_Application_Starter_%28MIDAS%29.
Texas
Instruments Embedded Processors Wiki, “Keystone Device Architecture,” Texas
Instruments Inc, 2011. [Online]. Available: http://processors.wiki.ti.com/index.php/Keystone_Device_Architecture
Texas Instruments Website, “Medical Imaging Analog and Embedded Processing, Texas
Instruments Inc, 2011. [Online]. Available: http://www.ti.com/medicalimaging
Uday Gurnani is an applications engineer and Gene Frantz is
a principal fellow, both with Texas Instruments.
