Medical Communications for Combat
Casualty Care
John H. Benson, William A. Irizarry-Cruz, Jerrold E. Dietz, Jorge A.
Aviles, Christian D. Reid, M. Shane Stephens, and Kristen N. Steinman
edical Communications for Combat Casualty
Care (MC4) is the Army program responsible
for fielding information management/
information technology systems to document and process the medical care provided
to U.S. deployed forces. APL supported the MC4 Product Management Office for
more than 10 years in the areas of research, development, testing and evaluation, and
systems engineering and served as a trusted agent. APL’s contract with MC4 concluded
in February 2011.
MEDICAL COMMUNICATIONS FOR COMBAT
CASUALTY CARE PROGRAM OVERVIEW
Medical Communications for Combat Casualty
Care (MC4) is a U.S. Army Acquisition Category III
(ACAT III) program under the auspices of the Program
Executive Office for Enterprise Information Systems,
PEO EIS [formerly PEO Standard Army Management
Information Systems (STAMIS)]. MC4’s mission is to
integrate, field, and support comprehensive medical information systems, thus enabling lifelong electronic medical records, streamlined medical logistics, and enhanced
situational awareness for Army tactical forces. The MC4
Product Management Office receives functional, technical, and requirements oversight through the Office
of the Surgeon General, the Chief Information Officer of the Army Medical Department (AMEDD), and
the AMEDD Center & School, respectively. It receives
acquisition oversight through the Assistant Secretary
JOHNS HOPKINS APL TECHNICAL DIGEST, VOLUME 31, NUMBER 4 (2013)
of Defense for Networks and Information Integration.
Funding for the program is managed through the Office
of the Surgeon General, Army Information Systems, and
its Milestone Decision Authority is PEO EIS.
The MC4 Product Management Office integrates
the Defense Health Information Management Systems
(DHIMS) government-furnished software into the MC4
system. MC4 also provides new equipment training
and supports systems in theater and in garrison. MC4
also addresses all other Army-unique tactical medical
requirements.
HISTORY
During the Gulf War and other deployments, the
Army identified the need to find a way to central-
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ize medical records. In the past, medical records were
manually recorded on paper and often lost or destroyed
because of environmental conditions during an operational deployment. Because of incomplete or missing medical records, many soldiers are unable to apply
for Veterans Affairs benefits. In November 1997, the
National Defense Authorization Act identified that all
records of health-care services given to service members
in connection to a deployment must be maintained centrally to allow future access to those records. As a result
of the Special Report of the Presidential Advisory Committee on Gulf War Veterans’ Illnesses,1 the President
directed, “Every soldier, sailor, airman, and marine will
have a comprehensive, lifelong medical record of all illnesses and injuries they suffer, the care and inoculations
they receive, and their exposure to different hazards.”2
The same year, MC4 principles were established under
U.S. Code, Title 10 § 1074f, Medical Tracking System
for Members Deployed Overseas3 with the objective
to “. . . assess the medical condition of members of the
armed forces (including members of the reserve components) who are deployed outside the United States or its
territories or possessions as part of a contingency operation (including a humanitarian operation, peacekeeping
operation, or similar operation) or combat operation.”
MC4 was commissioned on 1 May 1999 with headquarters in Fort Detrick, Maryland.
MC4 was first deployed into combat operations at the
onset of Operation Iraqi Freedom in March 2003, with
initial deployments in Qatar, Kuwait, and Iraq followed
shortly after with deployments in Afghanistan as part of
Operation Enduring Freedom.
Since then, MC4 has expanded to include Special
Operations Forces in 2006 and the Air Force in 2007.
MC4 has also been deployed to Djibouti, Germany,
Japan, Kosovo, Italy, Philippines, Poland, Romania,
Thailand, and the United States. In January 2009,
President Barack Obama, in a speech to George Mason
University, stated, “To improve the quality of our health
care while lowering its costs, we will make the immediate investments necessary to ensure that within 5 years,
all of America’s medical records are computerized. This
will cut waste, eliminate red tape, and reduce the need
to repeat expensive medical tests.” There continues to
be a need to deploy and improve the capture and storage
of electronic medical records (EMRs).
APL INVOLVEMENT
In the fall of 1999, the Laboratory was approached to
discuss the possibility of providing technical assistance
for a newly formed Army medical program (MC4). Discussions continued, and the first task order from MC4
was received in the spring of 2000 with a period of performance from 1 May 2000 to 31 January 2001. The
Statement of Work included development of technical
302
requirements, Global Combat Support System–Army
(GCSS-A) interoperability modeling, and applications
interoperability and integration. APL delivered the first
version of the GCSS-A Medical Information Interface
Communications Component (MEDIICC) Operations
Concept Document in December 2000. In 2001, APL
continued supporting MC4 but at a reduced level of effort
until late 2002. A new contract established the creation
of an MC4 laboratory at APL for the evaluation of hardware and government off-the-shelf and COTS software.
APL also assisted MC4 with medical logistics and the
implementation of a database for government asset tracking. By the end of 2003, APL’s role in supporting MC4
had increased to seven full-time equivalent staff including test, requirements, logistics, and systems engineers in
addition to its key role as Technical Direction Agent.
In the spring of 2004, three APL engineers traveled
to Qatar and Kuwait to visit several U.S. military facilities and assess firsthand the operational, functional, and
environmental setting of MC4 systems in theater. This
resulted in a better understanding of the needs of end
users and the demands they place upon deployed systems. Consequently, APL’s systems engineering role in
support of the program greatly improved.
When Hurricane Katrina struck the Gulf Coast in
August 2005, MC4 deployed with the Army National
Guard. While deployed, APL engineers worked alongside the National Guard to support the humanitarian
operation. APL was also instrumental in identifying
software compatibility issues between MC4 systems and
the Future Combat System Medical Variant software
architecture. This resulted in an extensive trade study
effort that included several Army and contractor organizations, with APL participating as the technical representative (with voting rights) for the government (MC4).
Over time, APL has been instrumental in assisting
the MC4 Product Management Office to reach Milestone C, Full Rate Production, and Deployment and
Sustainment phases in its evolutionary acquisition strategy. To that end, APL closely collaborated with government personnel in the preparation of programmatic
documentation, developing MC4’s DoD Architecture
Framework-compliant system architecture, and ensuring
that MC4 systems maintained the levels of security and
software readiness required for deployment and integration within Army tactical networks. APL also conducted modeling and simulations of network topologies
for the Iraq and Afghanistan theaters4 to better forecast
communications needs as demand for bandwidth continued to increase. The increase was due to greater interest in telemedicine and the processing and distribution
of diagnostic-quality digital imagery.
In recent years, APL gradually transitioned from a
largely test and evaluation function to that of research
and development. APL explored a wide range of capabilities as part of a technology roadmap initiative coverJOHNS HOPKINS APL TECHNICAL DIGEST, VOLUME 31, NUMBER 4 (2013)
MEDICAL COMMUNICATIONS FOR COMBAT CASUALTY CARE (MC4)
ing future government off-the-shelf software products,
COTS hardware, telemedicine (telepresence, teleconsultation, and telesurgery), mobile technologies and communications [Warfighter Information Network-Tactical
(WIN-T), the Global Information Grid (GIG)], and
intelligent speech-to-text translation [hands-free (HF)
EMR]. Some of these are discussed later in this article.
These new capabilities, when applied to the medical
domain on the battlefield, hold promise for improving
warfighters’ survivability.
MOBILE TECHNOLOGIES
the creation of a medical encounter, also known as an
EMR. Once the encounter is generated, the handheld
device needs to be physically interfaced, or tethered, to
the nearest MC4 notebook running the tactical version
of AHLTA or AHLTA-T. This is the clinical application residing on MC4 systems for the documentation
and processing of outpatient medical records. The closest locations where these notebooks are accessible to
combat medics are in medical evacuation platforms like
ambulances or helicopters. Obviously, combat medics do
not always have immediate access to evacuation vehicles to upload pending EMRs into MC4 systems. More
importantly, the notebooks on the evacuation vehicles
lack direct connectivity to the NIPRnet. Therefore, the
medical records are not being processed to the central
In the spring of 2010, MC4 directed the Laboratory
to conduct an analysis of alternatives for Web portal
technologies to better manage
and implement remote access
capabilities of deployed systems.
The intent was to reduce the
time/man power required during
the distribution and/or update of
software releases to hundreds of
Army medical units in a theater
of operations. One striking conclusion of this analysis was the
possibility of a “lighter,” more
versatile architecture at tactical
Combat Support Hospitals in
theater. This new architecture,
optimized for more dynamic and
secure access to medical applicaFigure 1. Outpatient application on an iPhone 4.
tions residing on MC4 servers,
was conceived using technologies that are suitable for data
streaming over wireless communications networks.
The proliferation of mobile
technologies at a global scale, i.e.,
smart phones and tablets, provides
low-cost alternatives for implementing solutions applicable to
a tactical environment like the
Combat Support Hospitals. The
extended network capabilities
already available and forecasted to
expand could enable the remote
access to and from the lowest level
of care in the U.S. Army medical infrastructure—the point of
injury in the battlefield.
Currently, to document medical care in the combat zone,
medics are provided with a PDAlike device (handheld) that runs a
localized electronic version of the
field medical card (DD1380) for
Figure 2. Outpatient application on an iPad.
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repositories in the continental United States or to the
nearest medical treatment facility in a timely manner.
The Laboratory’s solution to the Web portal analysis
of alternatives included the Citrix XenApp application
for data streaming. Similarly, Citrix provides a client
application for mobile devices running Apple iOS and
Droid OS. APL saw this as an opportunity to implement
a remote connectivity capability for smart devices such
as iPhone, iPad, iPod Touch, HTC EVO, and Samsung
Epic over Wi-Fi or 3G networks to the centralized servers running AHLTA-T. In previous studies, the EMR
applications had issues with screen resolutions and various input methods. Initial tests at APL indicated that
the client was able to run and launch the applications
successfully on all platforms. Zoom capabilities and
screen size impose certain limitations for entering data.
However, the iPad device had the most successful tests
because of its screen size and clipboard-like configuration. Figures 1 and 2 show the outpatient clinical application currently used by Army tactical medical units
running on the iPhone 4 and iPad, respectively.
By allowing the operation of these applications on
smart phones or an iPad, medical personnel would have
a portable device they can use to easily input EMR
data while moving from bed to bed in a Combat Support Hospital or from anywhere, including the point of
injury, over global networks.
HANDS-FREE-ELECTRONIC MEDICAL RECORD
Medical first responders in today’s battlefield environments are equipped with technology to electronically
document medical care. However, these technologies
require providers to use their hands to perform the documentation. This solution is unsuitable because their
hands usually cannot be diverted from the casualty to
interact with the medical documentation device. Consequently, documentation is often not captured at the point
of injury. The unsuitable nature of the currently fielded
technology results in gaps in information that may have
been used to improve combat casualty care, medical situational awareness, and training. Furthermore, such gaps
may create voids in the lifelong medical records for service men and women who are injured in combat.
To address these issues, MC4 tasked APL to explore
the development of an HF EMR system for this operational environment. In addition to MC4, other stakeholders in the development of this HF EMR system
include the AMEDD, the Telemedicine and Advanced
Technology Research Center (TATRC), the U.S. Army
Institute of Surgical Research (USAISR), and the
Defense Advanced Research Projects Agency (DARPA).
Research into various methods of HF data entry
resulted in the selection of speech as the most mature
technology in today’s state of the practice. However, the
battlefield represents a challenging acoustic environ-
304
ment, requiring the development of a technical solution
to minimize the effects of ambient noise and preserve
the voice of the health-care provider. The recorded
voice must be intelligible enough such that a human, or
ideally an automated speech recognition (ASR) system,
coupled with a natural language processor, can convert
the unstructured recorded voice into a structured, mineable data record compatible with DoD enterprise-level
EMR systems such as AHLTA-T.
The objective of this study was to develop requirements for a HF processing system that creates an EMR at
all levels of Combat Casualty Care. HF EMR technology
has applicability across a wide range of programs such as
the Soldier as a System and the MC4 programs as well
as homeland civilian support operations. Accordingly,
there are a wide range of operational considerations
for this type of system including mobile (mounted and
dismounted), far-forward scenarios with harsh environmental conditions (including weather, noise, shock,
vibration, etc.), and clinical settings involving relatively
benign environments. Furthermore, because each of the
programs that may benefit from HF EMRs utilize a wide
range of computing platforms and networks, the technical considerations include multicomputing platform
applications (Windows, Linux, Embedded), near-realtime, accurate, complete medical records, and interoperability with other systems. The Laboratory’s approach
to this study involved a multiphase process for evolving
advanced technology to mature technical solutions that
meet operational requirements and produce requirements and specifications from which a production system
can be developed.
SYSTEMS ENGINEERING APPROACH FOR THE HF
EMR PROJECT
A disciplined system engineering process is required
to successfully develop such a complex system incrementally from generation to generation. The five steps
are shown in Fig. 3. MC4’s HF project reached Step 3—
technical performance evaluation of digital voice
recorder (DVR) technology—in the iterative research
and development cycle. A Measurement and Analysis
Plan describes a methodology for providing a performance baseline for a set of selected DVRs that are candidate solutions for this system.
EVALUATION STRATEGY
Initially, the evaluation focuses on the audio hardware and signal processing of the DVR, followed by
evaluation of downstream speech and language processing. Though the DVR and speech/language evaluations
can occur separately, they cannot be conducted entirely
independently of one another. For example, certain lanJOHNS HOPKINS APL TECHNICAL DIGEST, VOLUME 31, NUMBER 4 (2013)
MEDICAL COMMUNICATIONS FOR COMBAT CASUALTY CARE (MC4)
Objective
Threshold
Technology development
Performance feedback
Cycle requirements for improvement back to next-generation system
Step 5
Step 1
Step 2
Step 3
We are here
Fielded
system
Step 4
Downselect
Downselect
Operational
environment
Downselect
Technical Production,
solution
fielding,
sustainment
Prototype(s) demonstration test
– Test under near-operational environment
– Assess against performance metrics
Baseline performance testing
– Evaluate performance metrics
under unknown conditions
Identify technical solution alternatives
– Survey community (military, government, industry,
academia) for potential solutions
– Initial alternatives ranked based on alignment with
requirements and maturity
– Vet alternatives through SMEs
Requirements development
– Collect/document SME input
– Develop operational and technical performance metrics
– Develop data collection requirements for performance assessment
– Vet documented requirements through SMEs
• Program objectives and priorities drive
duration and scope of each step
(i.e., number of alternatives considered,
etc.)
• Data-driven process
• SMEs involved continuously from
the start
Figure 3. DVR roadmap. SMEs, subject-matter experts.
guage processors perform better than others at lower
speech-to-noise ratios. Additionally, different DVR systems may produce audio outputs with degraded speech
quality. It is up to the speech and language processors
to contend with a potentially low signal-to-noise ratio
and degraded speech quality. In order to compare the
intelligibility performance between DVRs, the speech
and language processors must present inputs from each
of the DVRs, where the DVRs have been subjected to
operationally relevant inputs (speech and noise).
Through a product survey using information (reports
and briefings) provided by industry, the candidate DVR
solutions were compared and assessed for further evaluation in a controlled laboratory setting. DVRs not
selected for initial laboratory testing may have an opportunity to be reconsidered during a subsequent development/assessment cycle.
As illustrated in Fig. 4, DVR speech intelligibility
evaluation involves several activities, including:
• Speech Corpus Collection: collection in a noisefree setting of human subjects reading prescribed
sets of words
• Sound Trials: collection in a sound-reproduction
facility of speech in the presence of simulated battlefield noise using the DVRs under evaluation
JOHNS HOPKINS APL TECHNICAL DIGEST, VOLUME 31, NUMBER 4 (2013)
• Speech Intelligibility Analysis: analysis of the data
collected during the sound trials with the goal of
ranking the performance of the DVRs
In addition to analyzing speech intelligibility, the
evaluation methodology also includes an assessment and
analysis of the spatial discrimination and signal-processing characteristics of each of the DVRs. An analysis of
the spatial discrimination is important. Operationally,
these devices will be used in environments where noise
is received at numerous angles and azimuths and the
ability of the devices to fixate on the speech signal in
the presence of this multidirectional noise field will be
key to assessing how well each device preserves speech
while rejecting noise. Additionally, technical characteristics such as dynamic range and interference rejection
are key to the performance of these DVRs and are also
included as evaluation criteria.
HF EMR RECENT ACCOMPLISHMENTS
High-Intensity Sound Test
The High-Intensity Sound Test (HIT) provides a
baseline evaluation of COTS voice recorders in support
of the HF EMR requirements development process. It is
reasonable to assume that COTS audio data may become
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J. H. BENSON ET AL.
Product surveys
Acoustic trials
Determine best of breed among
numerous potential technical solutions
MC4
DARPA
USAISR
TATRC
Speech intelligibility trials
Site: ARL/HRED (APG)
Contact mic corpus
Sound reproduction facility
Speech corpus
collection
Acoustic
recording WAV files
Human subject
listening analysis
Human subject listening
Sound trials
Speech
corpus
Talker(s)
Site: APL
Adjust
speechto-noise
ratio
Noise scenarios
DVR #1
Recordings
from each
DVR
100
Speech intelligibility
Site: APL
• Spatial processing
• Dynamic range and saturation
• Interference
80
DVR #1
60
DVR #2
40
DVR #3
DVR #4
20
DVR #5
0
Low
Med
High
Speech-to-noise ratio
Performance ranking
Figure 4. DVR evaluation strategy. ARL/HRED (APG), Army Research Laboratory/Human Research and Engineering Directorate (Aberdeen Proving Ground).
clipped or distorted under the acoustic environment of a
battlefield. The goal of the HIT was to evaluate clipping
and distortion by subjecting the COTS devices to sound
pressure levels that may be experienced on a battlefield: a peak pressure of 140 dB(P) (peak pressure) and a
root-mean-squared pressure of 120 dB(A) (A-weighted),
with both levels referenced to 20 µPa at 1 m. The HIT
was conducted at APL in two phases during July and
August 2010. Figure 5 shows the test configuration, a
schematic of the test procedure, and selected results. A
starter pistol was used to generate the peak sound pressure levels needed to measure clipping and can be seen
in the top picture. Narrow band-limited noise signals
were also transmitted at high sound pressure levels to
measure the harmonic distortion of the DVRs. Harmonic distortion was measured by comparing the DVR
recordings to a ground truth recording.
HIT Results
Initial indications showed that although transient
high-intensity noises may clip the COTS devices, many
of the devices recovered quickly and were less impacted
than originally thought. Steady-state loud noise, however, often distorted the recordings because of a nonlinear response of the microphone and preamp electronics
at such high levels. This distortion was quantified and
provided a ranking of the devices to be used as a downselect tool for evaluations.
306
ASR and Speech Intelligibility Risk Reduction Trials
The purpose of this test was to evaluate the performance of automatic speech recognition software to
transcribe (i.e., speech-to-text) audio recorded in austere
environments encountered by combat medics. All of the
audio files were recorded using commercial DVRs and
headsets under nominally equivalent environmental
conditions. The test conditions included noises selected
to resemble sounds heard on the battlefield during medical care (care under fire, tactical field medicine, medical/
casualty evacuation). The DVRs and headsets were worn
by active duty combat medics while they performed
simulated care as part of an operational demonstration.
This demonstration was the second of two conducted
by the Joint Medical Distance Support and Evacuation
Joint Capability Technology Demonstration project at
the Air Force Medical Evaluation Support Activity in
Fort Detrick (see Fig. 6).
The ASR evaluation method is shown schematically in Fig. 7. Human transcription of audio files will
be considered ground truth and compared with ASR
speech-to-text products. An independent listener with
a medical background manually transcribed each audio
file to text. These manual transcriptions were then
used as the ground truth for all analysis. The ASR tool,
Dragon NaturallySpeaking 9 Medical, processed the raw
audio files. This ASR tool specifically has a preloaded
medical vocabulary in addition to the ability to create
JOHNS HOPKINS APL TECHNICAL DIGEST, VOLUME 31, NUMBER 4 (2013)
MEDICAL COMMUNICATIONS FOR COMBAT CASUALTY CARE (MC4)
Calibration, sound level of background signals
• Pistol shots on axis with reference signal
• Pistol shots (on/off axis)
• Helicopter and automatic weapon sounds
• Rapid-fire pistol shots
Starter pistol Reference
Loudspeaker
signal
Ground truth Recorders
Analyzers
recording
Transmit tone
Loudspeaker
• Helicopter
• Machine gun
Crisp
High SPL
“wide tones”
Crisp
MC70
Ref mic
Frequency
Reference
tone
Frequency
Starter
pistol
Zoom
MC70
Ref mic
Edirol
iPhone
Zoom
HTC
Added distortion
HIT 1
HIT 2
Starter pistol
shots (first
and second)
Close-up of
first shot
Close-up of
second shot
Figure 5. HIT setup and analysis.
customized vocabularies. The text outputted from this
tool is then compared with the text ground truth using
ScLite. ScLite is a National Institute of Standards and
Technology software tool that matches like texts to
determine the word error rate (WER). The WER is calculated using the equation shown in Fig. 7.
An alternate method (objective) of evaluating speech
intelligibility known as the spectro-temporal modulation
index model was also investigated and compared with
the subjective method, i.e., the human subject listening
method, which was illustrated earlier (see Fig. 4, Speech
intelligibility trials). The spectro-temporal modulation
index model uses knowledge of neural mechanisms of
cortical auditory processing to formulate models that
address problems of speech intelligibility. Experimental
performance under certain noise conditions shows agreement with psychoacoustic analysis under the same condi-
JOHNS HOPKINS APL TECHNICAL DIGEST, VOLUME 31, NUMBER 4 (2013)
tions. A spectro-temporal modulation index model will
be evaluated using audio files collected during the speech
intelligibility trials at the Joint Medical Distance Support and Evacuation operational demonstration event.
FUTURE TESTS
DARPA selected and funded three companies for
Small Business Innovation Research program phase two,
development of DVR technology. These are to meet the
operational needs of the HF EMR. APL created a measurement and analysis plan to assess the performance
of the DARPA phase two vendors. Potentially, this will
also assess other DVR development candidates using a
common set of battlefield noise and speech samples.
Acoustic risk-reduction tests have provided insight
into the performance of COTS DVRs and useful distor-
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J. H. BENSON ET AL.
120 V of AC
power
Audio speaker cables
Audio
speakers
on tripods
Table and workbench
for sound generation
equipment (equipment
and tables to be
supplied by MC4
team) (~5 x 8 ft.)
Reference
microphone
on a boom
Medic work area,
~10-ft. diameter
•
Video to
augment
analysis
(videographer
supplied by
APL)
• Evaluate performance and suitability of COTS
and prototype DVRs and ASR software
• Refine data collection and analytic procedures
• Prepare for a future demonstration of a
prototype natural language processor
• Gain insight into U.S. Army Medic tactics,
techniques, and procedures to inform requirements and concept of operations development
for HF EMR
• Three COTS devices
• Define ASR metrics
Figure 6. Speech intelligibility field trial at the Air Force Medical Evaluation Support Activity in Fort Detrick.
tion metrics appropriate for evaluating DVRs in future
acoustic trials. Although analysis of the speech intelligibility risk reductions trials is ongoing, it is safe to assume
that an increase in distortion observed in the HITs will
cause a decrease in speech intelligibility. Through literature research and future testing, APL plans to develop
intelligibility scores as a function of distortion. If APL
can develop confident unambiguous relation curves,
these can be used to predict device performance and
reduce the need for human subject testing.
Upon completion of the acoustic and speech intelligibility assessments, APL has the capability to field
Medic speech
prototype HF EMRs with Army medics during training
evolutions in order to assess the operationally suitability
of the candidate technical solutions. As sensor technology matures, alternative input modalities such as gazedriven or brain sensors may be incorporated into the HF
EMR system in order to improve the accuracy and speed
of recording point-of-injury medical documentation.
SUMMARY
During the course of the MC4 contract, APL focused
on protecting the interest of the government and ensur-
Speech with noise
ASR software
A king ruled
the state in
the early days.
Text output
A king ruled the stake
in dearly days.
Dragon 9 Medical
WER = (S + D + I)/N
• S, number of substitutions
• D, number of deletions
• I, number of insertions
• N, number of words in the reference
For this example, WER = (2 + 1 + 0)/9 = 33%
• Lower scores are better
Compare output
with original text
ScLite: Speech Recognition Scoring Toolkit
(National Institute of Standards and Technology)
• Standard tool for calculating WER
Figure 7. ASR software assessment method.
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MEDICAL COMMUNICATIONS FOR COMBAT CASUALTY CARE (MC4)
ing that every aspect of the APL effort was oriented to
safeguard the integrity of the warfighter. At the conclusion of the contract, it is clear that several initiatives are
still a work in progress. These include the technology
roadmap, mobile devices, and the HF EMR. APL’s transition plan included specific recommendations to the government for the continuation of these initiatives. The
need for an HF capability at the combat medic level has
been documented and is well known. The HF research
and development completed by APL is an example of
how this technology can be deployed in a diverse combat
setting. The opportunity for the Army to achieve this
capability has been fully demonstrated by APL.
ACKNOWLEDGMENTS: APL supported the MC4 program for
more than 10 years. During this period, there were many
people, some no longer at the Laboratory, who contributed to the success of this effort. We thank Mickey Sullivan and Pam Smith, first Program Manager and Project
Manager, respectively, who recognized the humanitarian
aspect of the program and paved the road through difficult times in the initial years. We thank Karin Marr for her
true “trusted agent” commitment and dedication, which
resulted in a remarkable expansion of APL’s involvement
with MC4 in years following. We thank Ted Nieman for
his vision and leadership as the last MC4 Project Manager
and for inspiring the sponsor to recognize the impor-
The Authors
tance of a program technology roadmap. We thank Alan
Ravitz, Deborah Mendat, Monica Waters, Bob Hannon,
Jim Sari, Dave Vespoint, and John Sweeney, who collectively took the initial steps for the HF EMR research and
development task. We recognize the contributions of
the Communication and Networking Technology Group
for sharing their expertise and resources in the development of the network models and simulation studies. We
also thank MC4 team members Michael Vermilye, Walter
Hsu, Robert Narh, Shane Stephens, Keisha Garret, Annette
Formbly, Rae Mason, Thomas Johnson, Cindy Owca, Joe
Wolfrom, Carol Yates, Beth Magen, Jessica Gilligan, Chuck
Louie, Kristen Steinman, and Nguyen La for their unwavering dedication and professionalism exhibited over the
years, which have contributed to the success of the MC4
program in so many areas.
REFERENCES
1Lashof,
J. C., Presidential Advisory Committee on Gulf War Veterans’
Illnesses: Special Report, The Committee, Washington, DC (1997).
on the Special Report of the Presidential Advisory Committee on Gulf War Veterans’ Illnesses,” Weekly Compilation of Presidential Documents 33(46), 1757–1758 (1997).
3Medical Tracking System for Members Deployed Overseas, 10 U.S.C.
§ 1074f (2011).
4Pattay, R., Moy, D., Kim, P., Munjal, S., and Aviles, J., “Analysis of
Teleradiological Data Transmission in Iraq by Modeling and Simulation,” in Proc. IEEE Military Communications Conf., Boston, paper
900271 (2009).
2“Statement
The lead and principal engineer, John H. Benson, is a member of the APL Principal Professional Staff and a registered
Maryland Engineer in the Research and Exploratory Development Department (REDD). He orchestrated the HF research
and development, providing expert management and advice throughout the task. William A. Irizarry-Cruz, a software
engineer in APL’s Asymmetric Operations Department, has been a key contributor in two areas. He was the principal
architect in the design and integration of the software and hardware components for the proof-of-concept HF EMR
system. He also developed and defined an evaluation method for assessing the intelligibility of DVRs. Jerrold E. Dietz is
a senior research engineer in REDD with more than 9 years of experience in undersea warfare, homeland protection, and
biomedical research. Mr. Dietz defined test and evaluation procedures for the analysis of current and future technologies.
Jorge A. Aviles, also of REDD, is a Senior Systems Engineer with more than 10 years of APL experience. Mr. Aviles
provided overall systems engineering analysis and support to MC4 throughout the duration of the program at APL.
Christian D. Reid is a retired Army combat medic with 26 years of medical experience. Mr. Reid guided a combat,
common sense approach to what the ultimate solution should provide for the combat medic. His insight was invaluable to
the success of this task. M. Shane Stephens, a former network engineer at APL, provided technical communications and
network expertise for the overall interaction of the test. Kristen N. Steinman is an APL Associate Staff member in the
Global Engagement Department. For this project, she was responsible for researching experimental designs, performing
an analysis of variance, evaluating DVRs in an analysis of alternatives report, and assisting with testing efforts. For
further information on the work reported here, contact John Benson. His e-mail address is john.benson@jhuapl.edu.
The Johns Hopkins APL Technical Digest can be accessed electronically at www.jhuapl.edu/techdigest.
JOHNS HOPKINS APL TECHNICAL DIGEST, VOLUME 31, NUMBER 4 (2013)
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