Final Report
SMART MATTRESS SYSTEM FOR PATIENT IDENTIFICATION
AND BEDSORE PREVENTION
ECE4007 Senior Design Project
Section L03, Koblasz
Smart Mattress Team
Bryan KuoPriyen PatelDev ShahXitij Shah
Tim Stamm
SubmittedDecember 11, 2008
Smart Mattress (ECE4007L03)
TABLE OF CONTENTS
Executive Summary.......................................................................................................... iii
1. Introduction....................................................................................................................11.1 Objective ...........................................................................................................11.2 Motivation .........................................................................................................11.3 Background .......................................................................................................2
2. Project Description and Goals .....................................................................................2
3. Technical Specification..................................................................................................3
4. Design Approach and Details4.1 Design Approach ...............................................................................................44.2 Codes and Standards........................................................................................114.3 Constraints, Alternatives, and Tradeoffs .........................................................11
5. Schedule, Tasks, and Milestones.................................................................................12
6. Project Demonstration..................................................................................................13
7. Marketing and Cost Analysis7.1 Marketing Analysis...........................................................................................137.2 Cost Analysis ...................................................................................................14
8. Summary........................................................................................................................16
9. References......................................................................................................................17
Appendix A........................................................................................................................19
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EXECUTIVE SUMMARY
Infections acquired in hospitals cost the healthcare industry billions of dollars each year
and result in numerous preventable deaths. These infections can result from patients developing
bedsores due to lying stationary for an extended period as well as lying on wet sheets. Another
issue is mistaking the patient in the bed for the wrong patient and giving incorrect medication or
treatment. To prevent these overlooked problems, the Smart Mattress verifies the correct patient
is occupying the bed, detects patient movement, and senses the presence of moisture.
Proper patient identification was accomplished by displaying the patient’s name, patient
ID, doctor’s name, and unique ID barcode on a PC monitor using RFID to read data from the
patient’s wrist or ankle tag. An array of pressure sensors was used to monitor patient movement
and warn staff when a patient needed to be moved. To detect moisture, a disposable mattress
using a conductive pattern between the top paper layer and the bottom biodegradable plastic
layer was placed on the bed. Since polymer, reinforced paper loses its strength when wet, air-
laid paper widely used in hospital applications safely provides a flexible, and low cost
alternative.
The demonstration for the Smart Mattress took place in a classroom of the Van Leer
building located on the Georgia Institute of Technology main campus. The functionality of the
mattress was tested by simulating several possible scenarios that could occur in a typical patient
room. Specifically, a test “patient” went through scenarios demonstrating the functionality of the
wetness detection system, the movement detection system, and the patient identification system.
When the system is mass-produced, the cost of each unit will be $1,765. With the system
being so cheap, a profit margin of 15 percent results in a final selling price of $2,030.
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1. INTRODUCTION
Nosocomial infections, which are infections acquired in hospitals are prevalent at a rate
of about 9.8 percent per every 1000 days that a patient spends in the hospital. These infections
cost the healthcare industry $4.5 billion and caused 88,000 deaths in 1995 [1]. These infections
can result from patients developing bedsores from lying stationary for an extended period or
wetting the bed. In other instances, the patient in the bed is mistaken for the wrong patient and
given incorrect medication or treatment. To prevent these overlooked problems, the Smart
Mattress verifies the correct patient is occupying the bed, detects patient movement, and senses
the presence of moisture.
1.1 Objective
The purpose of the project was to design an inexpensive mattress system that prevents
bed-related nosocomial infection and identifies occupants. The proposed features were that the
mattress should be able to detect occupant movement; the mattress cover should be able to detect
the presence of moisture. Pressure and moisture sensors connected to a system that will notify
hospital staff in the event of a problem. The mattress should also identify the patient and display
the patient’s name and barcode on a monitor for easy and secure medicine distribution. This
product’s target consumers were to be hospitals, clinics, and nursing homes.
1.2 Motivation
According to the CDC, 2 million people are infected with nosocomial infections every
year. Increasingly, patients are contracting MRSA infections, which are harder to treat with
antibiotics, as they are more resistant than normal bacterial infections [2]. Infection rates vary
between hospitals and nursing homes, but on average, 10 percent of hospital patients contract an
infection, while the average rate in nursing homes is 25 percent [3].
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Though other smart beds are available to hospitals, these beds have many extra features
not required by hospitals that already have equipment to perform these functions. The Smart
Mattress will operate using stand-alone devices to be cost-effective.
1.3 Background
Several different designs for smart beds are used to reduce the pressure on the patient [4].
The problem with the smart beds on the market is they are expensive and only prevent bedsores
by detecting patient inactivity, overlooking bed-wetting, which is also a major cause of bedsores.
In recent years, expansive research in the commercial uses of RFID has led to major
advances in the healthcare industry. The market for RFID tags and systems in healthcare is
expected to grow to $2.1 billion by 2016 [5]. In the hospital environment, it is important for the
doctor to be able to access a patient’s information as fast as possible in case of an emergency, or
to ensure the correct patient is given the correct medication.
2. PROJECT DESCRIPTION AND GOALS
The Smart Mattress was supposed to integrate seamlessly patient identification and bed sore
prevention into a typical hospital bed by doing the following:
Identify patients using RFID
Display patient information and barcode on a PC monitor
Detect moisture and pressure that could create bed sores
Alert staff if patient is in danger of developing bed sores
The Smart Mattress was to be equipped with a RFID receiver to communicate with wrist or ankle
tags worn by the patient. Once the patient was identified, an external PC monitor displayed the
name of the patient, patient ID, doctor’s name, and unique barcode that when scanned displays to
hospital staff the correct medications to administer. Pressure and wetness sensors also located in
the Smart Mattress detected the presence of fluid and monitor pressure changes. If the patient is
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in danger of developing bedsores, the hospital staff was alerted. The expected unit price of the
Smart Mattress is $2,030, which is cost-effective in the target market of hospitals and nursing
homes.
3. TECHNICAL SPECIFICATIONS
The following table shows the proposed and actual technical specifications for the
technology used to design the Smart Mattress. The previous passive RFID system did not meet
our range detection specifications. An active RFID system proved to be a better alternative as it
has a maximum antenna detection range of 35 ft. that is adjustable. A range of three feet was set
for the tags, as this range was sufficient for the purposes of detecting the patient lying on the bed.
The antenna for the RFID detection system was placed between a 2.5-inch thick high-
density memory foam and 1.5-inch thick low-density foam pad. The placement of the RFID
antenna in between the two-foam mattress pads and near the bottom of the bed provided the best
orientation for detecting a tag worn by the patient around the ankle. The antenna’s large and
adjustable maximum detection range of 35 ft secures that a three feet range is attainable. The
frequency of 433 MHz was chosen due to the commonality of equipment at this specification.
This high frequency is required so as to not interfere with other hospital equipment. Figure 1
shows the ranges that the RFID tags were detected based on the tag plane orientation; the degree
measurements were made from the vertical (positive Y) axis. Table 1 shows the specifications
that were proposed compared to the final specifications of the Smart Mattress.
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Figure 1. RFID tag orientation
Table 1. Technical Specifications
The inactivity monitoring system was implemented using four Force Sensing Resistor
(FSR) strips to measure the pressure applied by the patient to the mattress. The pressure strips
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were placed between the two foam mattresses on a cardboard base. The sensitivity range of the
pressure strips was calibrated by varying the voltage dividers connecting the strips to the Phidget
interface kit. Modifying the pressure range allows the pressure strips to measure up to 1,000 lbs.
4. DESIGN APPROACH AND DETAILS
4.1 Design Approach
The Smart Mattress project is comprised of patient identification and bedsore prevention
features. Patient identification will be accomplished using an RFID system, and bedsores will be
prevented by coupling movement and wetness monitoring systems. Each system will be
implemented separately using previous groups’ design solutions, and then modified in order to
combine them into a full product package.
Patient Identification
Proper patient identification will be assured by displaying the patient’s name, patient ID,
doctor’s name, and unique medication ID barcode on a PC monitor using RFID. The RFID
system will have four components: active RFID tags, antenna, a 433 MHz transceiver, and a
patient ID database.
Each tag has a unique ID corresponding to the tag’s owner. The RFID transceiver signals
the tag through an antenna. Upon receiving the transmitted signal from the antenna, the inner
circuitry in the tag returns the unique signal representing the binary ID assigned to each patient.
The response signal is detected by the antenna, decoded in the transceiver, and then processed on
a PC.
Once the transceiver detects a tag, the serial number of the tag is compared to a patient ID
database on the PC. In this database, information such as the patient’s name will be stored. A
bar code will be generated based off the patient’s unique ID. The patient’s name, patient ID,
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doctor’s name, and unique bar code will then be displayed on a PC monitor to help secure proper
medication delivery.
Bedsore Prevention
An array of pressure sensors are used to monitor patient movement and warn hospital
staff when a patient needs to be moved. Movements are monitored using the algorithm shown in
Figure 2. The movement monitoring system serves three main purposes. The system prevents
bedsores by detecting significant movements by the patient, or lack thereof. To accomplish this,
the system utilizes the four Trossen Robotics Force Sensing Resistors, which are located
equidistant from each other, to calculate the patient’s center of mass. The following is the center
of mass equation used.
(0*F1 + 1/3*F2 + 2/3*F3 + F4)/( F1 + F2 + F3 + F4) where FX is the force on strip X Eq. 1
In our system, a significant movement is defined as a 20 percent change, in either direction, from
the stored center of mass calculation. Finally, the patient monitoring system displays an alarm on
the monitor instructing staff to move the patient if the patient is inactive for more than 30
minutes.
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Figure 2. Movement detection algorithm.
The pressure sensing was carried out by several force sensing resistors (FSR) from
Trossen Robotics. The FSR functions by decreasing its resistance with an increase in force. The
sensitivity of the FSR was adjusted using a voltage divider, which was then interfaced with a PC
using the Trossen Robotics Interface Kit; all three of these components are shown in Figure 3.
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Figure 3. (a) TR Voltage Divider, (b) TR Phidget Interface Kit, (c) Force Sensing Resistor.
Figure 4 shows how the FSRs were laid out in relation to the patient and the mattress.
Figure 4. Pressure sensors on Smart Mattress.
The middle area of the bed is the best spot to put the pressure sensors because this is the area of
the body where bedsores are most likely to develop [6]. The FSRs will be placed in the bed so as
not to allow the sensors to bend.
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Wetness Detection System
A mattress cover consisting of two conductive loops was created in order to detect
wetness on the patient bed. The two conductive loops were made using conductive pieces of
tape. These two conductive loops, which are located near the middle region of the bed, were the
inputs into our wetness detection circuit. Combined with the patient inactivity monitoring
system, the wetness detection system greatly reduces the chances of developing bedsores. The
following sections describe how the conductive pattern and wetness detection circuit were
designed.
Conductive Pattern
The conductive pattern and the wetness detection circuit used on the prototype can be
seen in Figure 5 below. The two conductive loops are interfaced with the wetness detection
circuit using four leads at the edge of the mattress. Wetness is determined by monitoring the
output of the wetness detection circuit. Essentially, if the patient urinates on the bed (or wets the
bed in some other manner) the two conductive loops are shorted. Once the loops are shorted, the
output voltage of the wetness detection circuit is modified. The following section explains how
the wetness detection circuit was constructed and how wetness between the two conductive loops
affects its output.
Figure 5. Picture of conductive loops on prototype.
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Wetness Detection Circuit
The wetness detection circuit is shown in Figure 6 on the next page. As seen in the
figure, the wetness detection system consists of two 9V batteries, 6 resistors, and two
comparators. The conductive loops are in series with R2. Once the bed becomes wet, essentially
shorting the two conductive loops, R2 is bypassed. The shorting of R2 leads to a high output
voltage for the top comparator. This high output voltage is then processed by the Phidget 8/8/8
interface kit analog input sensor and the PC, and a “wetness alarm” is displayed for nurses to
view.
Phidget 8/8/8 Interface Kit
A Phidget 8/8/8 interface kit was used to interface the inactivity monitoring system and
the wetness detection system with the HP Slimline PC. Initially a PIC microcontroller was
proposed to integrate all aspects of our design together. Due to time constraints, implementing
the PIC microcontroller was not feasible, therefore the Phidget Interface Kit was utilized for the
Figure 6. Wetness and broken lead detection circuit.
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prototype.
Five of the eight analog inputs of the Phidget Interface Kit will be utilized to integrate the
wetness and inactivity detection systems. Four of these analog inputs will be dedicated to
monitor the 4 Trossen Robotics FSRs while one of them will be used to sample the wetness
detection circuit output.
4.2 Codes and Standards
The RFID technology implemented in the Smart Mattress system must meet the stringent
codes and standards of typical hospital equipment. RFID antennas pose a threat to patients if they
transmit a high-powered signal near patients. To minimize the power radiated by the RFID
antenna, the distance between the antenna and its receiver needed to be minimized. Several tests
were performed to determine the appropriate proximity of the antenna with respect to the
receiver in order to avoid harm to medical patients occupying the Smart Mattress.
Furthermore, the RFID system had to meet electromagnetic compatibility (EMC)
standards to prevent the interference with other significant medical equipment [8]. Specifically,
the RFID system must meet the standards specified by SC 31, which state that “device
manufacturers claiming conformance to this standard shall self-certify that RF emissions and
susceptibility comply with IEC 60601-1-2” [9]. The operating frequency of the RFID system
integrated in the Smart Mattress is 433 MHz; therefore, it meets the EMC requirements for
medical devices.
The active RFID system also had to meet transmitting range standards. In order to make
sure the RFID transceiver was not reading a patient tag in another room, testing was conducted
to verify that the transmitting range was not too large. Furthermore, testing was also done to
ensure that the transmitting range of the active RFID system would not read other patient tags in
rooms with multiple patient beds. According to tests, which are highlighted in Figure 1, the
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detection range was not greater than 4 ft. in either direction with respect to the transceiver. This
range would allow the transceiver to read tags on the bed, but not around the bed where other
patient beds might be located.
4.3 Constraints, Alternatives, and Tradeoffs
Alternatives to moisture detection systems exist, while complete wetness detection
systems requiring no assembly can be purchased. These systems often come with detailed
instructions and software to interface with a PC. However, a moisture detection system built by
the team will cost less because it can be created using cheap components that are easily
obtainable. This system can also be modified to interface with different hardware components.
Because cost and flexibility are important considerations in this project, the team-built moisture
detection system offers more advantages than a retail system.
Homemade RFID antennas present a different situation. Making an antenna is cheaper
than buying one. However, buying an antenna decreases the amount of time needed to design
and build the patient identification system because the antenna is ready to be used as soon as it
arrives. This project is a prototype, so keeping the project within time constraints is more
important than reducing costs.
5. SCHEDULE, TASKS, AND MILESTONES
The prototype of the Smart Mattress was built according to the timeline given below.
Table 2. Project Timeline
WBS
Task Name Duration
Start Finish Difficulty
Responsible Person
1 Define Project 21 days 8/18/2008
9/15/2008 Easy All Members
2 Acquire Parts 5 days 9/15/2008
9/19/2008 Easy All Members
3 Implement Microcontroller 11 days 9/22/2008
10/6/2008 Medium Tim
4 Implement Bed Sore Detection 29 days 9/22/2008
10/30/2008
High Bryan, Priyen, Xitij
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The team was divided into two subgroups that worked concurrently. Bryan, Priyen, and Xitij
focused on the bedsore prevention system. Dev and Tim concentrated on the patient
identification system. The subgroups met several times a week to work on tasks, and the
complete team met at least twice a week with the project adviser to discuss progress, problems,
and solutions. Both subgroups separated the tasks into subtasks to define responsibilities. These
are shown in the Gantt chart in Appendix A.
Construction of the Smart Mattress began on September 22. The hardware was installed
first. By October 13, both systems were ready to be tested and debugged independently. The full
system was assembled and was ready for demonstration by December 5th, 2008.
6. PROJECT DEMONSTRATION
The Smart Mattress was demonstrated in the senior design lab of the Van Leer building
located on the Georgia Institute of Technology campus. The team initially gave a power point
presentation explaining the background information, general functions and underlying
technology of the Smart Mattress. The functionality of the mattress was then tested by simulating
several possible scenarios that could occur in a typical patient room. Specifically, a test “patient”
went through scenarios that test the functionality of the wetness detection system, the movement
detection system, and the patient identification system. For example, to test the wetness detection
system, a team member poured water on the mattress. When the system detected the wetness, the
wetness alarm turned on to notify a nurse that the mattress was wet. The “patient” also simulated
cases that tested how these different systems (wetness detection, pressure detection, RFID, and
PC monitor) interact with each other.
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7. MARKETING AND COST ANALYSIS
7.1 Marketing Analysis
Many healthcare companies have developed “intelligent” patient beds in response to the
increasing occurrence of nosocomial infections. For example, TRADEWIN manufactures an
Alternating Pressure Mattress System that monitors pressure distribution and modifies airflow to
help prevent bedsores. The TRADEWIN 3000 8” Alternating Pressure Mattress system is sold
for $1,350 per unit [10]. MED-AIRE also manufactures a similar alternating pressure mattress
for $1,099 per unit [11]. Although the Smart Mattress system costs more than the previously
mentioned competitors, approximately $2,030 per unit, it possesses a unique set of features that
distinguish it from any intelligent hospital bed in the market.
The Smart Mattress system differs from many intelligent patient beds in the health care
industry because of its versatility. The proposed mattress system not only measure pressure, but
also measure wetness, which is a major contributing factor in the development of bed sores.
Along with bed sore prevention technology, the Smart Mattress also utilizes an RFID system to
display the patient’s name on a PC monitor located near the hospital bed. The monitor will also
display important medication information to prevent any potential medicine distribution errors.
7.2 Cost Analysis
Table 3 shows the cost of all the parts that will be used to make the Smart Mattress
system. The grand total of the parts to make one Smart Mattress system is $1,055. The most
expensive component is the RFID system, which includes the reader and the transmitter.
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Table 3. Part Costs
Part Quantity Unit Cost Total Cost
FSR Robotics Sensor Kit 4 $27 $108
Phidget 8/8/8 1 $80 $80
Wires/Cables 1 $15 $15
9V Battery 2 $7.50 $15
RFID Tag and Reader 1 $307 $307
Conductive Fabric Tape 100 ft $80 $80
Mattress Foam 1 $150 $150
Bed Sheet 1 $30 $30
HP Slimline PC 1 $250 $250
PC Monitor 1 $50 $50
Total Equipment Cost $1,055
Table 4 shows a list of the costs of developing the Smart Mattress system. Including the
labor to develop the system, the total cost of the initial Smart Mattress system is $34,350. The
labor cost was estimated based on the starting salary of $52,200 for someone who graduated
from the Georgia Institute of Technology with an electrical engineering degree [12]; this equals
$26.10/hour based on the 40-hour workweek. Fringe benefits and overhead were calculated at 25
percent each.
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Table 4. Development Costs
Component Labor
Hours
Labor
Cost
Total
Component
Cost
Pressure Sensor Testing 150 $3,915 $9,135Wetness Detection Testing 200 $5,220RFID Sensing 100 $2,610 $5,740RFID PC Monitor 120 $3,130Design Meetings 240 $6,265 $6,265
Total Labor 810 $21,140
Total Equipment Cost $1,055
Fringe Benefits, 25% Of Labor $5,285
Overhead, 25% Of Equipment,
Labor & Fringe
$6,870
Total Overhead $12,155
Total Project Cost $34,350
Table 5 shows the projected costs and revenue of when the Smart Mattress system is put
on the market. When the system is mass-produced, the cost of each unit will be $1,765. With the
system being so cheap, a profit margin of 15 percent was used for a final selling price of $2,030.
The projected rate of sales over five years is 15,000 units, for total revenue of $30,450,000 and a
total profit of $3,975,000.
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Table 5. Profit Projection
Equipment Cost $1,055
Assembly Labor $12
Testing Labor $8
Subtotal, Labor $20
Fringe Benefits, 25% of Labor $5
Subtotal, Labor & Fringe $1,080
Overhead, 25% of Material, Labor & Fringe $270
Subtotal, Input Costs $1,350
Sales & Marketing Expense, 20% of Production Price $270
Support & Warranty Expense, 10% of Production Price $135
Amortized Development Costs $10
Subtotal, All Costs $1,765.00
Profit, 15% $265.00
Selling Price $2,030.00
Total Revenue, Based on 15,000 Units over 5 years $30,450,000
Total Profit $3,975,000
8. SUMMARY
The prototype for the Smart Mattress was successful. The patient inactivity monitoring,
wetness detection and patient identification systems were successfully implemented and tested.
The inactivity monitoring system detected patients who had remained inactive for too long, and
the wetness detection system detected the presence of fluid. Both systems reported the current
status of the patient on the monitor. The RFID system identified the patient and displayed the
pertinent information on the monitor. The RFID tags were tested at different orientations and
ranges and exceeded our expectations. Figure 9 shows the final system with all of the
components.
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Figure 9. Final prototype of the Smart Mattress.
Future versions of this project should prioritize readying the product for manufacture by
decreasing costs, reducing power consumption, and ensuring patient safety and comfort.
Examples of ways to accomplish this are: replacing the Phidget 8/8/8 with a PIC18LF2321 (see
the following additional section for more details about using a PIC instead of the Phidget
Interface Kit), modifying the system to use an AC power supply instead of the two 9V batteries,
using RFID tags that fit comfortably on a patient's wrist or ankle, and implementing the system
on a printed circuit board. The product can also extend its applicability by using the RFID
system to identify hospital staff in the proximity of the patient's bed, detecting patient egress,
sending alerts directly to a nurse call station, and detecting fluids in other areas of the mattress to
account for IV leaks, sweat, blood, and vomit.
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PIC Microcontroller
A microcontroller-based design could reduce costs, lower current consumption, increase
patient safety, and provide a much more compact solution than a PC. Integrating patient
identification and bedsore prevention features into one compact product could be accomplished
using a PIC18LF2321 microcontroller as seen in Figure 7.
The microcontroller could be used in place of a PC to control and process data from the
RFID transceiver, FSRs, and wetness detection circuit. Using the onboard UART (universal
asynchronous receiver transmitter) communication between the PIC and RFID transceiver could
be accomplished via the RS232 standard. The FSRs could be monitored using the onboard ADC
and four of the PIC’s analog inputs. Wetness detection circuit outputs could also be tied to
analog input pins on the PIC.
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9. REFERENCES
[1] R.A. Weinstein. (July, 1998). Nosocomial Infection Update. Emerging Infection
Diseases [Online]. 4(3). [cited 2008 Sep 11], Available:
http://www.cdc.gov/ncidod/eid/vol4no3/weinstein.htm
[2] R. Moser, “Dirty Places, Part 12: Hospitals/Nursing Homes,” [Online Document],
[cited 2008 Sep 11], Available:
http://blogs.webmd.com/all-ears/2006/08/dirty-places-part-12-hospitalsnursing.html
[3] M. Haggerty, Gale Encyclopedia of Medicine, “Bed Sores” [Online], [cited 2008 Sep 11], Available:
http://www.healthatoz.com/healthatoz/Atoz/common/standard/transform.jsp?requestURI
=/healthatoz/Atoz/ency/bedsores.jsp.
[4] R&D Products, LLC, “The Smart Bed,” [Company Website], [cited 2008 Sep 12],
Available: http://thesmartbed.com/products.htm
[5] A. Lewcock, “Healthcare RFID market forecast at $1.2B,” [Online Document], 2007 July
09, [cited 2008 Aug 30], Available:
http://www.healthcareitnews.com/story.cms?id=7436
[6] P. Chung, Y. Hur, M. Wozniak, D. Yoon, "Disposable Mattress Cover with Wet Sheet
Sensors," [Online Document], [cited 2008 Sep 11], Available:
http://www.ece.gatech.edu/academic/courses/ece4007/08spring/ece4007l05/ak15/
proposal.pdf
[7] J.B. Peatman, Coin-Cell-Powered Embedded Design, Atlanta, GA: Quick&Low Books,
2008, pp. 7-14
[8] W. Khawaja, M. Saleheen, S. Sanyal, B. Virk, and R. Eiswerth, “Intellibed Hospital Bed
Add-On Kit For Improved Patient Safety,” [Online Document], [cited 2008 Sep 11],
Available:http://www.ece.gatech.edu/academic/courses/ece4007/08spring/ece4007l05/
ak11/files/Proposal.pdf
[9] C. K. Harmon, “RFID: Update on Standards and Regulatory Initiatives,”
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[Online Document], [cited 2008, Sep 12], Available:
http://www.aimglobal.org/members/news/templates/template.aspx?articleid=3302&zonei
d=45
[10] IDT Marketing, “Tradewind 3000 8” Alternating Pressure Mattress System,”
[Company Website], [cited 2008 Sep 12], Available:
http://www.alternatingpressuremattress.com/3000.html
[11] uCanHealth, “MED-AIRE 8” Alternating Pressure Mattress Overlay with Low Air Loss,”
[Company Website], [cited 2008 Sep 12], Available:
http://ucanhealth.com/goto.php?page=detail.php&graph1=14028&cat_page=alternating_
pressure_mattress
[12] Georgia Institute of Technology, “Bachelor’s Degree Candidates by Major,”
[Online Document], [cited 2008, Sep 12], Available:
http://career.gatech.edu/students/bachelor.pdf
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APPENDIX A
GANTT CHART
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