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Proceedings ArticleDOI

Wireless Sensor Networks for Home Health Care

21 May 2007-Vol. 2, pp 832-837

TL;DR: The goal of the work is to focus on health-related applications of wireless sensor networks and how current (and future) technologies will enable automated home health monitoring.

AbstractSophisticated electronics are within reach of average users. Cooperation between wireless sensor networks and existing consumer electronic infrastructures can assist in the areas of health care and patient monitoring. This will improve the quality of life of patients, provide early detection for certain ailments, and improve doctor-patient efficiency. The goal of our work is to focus on health-related applications of wireless sensor networks. In this paper we detail our experiences building several prototypes and discuss the driving force behind home health monitoring and how current (and future) technologies will enable automated home health monitoring.

Summary (1 min read)

Introduction

  • Various economic and technological factors (e.g. Moore’s Law) have brought sophisticated electronics within the reach of average users.
  • One important benefit is to help stem rising health care costs by increasing health observability and doctor-topatient efficiency.
  • More specifically, this paper will discuss several of these projects, highlighting their need, design, implementation, and results.
  • Demonstrate working prototypes with relatively simple technology which make incremental, but important, steps to toward ubiquitous deployment of health monitoring devices, as well as how they may be integrated into existing infrastructures.

II. TECHNOLOGIES

  • The authors prototypes use two similar sensor network mote technologies: Tmote Sky and SHIMMER.
  • The Tmote Sky is the latest derivative of the Berkeley Telos motes from Moteiv Corp. [1].
  • The other mote is Intel’s Digital Health Group’s platform for Sensing Health with Intelligence, Modularity, Mobility, and Experimental Re-usability, or SHIMMER.
  • Both are nearly identical with respect to processing and communication; each have the Chipcon CC2420 802.15.4 radio and TI MSP430 (with 10k RAM).

III. PROTOTYPES

  • The authors have developed several prototypes which demonstrate wireless sensor network technologies for heath care at home.
  • Each of these prototypes will be discussed in the following sections.

E. LISTSENse

  • If people with a severe hearing impairment are included with those who are deaf, then the number is 4 to 10 times higher.
  • At least half of these people reported their hearing loss after 64 years of age [9].
  • The deployment of mote technology further reduces the cost of their prototype.
  • Once the measured signal surpasses the reference value, an encrypted activation message is sent to the Base Station that incorporates the Transmitter address.
  • Figures 5(b) and 5(c) shows the manufactured Base Station and Transmitter prototype that were successfully tested and evaluated.

IV. DISCUSSION

  • Sophisticated, low-power, cheap, small, and mobile electronics will continue to permeate the home environment for a variety of applications, ranging from multi-media entertainment to home automation.
  • Therefore, this figure shows that hospital costs will rise sharply and health-care at home is one way of alleviating this problem.
  • Several technologies will be important to this evolution: sensor networks, RFID, and mobile consumer electronics.
  • Software may be deployed on these devices to remind patients of their responsibilities (e.g. taking their pills and how much to take) and performing real-time analysis of patient data, given parameters set by their physician.

V. CONCLUSION

  • Falling electronics prices and their increasing power, coupled with sensing technologies, promise to make health monitoring in one’s home, rather than frequent trips to the hospital, a reality.
  • These prototypes represent incremental, but important steps towards ubiquitous deployment of health monitoring devices for the betterment of human lives.

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UC Berkeley
Green Manufacturing and Sustainable Manufacturing
Partnership
Title
Wireless Sensor Networks for Home Health Care
Permalink
https://escholarship.org/uc/item/66s822jk
Journal
Proceedings of the 21st International Conference on Advanced Information Networking and
Applications Workshops, 2
Authors
Baker, Chris R.
Armijo, Kenneth
Belka, Simon
et al.
Publication Date
2007
eScholarship.org Powered by the California Digital Library
University of California

Wireless Sensor Networks for
Home Health Care
Chris R. Baker
, Kenneth Armijo
, Simon Belka
, Merwan Benhabib
, Vikas Bhargava
, Nathan Burkhart
,
Artin Der Minassians
, Gunes Dervisoglu
, Lilia Gutnik
,M.BrentHaick
, Christine Ho
, Mike Koplow
,
Jennifer Mangold
, Stefanie Robinson
,MattRosa
, Miclas Schwartz
, Christo Sims
, Hanns Stoffregen
,
Andrew Waterbury
, Eli S. Leland
, Trevor Pering
, and Paul K. Wright
University of California, Berkeley, USA
Intel Corporation
Abstract Sophisticated electronics are within reach of average
users. Cooperation between wireless sensor networks and existing
consumer electronic infrastructures can assist in the areas of
health care and patient monitoring. This will improve the quality
of life of patients, provide early detection for certain ailments, and
improve doctor-patient efficiency. The goal of our work is to focus
on health-related applications of wireless sensor networks. In this
paper we detail our experiences building several prototypes and
discuss the driving force behind home health monitoring and how
current (and future) technologies will enable automated home
health monitoring.
I. INTRODUCTION
Various economic and technological factors (e.g. Moore’s
Law) have brought sophisticated electronics within the reach
of average users. These technologies, when complimented with
wireless sensor networks, promise to add a truly ambient intel-
ligent component to our daily lives. Today, these technologies
may be integrated into existing consumer electronic and infras-
tructure already found in the home. The future home represents
an opportunity for the convergence of these technologies far
beyond what we see today. This future “smart” home would
be even more capable, providing an ambient awareness of
the home’s occupants through an ecosystem of ubiquitous
connectivity, disappearing devices, highly-available services,
and multi-modal sensing.
One promising application is the area of health care and
patient monitoring. The integration of sensing and consumer
electronics technologies would allow people to be constantly
monitored. One important benefit is to help stem rising health
care costs by increasing health observability and doctor-to-
patient efficiency. Moreover, constant monitoring will increase
early detection of adverse conditions and diseases for at-
risk patients, potentially saving more lives. This ability is
right around the corner and its beginning will be ushered in
with incremental integration of wireless sensor networks and
consumer electronics. This is the focus of the paper: crossing
that barrier by introducing prototypes for health monitoring
for smart home environments.
At the University of California, Berkeley, a project-based
graduate course on high-tech design and rapid prototyping has
worked for the three months to develop prototype high-tech
products utilizing wireless sensor network technology. Several
of the projects have focused on developing sensor network
based solutions for health care and patient monitoring. More
specifically, this paper will discuss several of these projects,
highlighting their need, design, implementation, and results.
The contributions of this paper are the following:
Identify opportunities for health monitoring applications
utilizing wireless sensor network technology.
Demonstrate working prototypes with relatively simple
technology which make incremental, but important, steps
to toward ubiquitous deployment of health monitoring
devices, as well as how they may be integrated into
existing infrastructures.
Discussion of why heath care at home is important and
how we believe future technology trends will continue to
merge health care and smart home environments.
This paper is organized as follows: §II will briefly dis-
cuss the base technologies with which we are working. §III
will discuss ve prototype designs. These prototypes vary in
application from infant monitoring, alerting the deaf, blood-
pressure monitoring and tracking, and monitoring fire-fighter
vital signs (a generic monitoring technology). After a brief
discussion of each prototype, §IV will reflect on the role of
technology in the convergence of health care and smart homes.
Finally, §V will conclude the paper.
II. T
ECHNOLOGIES
Our prototypes use two similar sensor network mote tech-
nologies: Tmote Sky and SHIMMER. The Tmote Sky is the
latest derivative of the Berkeley Telos motes from Moteiv
Corp. [1]. The other mote is Intel’s Digital Health Group’s
platform for Sensing Health with Intelligence, Modularity,
Mobility, and Experimental Re-usability, or SHIMMER. Sev-
eral of our prototypes use just Tmotes, while some use a
combination of Tmote and SHIMMER motes. Both are nearly
identical with respect to processing and communication; each
have the Chipcon CC2420 802.15.4 radio and TI MSP430
(with 10k RAM). However, the SHIMMER has additional
integrated sensors (e.g. 3-axis accelerometer) and has a smaller
form factor by approximately 55%. For programming both
motes, we use the TinyOS environment [2].
21st International Conference on
Advanced Information Networking and Applications Workshops (AINAW'07)
0-7695-2847-3/07 $20.00 © 2007

III. PROTOTYPES
We have developed several prototypes which demonstrate
wireless sensor network technologies for heath care at home.
Each of these prototypes will be discussed in the following
sections.
A. SleepSafe
Sudden Infant Death Syndrome (SIDS) strikes without
warning causing unexplained death to infants one month to one
year of age. While experts cannot fully explain the causes of
SIDS, research shows there are several factors which increase
the incidence of SIDS. Foremost among the risks is allowing
the infant to sleep on their stomach. An infant sleeping on their
stomach is up to 12.9 times more likely to die from SIDS [3].
To reduce the likelihood of SIDS, doctors warn parents to put
their children to sleep on their backs. This has reduced the
incidence of SIDS by 40%. However, SIDS still remains the
leading cause of death for infants less than one year old, with
approximately 2,500 deaths per year in the United States [4].
Between the ages of 4 to 7 months, infants gain the ability
to roll onto their stomachs. Parents and other care givers
may be worried about this new ability. We have built a
simple prototype (called SleepSafe) which detects the sleeping
position of the infant. It alerts the parents when the infant is
detected to be lying on its stomach, offering them peace of
mind without having to constantly watch their child while it
sleeps. Our prototype does this by attaching a sensor to the
infant’s clothing. This sensor detects if the infant is sleeping on
their back, side, or stomach. When the later two are detected,
the parent is notified. The sensitivity and delay can be adjusted
to accommodate the user’s preferences (e.g. different risk
levels and false-alarm frequency).
Our prototype consists of two sensor network motes. One
sensor mote is attached to the infant’s clothing, while the other
acts as a wireless base station to receive and process sensor
readings. Depending on the SleepSafe settings, the base station
will alert the parent. It is expected that this system could
be integrated into existing monitoring infrastructures, such as
those for audio and video. Additionally, alerts could be sent to
a pager-like device or cell phone. This prototype architecture
isshowninFigure1(a).
The mote attached to the infant’s clothing is a SHIMMER
mote. It is expected that with technology trends the reduction
in physical size will allow it to be seamlessly integrated into
the fabric of the clothing. This mote has a 3-axis accelerome-
ter; a single axis is used to sense the infants position relative to
gravity. With the mote oriented “face-up” on the infant’s chest,
3 discrete positions (back, side, and stomach) are measured
as anti-parallel, perpendicular, and parallel to the force of
gravity. Figure 1(b) illustrates how these positions are mea-
sured relative to gravity. The mote’s processor, running a small
TinyOS program, reads the accelerometer values periodically
via the on-board analog-to-digital converter (ADC), packetizes
the values, and sends the packet wirelessly to the base station
for processing.
Base Station
Sensor Mote
Sensor Readings
Infant on back.
Z
Z
Z
(a) System architecture consisting of sensing mote and base station.
(Face Up)
Back Position Stomach Position
(Face Down)
Side Position
Mattress Mattress Mattress
ggg
(b) The accelerometer detects the position of the infant in one of three
states relative to gravity (g).
Fig. 1. SleepSafe baby monitor for detecting infant sleeping position.
The base station is implemented using a Tmote and a laptop.
This mote is used to bridge the wireless to a serial port. A
Java program running on the laptop is listening for packets
from the SHIMMER mote. The Java program is very simple:
it detects the infant’s sleeping position given the sensor values
and sends an alert when infant is on its stomach. To adjust
the sensitivity of detection, the Java program keeps the last N
values in a buffer known as the sensing window (w, where
|w| = N). The values of the sensing window are averaged
to produce α: α
w
i
/N. To determine the actual sleeping
position of the infant, α must be mapped to one of the three
discreet sleeping positions s
i
(back, side, and stomach) of set
S .Athreshold t (0 < t 1) is used to determine intervals P
s
i
for mapping α to S: P
s
i
(s
i
(1 t), s
i
+ t]. For example,
suppose t = 0.5 and S = {−1, 0,1} (i.e. the states are: stomach
→−1, side 0, and back 1). Then the intervals for
mapping α are: P
1
= 1.5 < α ≤−0.5, P
0
= 0.5 < α 0.5,
and P
1
= 0.5 < α 1.5. If the average over the sensing window
is 0.78, then the infant is on their back. The user’s preferences
determine the size of the sensing window and the threshold.
Think of this processing by the base station as an adjustable
low-pass filter: a high-risk infant might have a smaller sensing
window and higher threshold value, while to reduce false-
alarms, a larger sensing window and lower threshold would
be used.
Experimentation shows the infant can move very slowly
without loss of detection. Furthermore, the delay between the
infant changing positions and the base station issuing an alert
is not observable. Future work may be to integrate this into an
existing commercial baby monitor, as well as adding additional
sensing to the SleepSafe infrastructure. For example, adding
sensing for body temperature which is also correlated to SIDS
incidence rate [3].
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Sensor Mote and
Circuitry Unit
Base Station Mote
Sensor Plates
(a) Experimental setup. (b) Baby glove swaddle.
Fig. 2. The Baby Glove prototype.
B. Baby Glove
Due to their tiny nature, premature infants are susceptible
to a variety of health problems based on the lack of proper
thermal regulation. Their underdeveloped state and low body
mass limits their ability to sweat which makes them vulnerable
to hypo- or hyperthermia, whereupon they become increas-
ingly susceptible to illness and death. Currently, children born
with a Low Body Weight (LWB) (weight < 5.5 lbs), which
account for 7% of all US births, incur a 68% mortality
rate [5]. As the weight of children decreases, the mortality
rate increases. Many of these statistics are due in part to
their extreme sensitivity to temperature fluctuations, which
must stay within a consistent range of 36
Cto38
C. With
these very tight restrictions, very sensitive, bulky and rather
expensive devices are implemented to closely monitor vitals.
In turn, we have developed an integrated health monitoring
device, contained within a swaddling baby wrap (called The
Baby Glove). The wrap design provides a comfortable method
of securing the child, with strategically placed sensors that
monitor their temperature, hydration and pulse rate, three main
health considerations important to development [6].
The Baby Glove prototype, as seen in Figure 2, encom-
passes two integrated sensor plates, which contain a thermistor
temperature sensor along with electrodes that monitor the
childs pulse rate and hydration. The sensor plates are placed
posterior and anterior to the childs upper torso, which is the
bodys largest thermal mass. The device consists of two sensor
network motes, one connected to the swaddling wrap and the
other to a base station computer. The first mote, connected
to the wrap, is a SHIMMER mote. It monitors the vitals
information coming from the sensors via an ADC, organizes
the measurements into packets and transmits them wirelessly
to the second mote, connected to the base station computer,
for processing. The mote’s sensitivity and sensor delays can
be adjusted based on user preferences.
The temperature sensor for the device calculates the baby’s
temperature (
C) based on thermistor input voltages and re-
sistances using a predefined equation: T =((V /R)(100/(3.3
V )) 1)(1/0.0039). The pulse rate electrode sensors operate
based on electrical signals that emanate from the heart as
it pumps blood. To ensure accurate readings, electrodes are
placed in two locations on the wrap. The hydration sensors,
operate using these same electrodes (with its own respective
circuitry) and calculates the childs hydration based on resis-
tivity measurements taken between them.
The Baby Gloves wireless feature allows it to monitor and
transmit vitals information to a variety of computing systems
such as PDAs, cell phones and laptops. As health condition
information is received by a computer, specialty software
analyzes the data and determines whether the childs vitals have
exceeded predefined health settings. If settings are exceeded,
an alert is sent to a parent or nurse as to the condition
of the child. The Baby Glove device software also has the
ability to send instructions to the environmental controls within
an incubator or thermostat to update the thermal conditions
autonomously.
C. FireLine
Note that while this prototype is geared toward monitoring
firefighters, it can easily be adapted to monitor the same vital
signs of patients in the home environment.
In 2005, there were 1,136,650 firefighters (both career and
volunteer) recorded protecting communities across the United
States. On average, U.S. fire departments respond to fire-
related emergencies every 20 seconds. Though firefighting
technology, protective gear, and operation procedures have
improved within the last three decades, the annual number
of on-duty firefighter deaths still remains around 100. Of
those fatalities, 50% are determined to be caused by stress,
with most firefighters experiencing sudden cardiac arrest.
Furthermore, 24.1% of injuries occurring during fire-related
emergencies have been attributed to strain [7]. The majority
of firefighter cardiac related complications can be traced to
the physical and psychological strain associated with having to
carry over 75 pounds worth of tools, equipment, and protective
gear [8]. Coupling labor intensive tasks with the heat stress
developed from extreme, hostile environments, the heart rates
of firefighters often exceeds maximal “healthy” rates.
Because of these alarming statistics, there has been great
interest in real-time monitoring of firefighter health. Any
irregularities in a firefighters heart rate can signal imminent
cardiac failure, so detecting these abnormalities immediately
and relieving the firefighter can prevent causalities. FireLine
is a wireless heart rate sensing system that can be used to
decrease stress related fatalities and injuries through real-time
firefighter health monitoring.
FireLine, illustrated in Figure 3(a), includes a wireless
sensor device (Tmote), a custom-made heart rate sensor board,
and three reusable electrodes. All components have been
integrated into a fire retardant shirt worn under the users
protective clothing and equipment. The wireless mote, sensor
board, and battery packs are housed in two slim cases that are
sewn into the inner right sleeve of the shirt. The case locations
were chosen to minimize any interference with equipment that
a firefighter must wear, such as backpacks and the breathing
apparatus, and to minimize the wiring length. The electrodes
and wires were sewn inside the shirt such that the positive and
negative electrodes are attached to each side of the chest, and
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(a) Diagram of FireLine shirt
embedded with sensors, elec-
tronic hardware, and wiring.
(b) EKG waveform measured using
FireLine. Each spike with an apex past
1.8V represents one heart beat.
Fig. 3. The FireLine prototype.
a ground electrode is attached to the stomach. The embedded
electrodes sample a voltage signal from the heart every 10
ms, and these readings form an EKG waveform. An example
waveform is shown in Figure 3(b). These measurements are
wirelessly transmitted from the mote on the firefighter’s sleeve
to a “base station” mote attached to a laptop monitored by an
incident commander. The readings are recorded and processed
by custom software that calculates the firefighters beats per
minute (bpm). The current bpm, EKG, and a graph of heart
rate over time are displayed in a Java based GUI.
If the heart rate were to increase or decrease past certain
limits, dependent on the firefighters resting heart rate, an alert
will appear on the laptop. For our test subject, a healthy heart
rate was approximated to be between 50-140 bpm. In the
event that a firefighters heart rate has increased substantially,
the commander (or patient’s doctor or care-giver) can use
the readings to make an informed decision to remove the
firefighter from the scene of the fire.
D. Heart@Home
Heart disease is the number one cause of death in America;
as our population ages, people are getting more and more
concerned about their high blood pressure as it leads to se-
rious cardiovascular diseases. This increased health awareness
pushes people to take their health into their own hands, into
their own home. Doctors nationwide agree that tracking blood
pressure daily at home is one of the best ways to live with
high blood pressure and preventing more serious health issues.
Keeping track of blood pressure at home is already a booming
business in the health care industry; millions of blood pressure
monitors are sold every year with quick and accurate readings.
At the same time, hundreds of websites are popping up with
suggestions, tips, and isolated tracking services to help people
keep track of their health stats, especially their blood pressure.
Furthermore, the user has to write down or manually enter
these stats into one of a dozen sites.
To remedy this deficiency, we have developed a blood
pressure monitor and tracking system we call Heart@Home
with a wireless sensor network as its core technology. The
Heart@Home blood pressure monitor is focused toward the
aging baby boomer population who are concerned with their
high blood pressure, are interested in maintaining a personal
health regime, and are comfortable with home PCs. It also
demonstrates integration of sensor network technology with
consumer electronics (i.e. an existing blood pressure monitor).
A SHIMMER mote is located inside the casing on the wrist
cuff connected to the electronic pressure sensor. When the start
button is pressed, it computes the user’s blood pressure and
heart rate using the oscillometric method. Initially, the wrist
cuff is inflated to restrict blood flow along the patient’s arm
(pressure sensor reads a constant value). As it deflates, the
pressure sensor value is monitored: the point at which its value
begins to oscillate is the pressure at which the blood flow is
no longer entirely restricted (systolic pressure), and the point
at which it returns to a constant value is the pressure at which
the blood flow is entirely unrestricted (diastolic pressure).
Also, the user’s heart rate can be inferred by measuring the
time between pressure peaks while the blood flow is partially
restricted and the pressure sensor value is oscillating.
The SHIMMER mote then broadcasts these readings, along
with a time-stamp, over the radio. This message is received
at the base station, which is plugged into the user’s computer
through the USB port. This base station contains a Tmote
Sky, which forwards the received message through the USB
port to the user’s computer. The included software application,
which is running on the user’s computer, monitors the specific
USB port for traffic. When a message arrives, the values are
recorded along with the time-stamp. If the wrist cuff is unable
to communicate with the base station, it will store the readings
and periodically broadcast them until it gets notification that
the base station received the message. Similarly, if the software
application is unable to retrieve the readings from the base
station, they will be stored locally until they are confirmed to
have been received by the application.
The software application provides a graph of the user’s
blood pressure and pulse rate over time (see Figure 4). The
software also offers helpful medical advice that is tailored to
the individual’s physical profile, taken from a database filled
with medical tips collected from doctors. The user can enter
their height and weight, along with any medications they are
taking and other health problems they have, in order to better
provide health tips. If alarming anomalies appear in the user’s
heart readings, such as a spike or steady increase in blood
pressure, the software alerts the user. To easily communicate
the readings to a physician, a report of the user’s health can
be emailed to a doctor or printed out in an easily readable
format.
E. LISTSENse
About 2 to 4 of every 1,000 people in the United States are
functionally deaf. However, if people with a severe hearing
impairment are included with those who are deaf, then the
number is 4 to 10 times higher. That is, anywhere from 9 to
22 out of every 1,000 people have a severe hearing impairment
or are deaf. At least half of these people reported their hearing
loss after 64 years of age [9]. Age is not the only cause
of hearing impairment. Recent studies show that one million
American children of school age have hearing impairments and
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