Wireless Sensor Networks for Home Health Care

doi:10.1109/AINAW.2007.376

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

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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 ﬁve 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)

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

(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].

21st International Conference on

Advanced Information Networking and Applications Workshops (AINAW'07)

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

21st International Conference on

Advanced Information Networking and Applications Workshops (AINAW'07)

(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

21st International Conference on

Advanced Information Networking and Applications Workshops (AINAW'07)

Wireless Sensor Networks for Home Health Care

Summary (1 min read)

Introduction

II. TECHNOLOGIES

III. PROTOTYPES

E. LISTSENse

IV. DISCUSSION

V. CONCLUSION

Figures (4)

Citations

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