# Ubiquitous Computing for Remote Cardiac

Authors: Sunil Kumar; Kashyap Kambhatla; Fei Hu; Mark Lifson; Yang Xiao
Journal: International Journal of Telemedicine and Applications
 (2008)

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## Abstract

New wireless technologies, such as wireless LAN and sensor networks, for telecardiology purposes give new possibilities for monitoring vital parameters with wearable biomedical sensors, and give patients the freedom to be mobile and still be under continuous monitoring and thereby better quality of patient care. This paper will detail the architecture and quality-of-service (QoS) characteristics in integrated wireless telecardiology platforms. It will also discuss the current promising hardware/software platforms for wireless cardiac monitoring. The design methodology and challenges are provided for realistic implementation.


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## Body

## 1. Introduction

Ubiquitous cardiac monitoring can be defined asmobile computing, medical sensor, and
communications technologies for monitoring cardiac patients. This
represents the evolution of e-health systems from traditional desktop
telemedicine platforms to wireless and mobile configurations. Ubiquitous
cardiac monitoring is part of telemedicine research [1–134]. Current and
emerging developments in wireless communications integrated with developments
in pervasive and wearable biomedical sensor technologies would have a radical
impact on future health-care delivery systems. They would provide a solution to
the problems such as access to care for large segments in the population,
continuing healthcare cost inflation, and uneven geographic distribution of
quality. Distribution of quality is improved by enhancing accessibility to care
for underserved populations, containing cost inflation, and improving quality
through the continuous care of patients.On the other hand, we have the
following requirements for the patient monitoring applications: (i) periodic
transmission of routine vital signs and transmission of alerting signals when
vital signs cross a threshold, patients cross a certain boundary, or device
battery drops below a level, (ii) addressing many usability issues including
user comfort and trust by monitoring wireless and mobile networks including the use of
wearable, portable, or mobile devices, (iii) diversity of patients including
those suffering from mental illnesses is likely to make patient monitoring by
wireless networks a challenge because of possible paranoia related to hand-held
or wearable wireless devices, (iv) comprehensive and high-speed access to
wireless networks, reliable and scalable wireless infrastructure, secure and
fast databases, and utilization of network intelligence and information, (v)
amount and the frequency of information that needs to be transmitted is another
challenge. Especially, for the cardiac monitoring systems, we have the
following few requirements: (a) maintaining periodic transmissions of routine heart-beating
signs and real-time transmission of alert/alarm, (b) creating wearable portable
or mobile devices that provide a user with comfort, (c) accommodating the diversity
amongst patients, (iv) providing comprehensive and high-speed access to
wireless networks, reliable and scalable wireless infrastructure, secure and
fast databases, (d) utilizing network intelligence and information for
calculations, (e) varying the amount and the frequency of information that
needs to be transmitted is another challenge. For example, some patients
require that certain vital signs be transmitted every few minutes, while for
others continuous monitoring every few seconds is necessary. For all patients,
any major changes in the vital signs should be transmitted immediately.Continuous cardiac monitoring,
through wireless technology, can be used to follow up with patients that have
survived cardiac arrest, ventricular tachycardia, or cardiac syncope as well as
for diagnostic purposes in patients with diffuse arrhythmia. As PDA devices are
reasonably priced and are becoming increasingly powerful, telemedicine systems
using PDAs are a cost-effective solution in a range of medical applications and
suitable for home care usage. Some currently used patient operated ambulatory
ECG recording equipments, such as holters and transtelephonic devices, are time
consuming to setup and suffer from poor patient compliance. Patients undergoing
acute myocardial infarction and subsequent arrhythmia ending in ventricular
fibrillation and sudden cardiac arrest will not be able to operate such
equipment. For reliable monitoring, it is necessary to develop a completely
automatic recording and analyzing unit, which can detect cardiac abnormalities
and automatically send data and alarm(s) to a health provider or central alarm
system. It has been clearly documented that time is a critical factor in order
to perform early cardiopulmonary resuscitation (CPR) and early defibrillation,
and if the time to start CPR after a cardiac arrest increases, the chance of
survival is reduced [4].New wireless technology for telecardiology
purposes give new possibilities for monitoring vital parameters withwearable biomedical sensors, and give
the patient the freedom to be mobile and still be under continuous monitoring
and thereby better quality of patient care. The implications and potential of wearable cardiac monitoring technologies
are paramount, since they could (i) detect early signs of health deterioration,
(ii) notify health care providers in critical situations, (iii) find
correlations between lifestyle and health, (iv) bring sports conditioning into
a new dimension by providing detailed information about physiological signals
under various exercise conditions, and (v) provide doctors with multisourced,
real-time physiological data [1]. They will therefore give the patient the
freedom to be mobile and still be under continuous monitoring in different
environments such as both inside and outside homes, offices, hospitals, nursing
homes, and traveling. Furthermore, context-awareness can enable personalized
functions such as reminder services or medication support depending on measured
vital signs and individual disease patterns.In order to make wearable
devices practical, a series of technical, legal, and sociological obstacles
should be overcome. The major design requirements of the mobile unit are the
following: (1) portable and lightweight, (2) power autonomy of a few hours, (3)
user-friendly interface, (4) collection and display of critical biosignals, (5)
very low failure rate and highly accurate alarm triggers, especially if used
for diagnostic purposes, and (6) reliable real-time wireless data transmission
any-time anywhere in any form.In this paper, we will first
introduce general requirements of ubiquitous computing telecardiology platforms
in Section2. Section 3 will discuss existing systems. The architecture of
heterogeneous wireless platforms is stated in Section 4. Quality-of-service (QoS)
analysis in mobile telecardiology systems is given in Section 5. The fourth-generation
(4G) system is discussed in Section 6. Finally, Section 7 provides the
prospective of next-generation (xG) telecardiology systems.


## 2. Ubiquitous Computing for Telecardiology

Ubiquitous computing, also
called pervasive computing, is a concept for future computing environments
where a user is surrounded by a large amount of small application-specific,
network-connected information appliances. It is characterized by (i) physical
and cognitive embedded systems, (ii) networking, (iii) ubiquity, (iv) context
awareness, and (v) application specific devices (appliances). The costs for integrating the necessary
communication abilities are affordable compared to the potential for cost
savings and to the medical advantages: (i) context-aware, cognitive-embedded
systems result in a better usability, which is essential for the use in a
home-monitoring scenario (the device is adapting itself to the user and not
vice versa), (ii) patient mobility is maximized by physically embedding the
devices into wearable or implantable distributed systems, and (iii) networking
compensates decentralization. Thus high performance services, such as pattern
recognition with neural networks, can be provided anywhere to the mobile
devices.Problems emerge in ubiquitous
computing in the following areas.(1)
Embedded [39]:(a)
both vital sensors and base
station have to be wearable to ensure mobility and attention;(b)
attention has to be paid to the
body placement, human movement, weight, size, and other constraints;(c)
reduce the power consumption
relatively with the increase in the performance of processors, memories, and
other components.(2)
Networking [40, 41]:(a)
providing ubiquitous access to
central information services;(b)
lower power consumption;(c)
ensuring high level of security;(d)
extensive interoperability
features;(e)
integrated functionality such
as service discovery, self-configuration, encryption, and authentication;(f)
protection of privacy and
communication security considering mobile Internet connections.(3)
Context-awareness [42]:(a)
personal identifications,
personalized health monitoring systems provide functions such as reminder
services or medication support depending on measured vital signs and individual
disease patterns. The data therefore should travel reliably to the remote
nurse/physician;(b)
time, a very simple but
important context used for the timing synchronization of distributed sensors.Wireless and mobile
technologies are finding a role in cardiac patient monitoring in several different
environments: homes, hospitals, and nursing homes. However, due to several
limitations including unpredictable and spotty coverage of users by wireless
networks, the quality and reliability of patient monitoring have not been
highly satisfactory.Wireless cardiac patient
monitoring also raises several issues: (i) introduction of wireless
technologies in patient monitoring is very preliminary as patient monitoring
requirements and challenges in different environments have not been identified,
(ii) unique capabilities of wireless and mobile infrastructure for patient
monitoring have not been utilized, (iii) applications and solutions for patient
monitoring are limited to using a single type of wireless network, thus
restricting the access and coverage, and (iv) introduction of wireless and
mobile technologies in patient monitoring is very fragmented and limited to few
simple cases.For some patients, certain
vital signs need to be transmitted every few minutes, while for others
continuous monitoring every few seconds is necessary. For all patients, any
major changes in the vital signs should be transmitted immediately. In wireless
environment, it could be better to transmit differential changes since the last
time or a reference value to reduce the amount of information. This would also
increase the chances of reception by others. An increasing number of patients
will be wearing portable or mobile devices that would have access to public or
private wireless networks. To improve the quality and reliability of patient
monitoring, these devices could be designed to operate in ad hoc wireless mode. Also with a
lack of coverage and variable fluctuating coverage by infrastructure-oriented
wireless networks in some spots combined with patients in locations not reachable
by others, an increased reliability of monitoring and higher chances of
transmission of alert signal can be achieved with the use of ad hoc wireless
networks. Due to power and size requirements of these devices, the range of
transmitted signal is likely to be small. Further, the range is likely to be
affected both by the frequency of operation and the nature of spectrum used
(licensed versus unlicensed). For monitoring of patients who are not covered by
an infrastructure-oriented wireless networks, the cooperation of others with
wireless devices in an ad hoc configuration will be utilized.Increasing life expectancy
accompanied with decreasing dependency ratio in developed countries calls for
new solutions to support independent living of the elderly.Ubiquitous computing technologies can be
used to provide these solutions so that they naturally support the elderly and
their caregivers in their everyday environment. While designing these
solutions, special attention should be paid on users' needs and abilities and
on the way the solutions fit to the provisioning of the care. Finally, any
solution should be properly validated and tested in real environments with a
sufficient number of real users.Another concept, calledmobile health (m-health), has a similar
definition as the above system. Current and emerging developments in wireless
communications integrated with developments in pervasive and wearable
technologies would have a radical impact on future health-care delivery
systems. A snapshot of recent developments in these areas and some of the
challenges and future implementation issues from the m-health perspective are presented
and addressed in [43]. A comprehensive overview of some of these existing
wireless telemedicine applications and research can be found in recent
publications in the area [44–47, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134].There are some limitations to
existing wireless technologies that mostly depend on general packet radio
service (GPRS) technologies and on their deployment strategies in health care.
Some of these issues can be summarized as follows [48]. (1) The lack of an
existing flexible and integrated “m-health-on-demand” linkage of the different
mobile telecommunication options and standards for e-health services. This lack
of linkage and compatibility for telemedical services exists due to the
difficulty of achieving operational compatibility between the telecommunication
services, terminals, and devices standards, and “m-health protocols.” (2) The high
cost of communication links, especially between satellites and global mobile
devices, and the limitation of existing wireless data rates especially for the
globally available 2.5G and third-generation (3G) services for some e-health
services. This is also combined with the availability of secure mobile Internet
connectivity and information access especially for e-health systems. (3) Health-care
is a very complex industry that is difficult to change. Organizational changes
are very often required for health-care institutions to benefit from e-health
and m-health services. (4) The short-term and long-term economic consequences
and working conditions for physicians and health-care experts using these
technologies are not yet fully understood or properly investigated. (5) The methods
of payment and reimbursement issues for e-health and m-health services are not
yet fully developed and standardized. (6) There is a lack of integration
between existing e-health services and other information systems (e.g.,
referral and ordering systems, medical records, etc.). (7) The demonstration
projects so far have failed to show that m-health services result in real
savings and have cost effective potential.Mobile wireless technologies
such as mobile computing, wireless networks, and global positioning systems
(GPS) have been employed in several countries for emergency as well as general
health care [49, 50]. Though the systems show promising research in using WLAN
radios to transfer patient information to the hospital in real time, analyzing
signal interference with other available Wi-Fi hotspots, security of medical
data, transmission in areas devoid of Wi-Fi hotspots has not been addressed
significantly.Complete reliance on cellular
architecture could prove futile in some locations where the cellular coverage
is either deteriorated significantly due to many factors or is totally unavailable
as in rural areas. In [51], excessive complex computations and frequently large
data transmissions could put serious restrictions on the energy utilization of
mobile phone. Also significant interference alleviation of the Bluetooth module
with other networks, such as Wi-Fi and personal area networks, has not been
addressed.Current 3G cellular and WLAN
networks experience signal attenuation/loss due to fading, multiradio
interference and multipath distortion. Fading can be because of interference
from other radio signals present in the same part of the spectrum as well as
because of moving equipment. Dead spots may occur within buildings due to
signal attenuation by the construction material and metals, creating a dead
spot in its radio shadow. Typical examples of dead spots include subway train
platforms, indoor environments, and underground areas. The spontaneous loss of
communications for no apparent reason is probably one of the most irritating
aspects of various wireless networks.Moreover, subscribers
experience higher call blocking in dense areas known as hot spots, such as
downtown areas and amusement parks. A costly solution is to install more base
stations or access points in such regions. Alternatively, multihop relaying in
ad hoc networks can be used to provide communication in dead spot and hot spot
regions, without having to depend on an existing central controller or an
infrastructure. Users in dead spot areas can maintain connectivity with the base
station (BS) by relaying their messages through other subscribers or by hopping
to a user who has a connection with the BS. In hot spots a user can obtain a
connection by hopping away from congested BSs to lightly loaded ones. Relaying
in cellular networks solves the coverage and high data rate problems, reduces
peak power consumption, and provides load balancing in dense and highly
populated areas. In fact, due to these potential benefits, there has recently
been an interest in deploying this technique in 3G cellular systems as
discussed below. Efforts in developing heterogeneous networks by
interconnecting these technologies have opened up new areas of research.


## 3. Overview of Existing Mobile  Telecardiology Systems

In this section, we provide an
overview of technologies used for transmitting the vital physiological data
from a cardiac patient to a remote monitoring station.The European EPI-MEDICS project
[24] uses an intelligent personal ECG monitor (PEM) for the early detection of
cardiac ischemia and arrhythmia. The PEM records a 3-lead ECG (DI, DII, and
V2), derives the corresponding standard 12-lead ECG using a patient specific
transform [25], and stores the information in patient's electronic health
record (EHR) on a smart media card in the PEM device. The PEM generates
different levels of alarms based on the ECG and the patient’s clinical history,
and forwards them with the recorded signals and the EHR to the health care
providers by means of Bluetooth and GSM/GPRS in store and forward mode [26].The fast development of mobile
technologies, including increased communication bandwidth and miniaturization
of mobile terminals, has accelerated developments in the field of mobile telecardiology
[2]. Development of the efficient portable and body-worn devices and systems to
measure physiological parameters of cardiac patients (e.g., ECG, heart rate,
SpO2, and blood pressure) has been witnessing active research lately. A
wireless PDA-based physiological monitoring system for patients inside the hospital
was reported in [3] which transmits the acquired data to a central management
unit by using the hospital WLAN.A system for out-of-hospital
follow-up and monitoring of patients with chronic heart disease was discussed
in [29]. The patients belonged to one of four risk groups: arterial
hypertension, malignant arrhythmias, heart failure, and post-infarction
rehabilitation. They were provided with portable recording equipment and a
cellular phone that supported ECG data transmission and wireless application
protocol (WAP). In order to avoid hospitalization for purely health monitoring
purpose, researchers at the University of Karlsruhe
are
developing a remote personal health monitoring system by employing a platform
consisting of wearable smart sensors measuring vital signs and of a base
station communicating wirelessly with the sensors [30, 31]. A patient monitoring system using multihop ad
hoc wireless networks is presented in [32], in which vital signs from one
patient are forwarded to another patient and this could then be transferred to
an access point within range.The patients with an artificial
heart implant are discharged from the hospital after an appropriate
stabilization period. A web-based database system for reliable intelligent
continuous remote monitoring of such patients was developed in [34]. The system
consists of a portable/desktop monitoring terminal, a database for continuous
recording of patient and device status, and an “intelligent diagnosis algorithm
module” that noninvasively estimates blood pump output.


### 3.1. Using Wearable Sensors

Among commercial telemetry
systems, CardioNet is the first provider of mobile cardiac outpatient telemetry
(MCOT) service in USA for continuous monitoring of patient’s ECG and heartbeat,
at home, at work, or traveling [14, 15]. It automatically detects and transmits
(using cellular connection) abnormal heart rhythms to the CardioNet monitoring
center, where certified cardiac technicians analyze the transmissions and
respond appropriately 24/7/365. In a clinical study, CardioNet mobile cardiac
outpatient telemetry detected serious arrhythmias in 53% of patients who had
been previously monitored with Holter and/or event recording where no
arrhythmia was detected. Philips
provides a telemetry system, which consists of a portable TeleMon companion
monitor and the IntelliVue Information Center to offer an integrated
surveillance and monitoring solution for ambulating patients who require
vigilant oversight of ECG and SpO2 [16]. The IntelliVue telemetry system uses a
cellular network to provide reliable two-way communications between
transceivers and the Information Center. The system
provides audible feedback from transceiver on SpO2 spot checks and patient out
of range. The GMP Wireless Medicine Corp. developed LifeSync wireless ECG
system for bedside monitoring [17, 18].A wearable wireless biomedical
sensor system has been developed in [5]. The patient wears a wireless ECG
sensor, which transmits ECG signals to a dedicated hand-held device (HDD). If an abnormal cardiac signal is encountered,
the HHD unit transmits (using 3G cellular phone) the recorded ECG to a hospital
with an alarm. The system uses an error correction protocol based on the TCP/IP
for reliable transmission. However, the system prototype seems to be too large
for routine use by outpatients.An innovative system named
WEALTHY is presented in [6], where conducting and piezoresistive materials in
form of fiber and yarn are integrated in a garment and used as sensor and
electrode elements for simultaneous recording of vital signs. Microsoft
Corporation has developed “HealthGear,” a real-time wearable system consisting
of a set of physiological sensors wirelessly connected via Bluetooth to a
Bluetooth-enabled cell phone for monitoring and analyzing physiological signals
[1]. Some other wearable health monitoring devices have been discussed in
[7–12]. The MobiHealth project in Europe aims
to provide continuous monitoring of patients outside the hospital environment
by using a 3G-enabled body area networks (BAN) [13]. The major issues considered in the MobiHealth
project are security, availability, and reliability of communication resources
and QoS guarantees for bandwidth, delay, and bit error rate.A wireless and wearable ECG
monitoring system was proposed in [27] to detect the rare occurrences of
cardiac arrhythmias and to follow up critical patients from their home. It
continuously measures and transmits the sampled ECG signals to the patient’s
PDA using a built-in RF-radio transmitter. The PDA automatically connects to a
GPRS mobile network to transmit the data to health provider. A real-time
patient monitoring system that integrates vital signs sensors, location
sensors, ad hoc networking, electronic patient records, and web portal
technology was designed and developed in [28].The design of a processor,
which samples signals from sensors on the patient, has been addressed in [37].
The processor consists of a signal conditioning module, a peripheral control
module, a processor and memory module with a microcontroller, and a Bluetooth
communication module. In Finland, a system with secure mobile healthcare services was
tested in 2003 [38].CodeBlue is a wireless
infrastructure for emergency medical care integrating low-power wireless vital
sign sensors, PDAs and PCs [19, 20]. Some of their research interests include
the integration of medical sensors with low-power wireless networks, wireless
ad hoc routing protocols, and adaptive resource management. The system is
scalable and robust with respect to the number of simultaneous queries, data
rates, and transmitting sensors. Some other critical issues considered by
CodeBlue are flexible device discovery and naming for sensors, prioritization
of patient data, security, and fast and reliable tracking of rescuer and victim
locations. The AMON system is a wrist-worn medical monitoring and alert system
targeting high-risk cardiac/respiratory patients [21]. The system includes
continuous collection and evaluation of multiple vital signs, medical emergency
detection, and GSM/UMTS cellular connection to a medical center.More recent advances in wearable medical sensors
A new system-on-a-chip radar
sensor for next-generation wearable wireless interface applied to the human
health-care and safeguard is presented in [135]. The overall system consists of
a radar sensor for detecting the heart and breath rates and a low-power IEEE
802.15.4 ZigBee radio interface, which provides a wireless data link with
remote data acquisition and control units. Particularly, the pulse radar
exploits 3.1–10.6 GHz ultrawide band signals, which allow a significant
reduction of the transceiver complexity and, then, of its power consumption.
Such a novel system-on-a-chip wireless wearable interface enables low-cost
silicon technologies for contactless measuring of the primary vital signs and
extends the capability in terms of applications for the emerging wireless body
area networks.
Reference [136]
presents a compact planar antenna designed for wireless sensors intended for
healthcare applications. Antenna performance is investigated with regards to
various parameters governing the overall sensor operation. The study
illustrates the importance of including full sensor details in determining and
analyzing the antenna performance. A globally optimized sensor antenna shows an
increase in antenna gain by 2.8 dB and 29% higher radiation efficiency in
comparison to a conventional printed strip antenna. The wearable sensor
performance is demonstrated, and effects on antenna radiated power, efficiency,
and front-to-back ratio of radiated energy are investigated both numerically
and experimentally.
Although it is suggested to use wearable medical devices and sensors as the nodes of body sensor networks (BSN) could
allow better long-term monitoring of health condition, the protocol and
criteria for validating these nodes in clinical settings are often overlooked.
By using the validation of blood pressure (BP) measurement devices as an
example, [137] reveals the need for new standards for nodes of BSN and proposes
essential considerations to it. It is observed from a previous clinical survey
and their theoretical analysis that there are disagreements in existing
standards on the validation of conventional BP devices. Moreover, an experiment
carried out by their group on 85 subjects demonstrates the inappropriateness of
using the existing protocols that are setup for validating cuff-based BP
devices to evaluate new cuff-less measurement techniques. The results suggested
that a third objective measure could be introduced to relate the variant
standards. It is also proposed that different validation criteria should be
used for nodes of BSN that are developed based on new measurement principles.
Reference [138]
analyzes the main challenges associated with noninvasive, continuous, wearable,
and long-term breathing monitoring. The characteristics of an acoustic
breathing signal from a miniature sensor are studied in the presence of sources
of noise and interference artifacts that affect the signal. Based on these
results, an algorithm has been devised to detect breathing. It is possible to
implement the algorithm on a single integrated circuit, making it suitable for
a miniature sensor device. The algorithm is tested in the presence of noise
sources on five subjects and shows an average success rate of 91.3% (combined
true positives and true negatives).


### 3.2. Using Cell Phones

Some researchers have used
cellular phones to transmit the vital signs from the ambulance to the hospital,
either in store-and-forward mode [22] or in real-time mode [23].A 3G universal mobile
telecommunications system (UMTS) solution for the delivery of voice, real-time
video, ECG signals, and medical scans information from an ambulance to a
hospital is presented in [33]. The quality-of-service constraints for different
services are investigated and feasibility of using UMTS technology is
demonstrated. However, the QoS provisioning is provided within the patient’s
data only (ECG/video/voice) and not with other services in UMTS. The number of
lost packets is very high as the number of users approaches 30. The system has to be
evaluated for reliability measurement at high transmission rate requirements.Steady advances in wireless
networking, medical sensors, and interoperability software create exciting
possibilities for improving the way we provide emergency care. The Advanced
Health and Disaster Aid Network (AID-N) [35], being developed at Applied
Physics Lab of Johns Hopkins University, explores and show cases of how these
advances in technology can be employed to assist victims and responders in
times of emergency. The system in [28] covers a subset of the technologies in
AID-N.A cost-effective portable teletrauma
system that assists health-care centers in providing prehospital trauma care is
developed and implemented in [36]. The simultaneous transmission of a patient’s
video, medical images, and electrocardiogram signals, which is required
throughout the prehospital procedure, is demonstrated over commercially
available 3G wireless cellular data service. Physicians can remotely control
the information sent from the patient side. This allows a trauma specialist to
be virtually present at the remote location and participate in prehospital
care, which can potentially reduce mortality and morbidity. To alleviate the
limited and fluctuant bandwidth barriers of the wireless cellular link, the
system adapts to network conditions through media transformations, data
prioritization, and application-level congestion control methods.A multihop relaying scheme is
used as overlay architecture for single-hop time division duplex (TDD) wideband-code
division multiple access (W-CDMA) cellular networks in [52]. A major challenge
pertaining to the introduction of this technology into cellular networks is the
design of an efficient slot assignment algorithm for relaying nodes. An
heuristic slot assignment scheme, namely delay-sensitive slot assignment (DSSA),
is proposed in [53]. DSSA is capable of fully utilizing a limited number of
channels to enhance spatial reuse and reduce the end-to-end delay.A third-generation universal
mobile telecommunications system (UMTS) solution for the delivery of biomedical
information from an ambulance to a hospital is presented in [115]. The joint
transmission of voice, real-time video, electrocardiogram signals, and medical
scans in a realistic cellular multiuser simulation environment is considered,
taking into account the advantages and particularities of UMTS technology for
such transmission. The accomplishment of quality-of-service constraints for
different services is investigated and quantitative results were provided to
demonstrate the feasibility of using UMTS technology for emergency care
services on high-speed moving ambulance vehicles.The evaluation of the above
technologies points to a number of critical areas for future work. The most
serious is the lack of reliable communication, although results show that this
problem can be mitigated somewhat through redundant transmissions. Reliable
routing may not be required for all medical data; rather, the system should
allow each query to specify its reliability needs in terms of acceptable loss,
data rate, or jitter. Another area worth exploring is the impact of bandwidth
limitations and effective techniques for sharing bandwidth across patient sensors.
For example, each CodeBlue query could specify a data priority that would allow
certain messages (e.g., an alert from a critical patient) to have higher
priority than others in the presence of radio
congestion. This approach can be combined with rate-limiting congestion control
[14, 25] to bound the bandwidth usage of patient sensors. An important
shortcoming of the current CodeBlue prototype is its lack of security.
Integration of private-key encryption [29] along with a public-key protocol for
key distribution [22, 38] should be investigated. The privacy and security
requirements for medical care are complex and differ depending on the
scenario. For example, HIPAA privacy regulations need not be enforced during
life-saving procedures. Nevertheless, integration of some forms of end-to-end
security would be very helpful.


## 3.1. Using Wearable Sensors

Among commercial telemetry
systems, CardioNet is the first provider of mobile cardiac outpatient telemetry
(MCOT) service in USA for continuous monitoring of patient’s ECG and heartbeat,
at home, at work, or traveling [14, 15]. It automatically detects and transmits
(using cellular connection) abnormal heart rhythms to the CardioNet monitoring
center, where certified cardiac technicians analyze the transmissions and
respond appropriately 24/7/365. In a clinical study, CardioNet mobile cardiac
outpatient telemetry detected serious arrhythmias in 53% of patients who had
been previously monitored with Holter and/or event recording where no
arrhythmia was detected. Philips
provides a telemetry system, which consists of a portable TeleMon companion
monitor and the IntelliVue Information Center to offer an integrated
surveillance and monitoring solution for ambulating patients who require
vigilant oversight of ECG and SpO2 [16]. The IntelliVue telemetry system uses a
cellular network to provide reliable two-way communications between
transceivers and the Information Center. The system
provides audible feedback from transceiver on SpO2 spot checks and patient out
of range. The GMP Wireless Medicine Corp. developed LifeSync wireless ECG
system for bedside monitoring [17, 18].A wearable wireless biomedical
sensor system has been developed in [5]. The patient wears a wireless ECG
sensor, which transmits ECG signals to a dedicated hand-held device (HDD). If an abnormal cardiac signal is encountered,
the HHD unit transmits (using 3G cellular phone) the recorded ECG to a hospital
with an alarm. The system uses an error correction protocol based on the TCP/IP
for reliable transmission. However, the system prototype seems to be too large
for routine use by outpatients.An innovative system named
WEALTHY is presented in [6], where conducting and piezoresistive materials in
form of fiber and yarn are integrated in a garment and used as sensor and
electrode elements for simultaneous recording of vital signs. Microsoft
Corporation has developed “HealthGear,” a real-time wearable system consisting
of a set of physiological sensors wirelessly connected via Bluetooth to a
Bluetooth-enabled cell phone for monitoring and analyzing physiological signals
[1]. Some other wearable health monitoring devices have been discussed in
[7–12]. The MobiHealth project in Europe aims
to provide continuous monitoring of patients outside the hospital environment
by using a 3G-enabled body area networks (BAN) [13]. The major issues considered in the MobiHealth
project are security, availability, and reliability of communication resources
and QoS guarantees for bandwidth, delay, and bit error rate.A wireless and wearable ECG
monitoring system was proposed in [27] to detect the rare occurrences of
cardiac arrhythmias and to follow up critical patients from their home. It
continuously measures and transmits the sampled ECG signals to the patient’s
PDA using a built-in RF-radio transmitter. The PDA automatically connects to a
GPRS mobile network to transmit the data to health provider. A real-time
patient monitoring system that integrates vital signs sensors, location
sensors, ad hoc networking, electronic patient records, and web portal
technology was designed and developed in [28].The design of a processor,
which samples signals from sensors on the patient, has been addressed in [37].
The processor consists of a signal conditioning module, a peripheral control
module, a processor and memory module with a microcontroller, and a Bluetooth
communication module. In Finland, a system with secure mobile healthcare services was
tested in 2003 [38].CodeBlue is a wireless
infrastructure for emergency medical care integrating low-power wireless vital
sign sensors, PDAs and PCs [19, 20]. Some of their research interests include
the integration of medical sensors with low-power wireless networks, wireless
ad hoc routing protocols, and adaptive resource management. The system is
scalable and robust with respect to the number of simultaneous queries, data
rates, and transmitting sensors. Some other critical issues considered by
CodeBlue are flexible device discovery and naming for sensors, prioritization
of patient data, security, and fast and reliable tracking of rescuer and victim
locations. The AMON system is a wrist-worn medical monitoring and alert system
targeting high-risk cardiac/respiratory patients [21]. The system includes
continuous collection and evaluation of multiple vital signs, medical emergency
detection, and GSM/UMTS cellular connection to a medical center.More recent advances in wearable medical sensors
A new system-on-a-chip radar
sensor for next-generation wearable wireless interface applied to the human
health-care and safeguard is presented in [135]. The overall system consists of
a radar sensor for detecting the heart and breath rates and a low-power IEEE
802.15.4 ZigBee radio interface, which provides a wireless data link with
remote data acquisition and control units. Particularly, the pulse radar
exploits 3.1–10.6 GHz ultrawide band signals, which allow a significant
reduction of the transceiver complexity and, then, of its power consumption.
Such a novel system-on-a-chip wireless wearable interface enables low-cost
silicon technologies for contactless measuring of the primary vital signs and
extends the capability in terms of applications for the emerging wireless body
area networks.
Reference [136]
presents a compact planar antenna designed for wireless sensors intended for
healthcare applications. Antenna performance is investigated with regards to
various parameters governing the overall sensor operation. The study
illustrates the importance of including full sensor details in determining and
analyzing the antenna performance. A globally optimized sensor antenna shows an
increase in antenna gain by 2.8 dB and 29% higher radiation efficiency in
comparison to a conventional printed strip antenna. The wearable sensor
performance is demonstrated, and effects on antenna radiated power, efficiency,
and front-to-back ratio of radiated energy are investigated both numerically
and experimentally.
Although it is suggested to use wearable medical devices and sensors as the nodes of body sensor networks (BSN) could
allow better long-term monitoring of health condition, the protocol and
criteria for validating these nodes in clinical settings are often overlooked.
By using the validation of blood pressure (BP) measurement devices as an
example, [137] reveals the need for new standards for nodes of BSN and proposes
essential considerations to it. It is observed from a previous clinical survey
and their theoretical analysis that there are disagreements in existing
standards on the validation of conventional BP devices. Moreover, an experiment
carried out by their group on 85 subjects demonstrates the inappropriateness of
using the existing protocols that are setup for validating cuff-based BP
devices to evaluate new cuff-less measurement techniques. The results suggested
that a third objective measure could be introduced to relate the variant
standards. It is also proposed that different validation criteria should be
used for nodes of BSN that are developed based on new measurement principles.
Reference [138]
analyzes the main challenges associated with noninvasive, continuous, wearable,
and long-term breathing monitoring. The characteristics of an acoustic
breathing signal from a miniature sensor are studied in the presence of sources
of noise and interference artifacts that affect the signal. Based on these
results, an algorithm has been devised to detect breathing. It is possible to
implement the algorithm on a single integrated circuit, making it suitable for
a miniature sensor device. The algorithm is tested in the presence of noise
sources on five subjects and shows an average success rate of 91.3% (combined
true positives and true negatives).


## 3.2. Using Cell Phones

Some researchers have used
cellular phones to transmit the vital signs from the ambulance to the hospital,
either in store-and-forward mode [22] or in real-time mode [23].A 3G universal mobile
telecommunications system (UMTS) solution for the delivery of voice, real-time
video, ECG signals, and medical scans information from an ambulance to a
hospital is presented in [33]. The quality-of-service constraints for different
services are investigated and feasibility of using UMTS technology is
demonstrated. However, the QoS provisioning is provided within the patient’s
data only (ECG/video/voice) and not with other services in UMTS. The number of
lost packets is very high as the number of users approaches 30. The system has to be
evaluated for reliability measurement at high transmission rate requirements.Steady advances in wireless
networking, medical sensors, and interoperability software create exciting
possibilities for improving the way we provide emergency care. The Advanced
Health and Disaster Aid Network (AID-N) [35], being developed at Applied
Physics Lab of Johns Hopkins University, explores and show cases of how these
advances in technology can be employed to assist victims and responders in
times of emergency. The system in [28] covers a subset of the technologies in
AID-N.A cost-effective portable teletrauma
system that assists health-care centers in providing prehospital trauma care is
developed and implemented in [36]. The simultaneous transmission of a patient’s
video, medical images, and electrocardiogram signals, which is required
throughout the prehospital procedure, is demonstrated over commercially
available 3G wireless cellular data service. Physicians can remotely control
the information sent from the patient side. This allows a trauma specialist to
be virtually present at the remote location and participate in prehospital
care, which can potentially reduce mortality and morbidity. To alleviate the
limited and fluctuant bandwidth barriers of the wireless cellular link, the
system adapts to network conditions through media transformations, data
prioritization, and application-level congestion control methods.A multihop relaying scheme is
used as overlay architecture for single-hop time division duplex (TDD) wideband-code
division multiple access (W-CDMA) cellular networks in [52]. A major challenge
pertaining to the introduction of this technology into cellular networks is the
design of an efficient slot assignment algorithm for relaying nodes. An
heuristic slot assignment scheme, namely delay-sensitive slot assignment (DSSA),
is proposed in [53]. DSSA is capable of fully utilizing a limited number of
channels to enhance spatial reuse and reduce the end-to-end delay.A third-generation universal
mobile telecommunications system (UMTS) solution for the delivery of biomedical
information from an ambulance to a hospital is presented in [115]. The joint
transmission of voice, real-time video, electrocardiogram signals, and medical
scans in a realistic cellular multiuser simulation environment is considered,
taking into account the advantages and particularities of UMTS technology for
such transmission. The accomplishment of quality-of-service constraints for
different services is investigated and quantitative results were provided to
demonstrate the feasibility of using UMTS technology for emergency care
services on high-speed moving ambulance vehicles.The evaluation of the above
technologies points to a number of critical areas for future work. The most
serious is the lack of reliable communication, although results show that this
problem can be mitigated somewhat through redundant transmissions. Reliable
routing may not be required for all medical data; rather, the system should
allow each query to specify its reliability needs in terms of acceptable loss,
data rate, or jitter. Another area worth exploring is the impact of bandwidth
limitations and effective techniques for sharing bandwidth across patient sensors.
For example, each CodeBlue query could specify a data priority that would allow
certain messages (e.g., an alert from a critical patient) to have higher
priority than others in the presence of radio
congestion. This approach can be combined with rate-limiting congestion control
[14, 25] to bound the bandwidth usage of patient sensors. An important
shortcoming of the current CodeBlue prototype is its lack of security.
Integration of private-key encryption [29] along with a public-key protocol for
key distribution [22, 38] should be investigated. The privacy and security
requirements for medical care are complex and differ depending on the
scenario. For example, HIPAA privacy regulations need not be enforced during
life-saving procedures. Nevertheless, integration of some forms of end-to-end
security would be very helpful.


## 4. Using Heterogeneous (Cellular, WLAN,  and Ad Hoc) Networks

The advent of a myriad of
wireless networking technologies allows a mobile host today to be equipped with
multiple wireless interfaces that have access to different wireless networks.
The present cellular network-based hybrid schemes to handle host mobility are
heavily dominated by infrastructure-based schemes. The vertical handoffs [65, 66] assuming the support of Mobile IP [67] have been proposed to ensure
continuous connectivity when the mobile host roams between different wireless
networks. Various interworking architectures [68–70, 139, 140] have
also been proposed to facilitate link-layer handoffs between the WLAN and cellular
networks. Other approaches include providing a basic access network [71] or a
communication gateway [72] that the mobile host can access directly without
being exposed to the heterogeneity of the backend network infrastructure. In
[73], an end-to-end approach (without relying on the infrastructure support) is
proposed to handle connection migration when the network address of the mobile
host changes during the lifetime of the connection.The major drawbacks in handling
host mobility in 3G cellular-based heterogeneous networks are as follows.(i)
Reliance
on infrastructure support. Although several approaches
have been proposed recently for achieving host mobility without incurring the
overheads in Mobile IP [74–77], given the
increasing heterogeneity of wireless access technologies, the effectiveness of
these approaches is greatly limited by the specificity to the networks they are
designed for.(ii)
Inability
to leverage soft handoffs. Even if soft handoffs are
possible at the link layer, in the absence of any explicit support at a higher
layer, the migrated connection experiences packet losses and suffers from
performance degradation during the handoffs across heterogeneous networks.
Specifically, although TCP migration [78] achieves host mobility without relying
on the network support, it performs a “hard handoff” at the transport layer
between the new and old TCP states (i.e., transmission control blocks [79]).(iii)
Lack
of support for network-specific congestion control schemes.
Despite the availability of network-specific congestion control schemes, no
existing solutions allow the mobile host to dynamically change them for a live
connection when it migrates to a heterogeneous network.(iv)
No
provision for resource aggregation. When a multihomed
mobile host is within reach of more than one network, existing approaches do
not allow it to leverage their resources simultaneously.An end-to-end scheme that
enables a multihomed mobile host to seamlessly use the heterogeneous wireless
access technologies is recently proposed in [80], which allows host mobility,
seamless vertical handoffs, and effective bandwidth aggregation when the mobile
host has simultaneous access to multiple networks.In 3G cellular networks, mobile
users experiencing poor channel quality usually have low data-rate connections
with the base station. A unified cellular and ad hoc network (UCAN)
architecture for enhancing cell throughput, while maintaining fairness, is
proposed in [54]. In UCAN, a mobile client has both 3G cellular link and IEEE
802.11-based peer-to-peer link. The UCAN architecture improves individual
user's throughput by up to 310% and the aggregate throughput of the HDR
downlink by up to 60%. Several companies such as GTRAN Wireless [55] are
offering integrated cards that implement both IEEE 802.11b and 3G wireless
interfaces. Thus, if routing protocols can be made aware of both interfaces,
they can improve performance significantly by selecting the best interface(s)
to deliver packets to the mobile users.Deficiencies of mobile ad hoc networks
include limited wireless bandwidth efficiency, low throughput, large delays,
and weak security. Integrating it with a cellular network can improve
communication and security in ad hoc networks, as well as enrich the cellular
services. A cellular-aided mobile ad hoc network (CAMA) architecture is
proposed in [56], which provides throughput enhancements. A CAMA agent in the
cellular network manages the control information, and the routing and security
information is exchanged between mobile terminals (MTs) and the agent through
cellular radio channels. A position-based routing protocol is developed in CAMA
to make more accurate routing decisions. CAMA involves high GPS cost and incurs delay when talking to the CAMA
agent. The integrated cellular and ad hoc relaying (iCAR) architecture
addresses the congestion problem due to unbalanced traffic in a cellular system
and provides interoperability for heterogeneous networks [57]. A limited number
of ad hoc relaying stations (ARS) and some increase in the signaling overhead
(as well as hardware complexity) reduce the call blocking/dropping probability
in a congested cell and the overall system. A thorough performance study of two
such novel throughput enhancement architectures, iCAR and multihop cellular
network (MCN), is carried out in [58]. iCAR balances the traffic load and
increases the network throughput by relaying excess traffic from a hot cell to
cooler cells through a multihop path over special routers called ad hoc
relaying stations (ARS). However, it requires large number of relay stations
due to small coverage and cellular channel shared between relay station and
base station. MCN increases the network throughput by reducing the data
transmission power to half of the cell radius, thus increasing the spatial
reuse of bandwidth. These two architectures thus benefit by combining the best
of cellular and ad hoc systems.Directional antennas were used
to enhance the spatial reuse in the ad hoc-cellular (A-Cell) architecture [59].
In [60], the throughput performance of ad hoc GSM (A-GSM) scheme with respect
to the number of dead spot locations, average dead spot size, and mobile node
population has been investigated and compared to that of a 2G GSM system. Area
coverage and capacity enhancement have also been investigated in [61], where
the multihop relaying increases the area coverage by 40% compared to the
single-hop case.Correlated usage of mobile
devices intensifies traffic bursts and introduces congestion in cellular
networks. “PARCelS,” which utilizes roaming mobile hosts to perform
route relaying, is discussed in [62]. “PARCelS” performs operations
such as balancing traffic load, avoiding traffic congestion, and reducing
latency. The disadvantages of PARCelS are the need for high mobile station
density, complexity, and energy consumption.Another hybrid network model of
cellular and ad hoc networks called Sphinx is proposed in [63], which achieves
higher throughput and lower power consumption. At the same time, Sphinx avoids
the typical pitfalls of ad hoc networks including unfair resource allocation
and throughput degradation due to mobility and traffic locality.Users in a hot cell typically
experience a large delay. In mobile assisted data forwarding (MADF) scheme
[64], an ad hoc overlay network is added to the fixed cellular infrastructure
and special channels called “forwarding channels” are used to connect
users in a hot cell and its surrounding cold cells without going through the
base station. The forwarding channel management in MADF is done by mobile units
themselves. A major advantage in MADF is the low delay, but the need for
reserved cellular channels at the relay station (i.e., mobile unit) increases
the computational complexity.


## 5. QoS Requirements in Mobile Telecardiology Applications

A comprehensive overview of
various mobile telemedicine technologies as used in different settings is given
in [81]. Based on its delay tolerance, the telemedicine data can be classified
as stream (e.g., ambient video and audio), conversational (videoconferencing),
near real-time, and not real-time. In medical environment, different data traffics with different
classes of QoS requirements have to be transmitted simultaneously. One of the
critical issues to be investigated is how to optimize the network performance
to provide medical services with other multimedia services simultaneously.The telehealth data from
different patients, who may be widely scattered, will consist of various
physiological parameters, text, voice as well as video for diverse chronic diseases.
These data must
coexist together as well as with other commercial data such as voice, video
(streaming or real), multimedia, and Internet. QoS provisioning for the future
advanced telehealth monitoring technologies and systems is therefore a difficult
proposition as the communication infrastructure must satisfy QoS requirements
of different classes of applications. In this section, we analyze the research
carried out in QoS provisioning in past telehealth monitoring projects.The wide development of multimedia
clinical applications and the use of inter- and intrahospital communication
networks require a specific analysis to increase healthcare services
efficiency. A processing toolbox (QoSM3) for technical evaluation of quality-of-service
(QoS) traffic requirements in new healthcare services based on telemedicine is
proposed in [116]. This tool consists of the multimedia service definition and
the measurement and modeling processes, which permit to analyze QoS
requirements and to optimize application design regarding available network
resources. The proposed methodology was tested to evaluate real-time and
store-forward medical services.With the advent of the “next-generation
Internet” and various related technologies, important tradeoffs between emerging
network capabilities and design-related application requirements for
network-based distributed healthcare systems are observed in [117]. One of the
aspects of these emerging network capabilities is quality of service (QoS). QoS
guarantees are a necessary characteristic of “next-generation” networks which
will have a profound impact on the deployment of advanced, network-sensitive
medical applications. Some of the underlying aspects of QoS technologies and
possible considerations in designing network-based medical systems are
discussed in [117]. One such system that
attempts to solve some QoS problems, as well as provides a system for
telehealth, is called “Cardimon,” and will be overviewed in Section 7.QoS guarantees are a necessary
characteristic of “next-generation” networks, which will have a profound impact
on the deployment of advanced, network-sensitive medical applications [82]. A
mobile telemedicine system was tested in three ambulances using commercial,
off-the-shelf equipment, with data-management and physician interface software
[83]. The main problems encountered by
the above prototype were the instability in the commercial system components
and unpredictable wireless connectivity and bandwidth resulting in inconsistent
system performance, which frustrates the physician. The project in [84] tested
a patient monitoring system and evaluated the network performance. Although,
the 3G networks significantly perform better than 2.5G, they might not be
adequate to support the bandwidth and delay requirements of the sophisticated
and demanding m-health services. The teletrauma scenario requires the
transmission of patient’s vital signs together with audio/video signals in
real-time from the scene of the accident [85]. High Plains Rural Health Network
(HPRHN), based in Fort Morgan, Colorado, is an interactive video network for
real-time monitoring and diagnosis of patients at the sites of serious
automobile accidents on the highways. In
[86], the notion of QoS for communication of telemedicine multimedia data is
presented for preorchestrated as well as live videoconferences.The InfraVIDA telemedicine
system allows remotely located health professionals to make telediagnosis and
get second medical opinion from consultants [87]. Applications get differentiated
services (i.e., DiffServ QoS) from the network (e.g., expedited forwarding,
assured forwarding), with associated parameters such as bandwidth, delay,
jitter, and packet loss. A scalable and flexible QoS provisioning is discussed
in [141] based on a bandwidth broker (BB) to automate admission control and
router configuration. The BB allocates resources for each incoming flow based
on the requested QoS, its service level agreement, and the available resources.
The performance of a WCDMA cellular system supporting teleechography services
is evaluated in [88] for two types of traffic with different source coding and
QoS schemes. A slow fading multipath Rayleigh channel is assumed in the paper.A load-balancing platform based
on differentiation of services that improves the application-level QoS (such as
client response time, priority) in a telecare application is presented in [89].
The platform allows the coexistence of Internet services and distributed
objects. QoS parameters are associated to different service classes (premium,
gold, bronze, and best effort). Some of these telecare services (such as signal
processing/conditioning, alarm generation) need high performance and
availability, while some others need higher priority (such as vital signals).
When a client request arrives, the system knows what QoS parameters must be
provided depending on its service class.Experts around the world
believe that new demands in providing healthcare will require fundamental
changes in the structure of the network and communication [90]. It is almost
impossible to separate the deployment of QoS capabilities from a thorough
evaluation in the context of an application (or class of applications) with the
major challenge being their vast and highly variable requirements. Some
compromises proposed in [91] are (i) evaluation of potential QoS mechanisms
jointly in the context of physical network elements and a representative class
of “next-generation” applications, (ii) the development of mechanisms
which end-users can access to participate directly in the negotiation between
the network capabilities and application requirements. In LAN-based networks and in the concept of next-generation
Internet, there tends to be relatively few general approaches such as (i)
shaping the aggregate traffic streams with simplistic regard for the needs of
individual streams, or (ii) having the capability to ensure specific service
characteristics for individual streams at the expense of tremendous complexity
for the user and/or application to ensure the integrity of data streams.The wide deployment of
multimedia clinical applications and the use of inter- and intrahospital
communication network require a specific analysis to increase healthcare
services efficiency. A processing toolbox (QoSM3) for technical evaluation of QoS
traffic requirements in new healthcare services based on telemedicine is
proposed in [104]. The multimedia service definition and the measurement and
modeling processes permit to analyze QoS requirements and to optimize application
design regarding available network resources. The proposed method has been
tested to evaluate real-time and store-forward medical services. In order to
extract the maximum benefit of telemedicine services, it is essential to define
a precise methodology to characterize the QoS requirements for the transmitted
information and the management of the available network resources [105]. Three
important QoS evaluation metrics are (i) efficiency, (ii) acceptability, and
(iii) usefulness. In order to optimize the QoS in these telemedicine services,
it is crucial to study
two aspects [106–108]: the nature of the transmitted biomedical information,
and the behavior of the communication networks. The variability of the
resources (e.g., in mobile infrastructures) and the heterogeneity of the
connections (e.g., in the Internet) require to measure and to model the
intercommunication networks [109–111].When we study the traffic modeling to offer QoS, it is essential to begin from source and network models
that compose it to understand traffic dynamics, and to use that knowledge in
the subsequent design. Hence, the teletraffic engineer role [112] would be the
“feedback” where the measures inform about their behavior and the QoS criteria
define their performance. An extended criterion consists of managing and adapting the information
generated by the applications (encoders, transmission rates, compression
ratios, etc.) to the available networks resources. Specifically in healthcare
environments, it would allow improving the telemedicine service QoS by looking
for the optimum values [113, 114].Reducing the elapsed time
between symptom onset and treatment can be of great benefit to the patient
while reducing the health care costs [83]. With mobile telemedicine, valuable prehospital
transport time can be used to diagnose and evaluate the patient en route.To alleviate the problems
encountered in using mobile communications, some enhancements proposed in [83] were as follows.(i)
Less
reliance on commercial systems integration. This
helps in rapidly identifying and solving the problems.(ii)
Creation
of a hybrid connectivity architecture using overlapping wireless
infrastructures. Overlapping network coverage provided by
competing network providers enables (a) higher aggregate data throughput and
(b) improved cell-to-cell connectivity. Combining different types of wireless
connectivity, including both “always-on” Internet-protocol-based connectivity
and more traditional dial-up cellular communications, the resulting smart
communications architecture allows to dynamically optimize the underlying
communications channels for bandwidth, delay, throughput, stability, and cost.(iii)
Bidirectional QoS control
allows the receiving physician to dynamically reprioritize the data
transmission to optimize bandwidth utilization and data throughput. For example,
the receiving physician can alter the frequency and quality of the images
transmitted or may opt to turn on or off the waveform and numerical vital signs
information being sent by the patient monitor. Providing this level of control alongside
a dynamic graphical QoS display provides the physician with the ability to
direct QoS delivered by the system in real time.A prerequisite for the
successful deployment of m-health services for continuous monitoring of a
patient’s vital signs is the QoS support (speed, accuracy, dependability of
data delivery and network availability, user mobility and number of concurrent
users) by underlying wireless network(s) [92] as follows.(i)
High delay variations (i.e., jitter)
have major negative influence on the system performance. The delay variations
are contributed from the physical layer mechanisms (e.g., due to 3G bearer
(re)assignments) to the high-level protocol mechanisms (e.g., protocol recovery
from lower-level communication errors). Within the higher layers, the jitter
may be caused by the TCP retransmission mechanism together with (unnecessary)
reduction of the sending rate due to the noncongestion-based message loss.
Another possible reason can be delays due to the unpredictable overall-system
events like resource problems or intermediary system (processing) delays. Due
to the high jitter, the average end-to-end delay is much higher than that
expected.(ii)
The 3G networks have asymmetric
capacity, that is, the downlink
capacity is (much) higher than the uplink. However, in telemedicine, the
patient/ambulance transmits high quantities of data to the health
provider/hospital.(iii)
Another problem observed is
concerned with the bearer (re)assignment within the 3G network. Data transport
always starts from the common bearer (which supports low bandwidth) and then
gradually, based on the traffic volume, the network assigns a higher bearer
(which supports higher bandwidth). The exact conditions under which the bearer
assignment takes place depend on operator. Bearer changes were observed when
the offered load was increasing, but random bearer changes were also observed
when the offered load was stable. This bearer change mechanism/policy might
cause problem (such as buffer overflow and delay variations) for the m-health
service when the service offers bursty traffic to the transport system.(iv)
The possibility to negotiate
QoS profiles that “reserve” a particular dedicated bearer for
transportation of m-health related data should be explored. If the bearer
assignment mechanism is known, the service can be deployed such that it
benefits from the performance characteristics of the underlying transport
system. Operators and manufactures should consider this fact in order to allow
for a better support of forthcoming m-health services.(v)
Fulfillment of the reliability
requirement is critical to success of mobile wireless communications in
telehealth applications. However, some services do not require 100% system
reliability. Moreover, there is a tradeoff between the system’s reliability and
the performance. The reliable service delivery is usually ensured by means of a
TCP-based underlying transport service. This reliable service delivery may
result in system performance degradation, that is, significant delay variation.
Therefore, the use of unreliable UDP-based underlying transport service should
be explored. A study of accuracy—(i.e., data corruption probability) and
dependability—related (i.e., transport system availability, data loss probability)
performance characteristics of the (UDP-based) transport system is an essential
subject for future research.(vi)
Low power consumption is also
an important issue to be considered in remote monitoring of mobile patients.
For example, the battery of the patient PDA will typically last only a few
hours in a 3G communication, whereas 24 hours battery life is expected.In [93], an in-depth analysis
on the system bottleneck and scalability performance characteristics is
presented. The QoS parameters for telemedicine constitute a set of
user-specified tolerable degradations of multimedia presentations that may
occur due to resource limitations. These parameters can be used to quantify the
presentation process from the user's point-of-view and establish network
resources requirements to ensure the delivery of multimedia information with
the desired quality. Interstream synchronization could be used on applications
which require that all data streams must be delivered prior to their deadlines
[91]. Another quality issue is the loss of telemedicine data due to limited
buffer capacity at the client site. Thus random network delays and scheduling
to ensure synchronization can lead to buffer overflow. However, isochronous
data such as video and audio can tolerate some information loss without
affecting their play-out quality. Depending on the required quality, a user can
quantify the acceptable data loss for each object.


## 6. Fourth Generation (4G) Mobile Telecardiology

In this section, we discuss the
limitations of 3G wireless technology in meeting some of the demands of
efficient real-time monitoring of cardiac patients. We analyze the 3G
technology and also discuss the evolution and features of 4G technology that
will give a magnanimous boost to telehealth monitoring applications.When the 3G systems scenario
and capabilities evolved, a lot of research work was carried out to create next-generation
telemedicine systems using this technology. One such effort was carried out by the
authors in [94], who proposed a test-bed based on a 3G cellular standard for
the next-generation mobile telemedicine. The 3G-based testbed (12.2 Kbps ∼ 2 Mbps) had higher and wider
transmission data rates than the 2G version (up to 9.6 Kbps). To demonstrate
the usefulness of the testbed and the potential to improve the QoS for mobile
medical applications, a simple cardiology system was designed. Because this testbed is based on
3GPP FDD mode standard, its data traffic channel has five rates 12.2,
64, 144, 384, and 2084 Kbps to be selected according to the required medical
service.There are multiple standards
for 3G making it difficult to roam and interoperate across networks. Therefore,
it cannot support the global mobility and service portability. 3G is based on primarily a wide-area concept.
It does not support hybrid networks that utilize both wireless LAN (hot spot)
concept and cell or base-station based wide area network design. 3G systems
support a peak bandwidth of only a few Mbps. Researchers have recently
developed spectrally more efficient modulation schemes that cannot be
retrofitted into 3G infrastructure. We need all digital packet networks that
utilize IP in its fullest form with converged voice and data capability.Research on fourth generation
(4G) and beyond 4G (4G+) mobile communication systems is already under way to
achieve both high data rates and extended coverage of the geographical area
[59, 60, 95–98]. 4G is an initiative by researchers from various universities
and industry (e.g., Motorola, Qualcomm, Nokia, Ericsson, Sun, HP, NTT DoCoMo)
to move beyond the limitations and problems of 3G to address future needs of a
universal high-speed wireless network that will interface with wired backbone
network seamlessly [99]. A comparison
between features of the 3G and 4G wireless networks is provided below.A number of spectrum allocation
decisions, spectrum standardization decisions, spectrum availability decisions,
technology innovations, component development, signal processing and switching
enhancements, and intervendor cooperation have to take place before the vision
of 4G will materialize. 3G experiences—good or bad,
technological or business—will be useful in
guiding the industry in this effort.Providing mobile communication
services based on new technology such as 4G technology involves more than
simply proposing and proving technology—it also requires
field-testing of functions and performance, standardization of technical
specifications, development of mobile terminals, and construction of network
facilities. A basic approach to the technical issues and system configuration
involved in achieving the capabilities and performance required of the 4G
system based on the research at NTT DoCoMo is described in [100].The major design objectives of
a 4G mobile communication system are (i)
providing higher transmission rates (approximately 100 Mbits/s in an outdoor
mobile environment and gigabit rates indoors) and larger capacity (both in
terms of number of users and traffic volume) than IMT-2000, (ii) a transmission
capacity (bandwidth) of at least 10 times that of IMT-2000 has to be achieved, (iii) for achieving high
throughput and high-level real-time communications, it is necessary to achieve
a low transfer delay time of 50 seconds, (iv) seamless connection and handoff between
heterogeneous access systems, (v) since future services will all be based on IP networks,
efficient transmission of IP packets over wireless connections is also a necessity
and (vi) while
increased capacity is also effective in lowering the bit cost, the cost per bit
must be reduced to between 1/10 and 1/100 of the current levels by reducing the
infrastructure equipment, operation, and construction costs.The major technical issues for
the development of a ubiquitous 4G mobile communication system are the following.(1)
High
capacity and high-rate transmission. IMT-2000 achieves a
transmission rate of 2 Mbps with a 5-MHz frequency bandwidth. Furthermore,
technology for transmission at approximately 10 Mbps with the same frequency
bandwidth using multilevel adaptive modulation and demodulation is under
development [101]. To achieve rates of 100 Mbps to 1 Gbps, larger frequency
bandwidth and new transmission systems are required that are suited to
high-rate transmission. A radio access system that can transmit packets
efficiently with considering
the importance of indoor area coverage in the future allows the use of both indoors and
outdoors. To obtain the broadband frequencies for achieving high-rate
transmission and meet the expected large increase in data traffic demand, new
frequency bands must be considered.(2)
Lower
costs. Using a higher frequency band to achieve a higher
transmission rate generally reduces the area of the cell that a base station
can cover. Retaining the original coverage area therefore requires more base
stations, and this increases the network cost. It is therefore necessary to
expand the cell radius by using higher performance radio transmission and circuit
technology such as improved modulation/demodulation techniques that can cope
with a low signal-to-noise ratio, adaptive array antennas, and low-noise
receivers. To further reduce the system construction and operating costs, a
study of diversified entrance links that connect base stations to the backbone
network, autonomous base station control technology, and multihop radio
connection technology employing simple relay stations is required.(3)
Interconnection
based on IP networking. To enable international roaming, a
terminal that can be configured to work with multiple systems based on software
defined radio (SDR) technology [102] could be an effective way to cope with
introductory periods and differences in operating frequency bands among different
countries and regions. Furthermore, future mobile communication networks will
be integrated with heterogeneous access methods and various kinds of cells with
interconnection capabilities based on IP networking. Accordingly,
interconnection and handover between such various access systems are required
in addition to handover and roaming within one mobile communication system.The system configuration for
the 4G mobile communication system is as follows. (i) IP-based connection configuration:
4G systems will be configured for connection to IP networks, considering
efficient transmission of IP packets, coexistence with other access systems,
ease of system introduction, expandability, and other such factors. IP networks
can also connect with or accommodate wireless access systems other than 4G
systems. (ii) Cell classification and configuration according to the
communication environment: the 4G system has cells for outdoors, indoors, and
inside moving vehicles. Outdoor cells cover a wide area, unlike the hotspot
areas of wireless LANs, and allow high-rate packet transfer for fast-moving
terminals. Indoor areas are covered by indoor access point (APs), because the
radio waves to/from outdoor base stations suffer large attenuation. Indoor APs
are designed not only to provide a high rate transfer and simple operation, but
also to compete with expected future wireless LANs [142, 143]. A multihop
connection, which is effective in expanding the cell size is being investigated
as a way to overcome dead spots caused by shadowing. Data transmission via
relay stations is expected to allow communications even when the effects of
limited terminal transmitting power and radio wave propagation attenuation are
large [103]. (iii) Multimedia communications: conventional IP networks have
provided mainly best-effort services, but with real-time applications expected
to increase as multimedia communication diversifies, the importance of services
that take into account QoS is also expected to increase. The 4G system
configuration allows for a mechanism that guarantees the transmission rate to
some extent and that prioritizes packet transfer by the packet type in
cooperation with the IP network for QoS-aware packet transmission on a mobile
radio link, which is the bottleneck.


## 7. Next-Generation (xG) Telecardiology  Network Architecture

Next-generation cardiac monitoringsystem provides ubiquitous monitoring to patients
wherever and whenever necessary as shown in Figure1. It consists of wearable
and light-weight wireless biomedical sensors (for measuring 3 lead ECG, Spo2,
heart beat, and blood pressure) which constantly communicate to the monitor, a
unit about the size of a mobile phone or PDA. The monitor
is battery powered and equipped with signal processing/conditioning module,
memory, and different wireless interfaces and radios. Major features of xG system are the following.(i)
The signal processing module
carries out local analysis of recorded physiological measurements and transmits
them based on the patient-specific monitoring thresholds and response
parameters, such as timing and frequency of response, as predetermined by the
health provider.(ii)
When the monitor detects an
abnormal or arrhythmic event, it automatically transmits the ECG and other
measurements to the health provider in real-time (with an alarm signal, if
required) as discussed below. Or, when a patient experiences symptom(s), he/she
can transmit the physiological measurements, symptom(s), and activity data
through a monitor touch-screen.(iii)
The system is equipped with
multiple radios and wireless interfaces for connectivity to different wireless
networks such as 3G cellular, WLAN, WiMax, and wireless ad hoc (for multihop
relaying). This enables the system to connect to the best available network
depending on various QoS parameters.(iv)
Location-based services using
Global Positioning System (GPS) for positioning, geographic information systems
and location management functions. This would enable the user to access nearby
emergency services whenever required.(v)
Generation of alarm signals
when (a) abnormal medical situation is detected, (b) health provider sends
instructions to the patient or needs additional information from the patient,
(c) when the system is unable to contact the health provider and send data, (d)
when the system is unable to detect signals from patient’s sensors, and (e)
when the system is low on battery.Figure 1
Ubiquitous monitoring of patients
using xG networking.The cardiac patients in xG
systems could be divided into the following categories based on the severity of
their health conditions as detected by the system based on the thresholds set
by health provider. The health provider while prescribing the system to the
patient assigns a particular class to the patient. This class is automatically
changed by the transport protocol in the system depending on the severity of
the health condition as
follows.(i)
Class
0 (highest priority requiring real-time monitoring). Patients
in emergency conditions like the patients in the ambulances or in the following
medical conditions:(a)
ventricular
fibrillation (VF), ventricular tachycardia (VT) with hemodynamic compromise,
electromechanical dissociation (cardiac standstill) indicating risk of sudden
cardiac death requiring medical assistance in less than 3 minutes;(b)
stable
VT with no hemodynamic compromise but still indicating very high risk of sudden
cardiac death requiring medical assistance in 15–20 minutes;(c)
AF
with fall in BP and SpO2 indicates that ventricle is also beating fast, which
is life threatening. Arrhythmias (such as short runs of VT) that precede and
succeed a heart attack (i.e., myocardial infarction) and also precede sudden
cardiac death requiring medical assistance in 30 minutes.(ii)
Class
1 (requiring near real-time monitoring within few hours). The
patients experience the following: abnormal
rhythms, such as atrial flutter, paroxysmal atrial fibrillation, fast
supraventricular tachyarrhythmia, sinus bradycardia like sick sinus syndrome or
mobitz type 2 block.(iii)
Class
2 (requiring periodic monitoring such as twice daily).(a)
Patient
with recurrent episodes of AF of more than 10 minutes for 4-5 times in a day
who is not covered by anticoagulant like “comudin.” Health provider should be
notified so that he/she can be put on blood thinning drug “comudin” to prevent
development of highly morbid and often mortal disease, such as stroke.(b)
Patient
with recurrent and prolonged AF (frequency and duration?) associated with fast
ventricular rate (150–200). Health provider should be notified for change in
treatment to prevent development of sudden cardiac death.(iv)
Class
3 (requiring monitoring from time to time).(a)
Patients
with heart failure who are at risk of SCD but are not candidates to get ICD
implantation. Based on the monitoring results, some of such patients may be
triaged to get an ICD despite not fulfilling the criteria.(b)
Patients
with syncope of unknown etiology, dizziness, lightheadedness, palpitations.(c)
Patients
with obstructive sleep apnea to evaluate possible nocturnal arrhythmias.(d)
Patients
requiring arrhythmia evaluation for etiology of stroke or transient cerebral
ischemia, possibly secondary to atrial fibrillation.The cardiac telehealth
application has to coexist with other telemedicine, emergency, and consumer
applications on public wireless networks. These applications have different
bandwidth (text, audio, video), reliability, and delay requirements. Though the
bandwidth utilized by cardiac telehealth data could be much less than many
multimedia applications, reliable and low latency transmission of the data
could become challenging in many situations such as heavy traffic load and
unavailability of reliable wireless link in dead or hot spots.The unpredictable xG wireless
network shown in Figure2 could be a combination of wireless and wired
networks. The wireless networks are in turn a combination of WLANs (like Wi-Fis
of offices and other buildings), WiMAX networks, 3G cellular and ad hoc
wireless networks.Figure 2
Unpredictable xG network
over which the data has to be reliably sent to the remote health provider.As discussed earlier, xG system
has the capability to connect to different networks simultaneously, whereas the
other routers including the edge routers shown in Figure2 may or may not have
this capability. The backbone network is always chosen as the wired Internet.
The front-end networks are chosen by the system based on patient’s location,
required telehealth service class, and condition of available networks. The
cardiac telehealth data could be sent in either a single hop or multihop
manner. The multihop transfer of medical data is justified in cases of
nonavailability of cellular connection in some portions of a building due to
fading or interference from other networks. The data is then sent through
personal area networks or Wi-Fi networks available and finally through the Internet
or through a cellular base-station.xG system first senses for the
available networks and tries to obtain information about their available
bandwidth, traffic characteristics, maximum delay, and so forth. As shown in
Figure2, the patient can either connect to a Wi-Fi network, which could exist
in a WiMax network, or could pick up an ad hoc network. The data sent by the
patient reaches the service provider through the Internet, which is the backend
network or Wi-Fi or cellular network. Another critical issue of the system is that when it is unable to
connect to an intermediate network, it immediately tracks a group of closely available
systems (through location-based services) to whom it can directly communicate,
selects the system that has the best connectivity in terms of network resources
like available bandwidth, traffic through the network, and then may send the
data simultaneously through all of them. This process requires tracking of
neighboring systems, negotiation for cognizance of the network parameters, and selection
of the best system to reduce the delay of data transfer to the nearest
emergency rescue squad.When xG system is unable to
find any network for data transmission, it stores the data in its memory and
transmits it as soon as it can establish connection with a network. When
network connection is not available and the signal processing module detects an
abnormal medical measurement, the patient may be suitably alerted by the system
to contact health provider or seek medical help by locating nearby health
facility with the help of GPS unit.


## 8. Conclusions

This paper provides an overview of telecardiology systems via wireless and mobile technologies. Especially, we
covered 1G∼XG evolutions and their QoS requirements. There are many pitfalls
encountered when creating a mobile telecardiology network. Firstly, the hardware itself must be wearable
and reliable as it will be worn for long periods of time in various
environments. Secondly, sensor
communication to a base-station, also worn on the body, requires additional
research as the interference from multiple sensors does not scale
linearly. Thirdly, the communication
from base-station to doctor must traverse multiple network types (3G, WiFi, 4G,
Bluetooth, etc.) with different packet size requirements and data loss
parameters. New protocols must be
devised that allow for transmission across all networks with a consistent
quality of service; because patients have differing severity of health, and
sensors have different media to transmit (video, sound, text, etc.), the QoS
can be different from patient to patient. In this paper, we addressed
telehealth problems along with existing technologies mitigating these
issues. This included the advent of xG
system which can operate across a few networks with some quality of
service. In sum, there are a wide
variety of problems that must be overcome to make mobile telecardiology a
reality.Table 1
Parameter3G (including 2.5G, sub 3G)4GMajor requirement, Driving architecturePredominantly voice driven-data was always add onConverged data and voice over IPNetwork architectureWide area cell-basedHybrid-integration of wireless LAN (Wi-Fi, Bluetooth) and wide areaSpeeds384 Kbps to 2 Mbps20 to 100 Mbps in mobile modeFrequency bandDependent on country or continent
(1800–2400 MHz)2–8 GHzBandwidth5–20 MHz100 MHz (or more)Switching design basisCircuit and packetAll digital with packetized voiceAccess technologiesW-CDMA, 1xRTT, edgeOFDM and MC-CDMAForward error correctionConvolutional rate 1/2, 1/3Concatenated coding schemeComponent designOptimized antenna design, multiband
adaptersSmarter antennas, software multiband and
wideband radiosIPA number of air link protocols, including IP 5.0All IP (IP6.0)



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*Source: 459185-2008-06-30.xml*