Comparative Analysis of Short-range Wireless Technologies for

m-Health: Newborn Monitoring Case Study

Fernando Crivellaro

1 a

, Anselmo Costa

and Pedro Vieira

1 b

Faculty of Science and Technology, NOVA University of Lisbon, Caparica Campus, 2829-516 Caparica, Portugal

Departament of Pediatrics, Hospital Garcia de Orta, EPE, Almada, Portugal

Keywords:

Short-range, Wireless, Healthcare, mHealth, Internet of Things, WBAN, Newborn.

Abstract:

The Healthcare and the Internet of Things (IoT) are being integrated to improve the people life quality in

many aspects, as for example, through the increasing of the patients wellness and also optimizing Hospitals

activities. One of the main actors in this integration is the communication link that connects the people to

the systems, which is made in most of the cases through wireless devices. There are many available wireless

technologies to be applied in a great diversity of healthcare scenarios, in which would stands out speciﬁc

technologies advantages for each one. Therefore, among the great number of information about it, in this work

it is detailed the physical layer characteristics of 9 most used technologies in short-range wireless applications

for healthcare. Also, it is made a technology selection for one speciﬁc application scenario of newborn babies

monitoring.

1 INTRODUCTION

The information and communication evolution of

healthcare, as a consequence of the globalization,

quick technological developments or even unexpected

reality of pandemic scenarios, is called e-health. It

represents a mean of improving health services ac-

cess, efﬁciency and quality, having one of its branches

called m-Health, which is basically the practice of

medicine and public health supported by mobile smart

healthcare wireless devices (European mHealth Hub,

2020; Watson et al., 2020; Maksimovi

c and Vujovi

2017).

In this context, the Internet of Things (IoT) plays

a key role by enabling, for example, constant medical

supervision through patients remote healthcare moni-

toring, instead of staying in hospital for monitoring of

vital signals. However, despite the IoT-based health-

care advances, there are some research challenges

to be addressed in short-range wireless communica-

tions, being energy efﬁciency considered as one of

the key concerns about it. From this energy point

of view, usually the communication module draws

more power than sensing or even data processing. Al-

though the transmission power increasing eventually

can improve the communication reliability, this ap-

https://orcid.org/0000-0002-7534-9149

https://orcid.org/0000-0002-3823-1184

proach does not contribute to the energy efﬁciency

nor to the effects of radiation on human body, what

is also an important factor for wireless sensors net-

works placed in, on or around the human body (Roy

and Chowdhury, 2021).

This wireless communication in the vicinity or in-

side the human body are called Wireless Body Area

Network (WBAN) and uses existing industrial scien-

tiﬁc medical (ISM) bands as well as frequency bands

approved by national regulatory authorities (IEEE Std

802.15.6, 2012).

A comprehensive understanding of WBAN archi-

tecture is its division into tiers. The Tier-1 which

covers the intra-WBAN communication, that is, the

network interaction of small-sized, low-power sensor

nodes and their respective transmission ranges. The

body signals are forwarded to a hub device that can

act as a network coordinator of a star or mesh topol-

ogy and transmit the concentrated data to the Tier-

2. The Tier-2 covers the inter-WBAN communica-

tion, which is the communication between the hub in

Tier-1 with a gateway at Tier-2. Here are also in-

cluded eventually more patients Tier-1 communica-

tions handled by the same or others Tier-2 gateways.

Finally, the Tier-3 is application-speciﬁc and essen-

tially used to bridge the connection from Tier-2 to a

database, for example, for knowledge discovery and

decision-making (Movassaghi et al., 2014). The Fig-

Crivellaro, F., Costa, A. and Vieira, P.

Comparative Analysis of Short-range Wireless Technologies for m-Health: Newborn Monitoring Case Study.

DOI: 10.5220/0010611700990106

In Proceedings of the 18th International Conference on Wireless Networks and Mobile Systems (WINSYS 2021), pages 99-106

ISBN: 978-989-758-529-6

ure 1 presents this Tier approach applied to the new-

born monitoring case study.

Therefore, the objective of this work is to con-

tribute with technical discussions around the use of

WBANs in healthcare through the comparison of

most used Tier-1 radio technologies, and also enlight-

ening some requirements, challenges and possible so-

lutions for an exempliﬁed application scenario.

1.1 Related Work

A survey on emerging IoT-based healthcare com-

munication standards and technologies was made by

(Garda

sevi

c et al., 2020), with the comparison of low-

power wireless technologies. However, it is not con-

sidered the different network topologies and it is not

clear about the energy efﬁciency analysis performed.

The short-range wireless comparative study made

by (Vidakis et al., 2020) considering Bluetooth, BLE,

Near Field Communication (NFC) and Wi-Fi Direct

concluded that Bluetooth is the ideal candidate for the

healthcare domain, when considered the transference

of large medical ﬁles.

In terms of power consumption, the study made by

(Thomas et al., 2016) conclude that Wi-Fi can con-

sume less power than Bluetooth Low Energy (BLE)

due to the capacity of retaining the network connec-

tions in sleep mode. However, it is not speciﬁed

important conﬁgurations of the communication mod-

ules, as for example the transmission power, which

has a huge impact on energy consumption.

In the study made by (

Culjak et al., 2020), the

ultra-wideband (UWB) technology has not been yet

adapted in everyday use and commercial devices be-

cause the relevant standards that regulate their use

have appeared only recently. Also there are still being

developed intensive research to overcome obstacles in

the inﬂuence of random body movements and UWB

antenna, for example.

The work developed by (Seferagi

c et al., 2020) re-

marks that the absence of random backoff in Blue-

tooth Low Energy (BLE) would increase the collision

probability, decreasing the reliability and scalability

of BLE mesh networks.

The review made by (Abugabah et al., 2020) iden-

tiﬁed challenging factors related to radio-frequency

identiﬁcation (RFID) efﬁcient implementation, for

example, the cost effectiveness, troubles with metals

and liquids, difﬁculty in training, ethical issues related

to breach of privacy and narrow channel bandwidth.

About the electromagnetic ﬁeld (EMF) related to

wearable devices, (Zradzi

nski et al., 2020) suggest

that emissions below 3 mW of equivalent isotropi-

cally radiated power (EIRP) from wireless communi-

cations modules may be considered environmentally

insigniﬁcant EMF sources.

2 APPLICATION SCENARIO

The scenario that is being considered in this short-

range wireless technology analysis comprehend the

operation of multiple non-invasive sensors distributed

through a WBAN, more speciﬁcally (but not exclu-

sively), in newborns, as presented in Figure 1.

When compared to adults, newborns cannot artic-

ulate pain and uneasiness, therefore, the continuous

monitoring of vital signs of newborns are very im-

portant, specially in cases of pre term or critically ill

newborn (Memon et al., 2020).

So, the concept is to perform non-invasive mea-

surements of oxygen saturation, heart rate, respiratory

rate, temperature and transcutaneous bilirubin from

the baby birth until at least the second day of life, or

even a week in more critical cases. For hospital cases,

the newborn can be monitored until discharge or even

in post-discharge if necessary.

Tier-1

Tier-2

Hub

Node

Gateway

Tier-3

Figure 1: Example of application scenario.

The measure data is gathered by one of the sensors

with the hub network role in Tier-1, which performs

the interconnection with a Tier-2 gateway. In Tier-

3, the network technology is highly dependent on the

local of application deploy (hospital or remote mon-

itoring at home, for example) and it is out the focus

of this study. Also, it is considered in this article that

security concerns are more relevant in the Tier-3 and

should be addressed in a speciﬁc study applied to it.

Among the sensors measurements mentioned

WINSYS 2021 - 18th International Conference on Wireless Networks and Mobile Systems

100

above, there are signals monitored in common rou-

tine procedures (respiratory rate, bilirubin) and also

signals (oxygen saturation, heart rate, respiratory rate,

temperature) that are normally continuously evalu-

ated in more critically situations/environments, like

pre terms in intensive care units (Chen et al., 2010).

In relation to data rate, it is estimated that the

list of the above measurements could be transmitted

with a period of about 2 seconds. Also, the measured

data could be ﬁrst evaluated in the node and then be

transmitted only when signiﬁcant deviations occurs.

(Philip et al., 2021).

Another important point to be considered in this

application is the electromagnetic risk of using wire-

less communication in sensors placed on the patient

skin. As pointed by (Calvente et al., 2017), the fact

that the newborns are at a vulnerable stage of de-

velopment and the electromagnetic exposure impact

on premature newborns is unknown, the use of wire-

less equipments in neonatal care unit environments

should have a prudent avoidance strategy (Magiera

and Solecka, 2020).

According to the recommendation (Ziegelberger

et al., 2020) of the European Union and the Interna-

tional Commission on Non-ionizing Radiation Pro-

tection (ICNIRP), it is used the Speciﬁc Absorption

Rate (SAR, W/Kg) measure to evaluate the human

body exposition to radio frequencies. For frequen-

cies from 10 MHz to 10 GHz, the average permissible

SAR for the entire human body is 0.08 W/Kg, with

speciﬁc values of 2 W/Kg for head and torso, while

for limbs this value is 4 W/Kg.

3 TECHNOLOGIES

COMPARISON

The objective of this comparison is to decide which

short-range wireless technology best ﬁt the more im-

portant requirements for the exempliﬁed application

scenario of healthcare.

3.1 Requirements

The requirements were summarized into 3 main con-

cerns: patient safety, network reliability and network

performance, which are detailed below.

3.1.1 Patient Safety

Considering the patient safety as the ﬁrst requirement,

the radio transmission power in WBANs should be

the lowest power possible in order to minimize the

heating of patient body tissues, while also reduces the

chances of interference of signals and preserves en-

ergy. According to the study made by (Yu-nan et al.,

2006), considering a body-worn Bluetooth device, the

peak SAR for an antenna output of 100 mW is 2.54

W/Kg (above the 2 W/Kg required by ICNIRP). The

study also suggest that the SAR levels will be lower

than the safety limits for an antenna output power be-

low 80 mW, which is considered as the limit required

for this case study.

However, lowering power during transmissions

can result in a poor link performance, especially for

non-line-of-sight (NOL) between the communication

nodes. In order to overcome this kind of issues, rout-

ing techniques as relay-based routing have been pro-

posed in (IEEE Std 802.15.6, 2012).

3.1.2 Network Reliability

The second relevant requirement is the capacity of the

network to handle the nodes distributed around the

patient body. Also, the body position is of substan-

tial importance for the WBAN network because baby

sleep posture, for example, can lead to a long duration

of link disconnection compared to other human pos-

tures. Therefore, the network topology should allow

dynamic adaptation to keep the necessary data ﬂow-

ing (Vyas et al., 2021).

The number nodes depends on the hardware in-

tegration of the sensors and the satisfactory mea-

surement locations on the body, but an estimative of

around 4 nodes is considered sufﬁcient for the above

mentioned monitored signals.

In relation to the number of patients, it depends

on the physical space as well as the type of patient,

being considered a maximum estimative of around 8

newborn patients in the Tier-2 for this case.

3.1.3 Network Performance

Another requirement is the capacity of handle the

measurement data generated by the sensors.

For the considered sensors nodes, it was ﬁrstly es-

timated to reach a maximum data rate of around 100

kb/s per node, which is considered a low bandwidth in

comparison to a 25 lead ECG at 500 Hz being trans-

mitted in real time, for example (Philip et al., 2021).

However, tt has to be noted that the integration

of more than one measurement in the same node

will need more throughput for it as well as the over-

all number of measurements will directly impact the

Tier-1/Tier-2 link data rate. Therefore, for this case

study and considering the network topology dynamic

adaptation, the Tier-1 node data rate requirement is

stipulated for at least 500 kb/s.

Comparative Analysis of Short-range Wireless Technologies for m-Health: Newborn Monitoring Case Study

101

3.2 Technologies

About the technologies selection, it was found 9

main technologies that are related to WBAN and

which are evaluated in this comparison. The Blue-

tooth/Bluetooth Low Energy (BLE) and Wi-Fi are the

most used wireless technologies found in literature for

smart healthcare applications, followed by ZigBee,

and RFID. There are studies mentioning/comparing

the use of Wi-Fi Direct, Z-Wave, Thread and UWB,

which are also included in the analysis (Albahri et al.,

2021; Vidakis et al., 2020; Ahad et al., 2020). Each

technology features are detailed below, with special

attention to the physical layer, which is the main fo-

cus of this study.

In Table 1 there is a summary of the technologies

comparison for a quick evaluation of each network

technology characteristics.

3.2.1 Bluetooth

The Bluetooth operation is based on its actual spec-

iﬁcation, Core v5.2, which spans from physical to

application layers. Bluetooth devices operate in

the unlicensed 2.4 GHz Industrial Scientiﬁc Medi-

cal (ISM) band using Adaptive Frequency Hopping

(AFH) through 79 radio frequency (RF) channels of 1

MHz in order to stablish robust communications with

less interference. The modulation technique is Gaus-

sian Frequency Shift Keying (GFSK) with a mode

called Basic Rate, that has a data rate of 1 Mb/s, and

another called Enhanced Data Rate, with a data rate

of 2 Mb/s or 3 Mb/s. The devices are classiﬁed into

three power classes based on the maximum transmit-

ter output power: class 1 (1 mW - 100 mW), class

2 (0.25 mW - 2.5 mW) and class 3 (1 µW - 1 mW)

(Bluetooth SIG, 2019).

3.2.2 BLE

The BLE operation is similar to Bluetooth (ISM fre-

quency band, AFH) and it is also based on Core v5.2

speciﬁcation. However, BLE has only 40 RF chan-

nels, which are spaced by 2 MHz each other, being

3 of them used for advertising, while the other 37

are available for use during connected communica-

tion. BLE also uses GFSK modulation technique and

deﬁne two modulation schemes. The 1 Msym/s mod-

ulation scheme supports a data rate of 1 Mb/s with

uncoded data or 125 kb/s - 500 kb/s for coded pay-

load. The 2 Msym/s modulation scheme supports a

data rate of 2 Mb/s with uncoded data. About the

transmission power, it is divided into 4 classes: class

1 (10 mW - 100 mW), class 1.5 (10 µW - 10 mW),

class 2 (10 µW - 2.5 mW) and class 3 (10 µW - 1

mW) (Bluetooth SIG, 2019).

3.2.3 Wi-Fi

The Wi-Fi 6 label in a device implies that its oper-

ation is certiﬁed by the Wi-Fi CERTIFIED 6™ pro-

gram, which is based on the IEEE 802.11ax standard.

The Wi-Fi network operates over the 2.4 GHz, 5 GHz

and also 6 GHz bands in United States (other coun-

tries worldwide regulatory bodies are taking steps to

expand Wi-Fi access to the 6 GHz band). Counting

with the 6 GHz band, the Wi-Fi operates over up to

59 channels of 20 MHz or 29 channels of 40 MHz

or 14 channels of 80 MHz or even 3 channels of 160

MHz. The IEEE 802.11ax mandatory use of Low-

Density Parity Check (LDPC) and Binary Convolu-

tional Encoding (BCC) coding techniques, as well as

Dual Carrier Modulation (DCM), contribute to the

robustness enhancing of radio transmissions. With

1024-QAM as the highest modulation together , the

data rate can theoretically reach up to 9.6 Gb/s con-

sidering the channel bandwidth of 160 MHz and 8

spatial stream. Considering the transmission power in

Europe, the limits are 0.1 W for 2.45 GHz band and

0.2 or 1 W for devices in the 5.2 and 5.5 GHz bands

respectively. On the other side, there are devices that

allows decrease the transmission power until around

1 mW (Qu et al., 2018; Foster and Moulder, 2013).

3.2.4 Wi-Fi Direct

The Wi-Fi Direct, speciﬁed in Wi-Fi Direct 1.8, op-

erates over IEEE 802.11 and has the approach of

Peer-to-Peer (Pr-to-Pr) devices interconnection, with-

out joining a traditional Wi-Fi home, ofﬁce or public

network. The idea is to simplify the data sharing be-

tween devices, therefore, multiple connections is an

optional feature that is not supported by all Wi-Fi Di-

rect devices. The frequency bands are 2.4 GHz and

5 GHz, not being mandatory the support for both fre-

quency bands. (Vidakis et al., 2020; Alliance, 2020).

3.2.5 ZigBee

The ZigBee speciﬁcation, ZigBee 2015, assumes the

use of the physical layer deﬁned in the IEEE 802.15.4.

A compliant ZigBee device shall support one of the

following options: offset quadrature shift-keying (O-

QPSK) at 2.4 GHz frequency band (16 channels) or

binary phase shift-keying (BPSK) at both 868 MHz (1

channel) and 915 MHz (10 channels) bands. The the-

oretical network size, limited by the destination ad-

dress frame ﬁeld, is 65535, while the network topol-

ogy can be organized as star and mesh. About the

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Table 1: Technologies comparative table.

Technology

Last

Speciﬁcation

Physical

Layer

Frequency

Network

Size

Topology

Data

Rate

Power

Bluetooth Core 5.2 Core 5.2 2.4 GHz 8

Star

Pt-to-Pt

1 Mb/s

3 Mb/s

1 µW

100 mW

BLE Core 5.2 Core 5.2 2.4 GHz 32000

Star

Pt-to-Pt

Mesh

125 Kb/s

2 Mb/s

10 µW

100 mW

Wi-Fi

CERTIFIED

6™

IEEE

802.11ax

2.4 GHz

5 GHz

6 GHz

250

Star

Pr-to-Pr

up to

9.6 Gb/s

1 mW

1 W

Wi-Fi

Direct

Wi-Fi

Direct 1.8

IEEE

802.11

2.4 GHz

5 GHz

Star

Pr-to-Pr

up to

250 Mb/s

1 mW

100 mW

ZigBee

2015

IEEE

802.15.4

868 MHz

915 MHz

2.4 GHz

65535

Star

Mesh

20 Kb/s

250 Kb/s

0.5 mW

CRL*

Thread Thread 1.2

IEEE

802.15.4

2.4 GHz 16352

Star

Mesh

20 Kb/s

250 Kb/s

0.5 mW

CRL*

UWB

WiMedia

UWB

Alliance

FiRa

IEEE

802.15.6

802.15.4z

ISO/IEC

26907

3.1 GHz

10.6 GHz

8 Pr-to-Pr

53.3 Mb/s

1024 Mb/s

74 nW

15 mW

Z-Wave

Plus v2

ITU-T

G-9959

865 MHz

923 MHz

232 Mesh

9.6 Kb/s

100 Kb/s

CRL-20 dB

CRL

RFID

ISO/IEC

18000

ISO/IEC

18000

120 kHz

5.8 GHz

2 Pt-to-Pt

4 Kb/s

848 Kb/s

1 mW

1 W

transmission power, the maximum value shall con-

form with each country regulated limit (CRL) and the

minimum value can reach the 0.5 mW. The standard

provide a raw data rate high enough (250 kb/s) to sat-

isfy a set of applications but is also scalable down to

the needs of sensor and automation needs (20 kb/s) for

wireless communications (IEEE Std 802.15.4, 2020;

Zigbee Alliance, 2008).

3.2.6 Thread

Thread is a technology based on Internet Protocol

(IPv6) communication, with the last speciﬁcation

Thread 1.2.

It also uses the IEEE 802.15.4 Physical layer

speciﬁcations, operating at 250 kb/s in the 2.4 GHz.

Thread devices use 6LoWPAN standard for transmis-

sion of IPv6 packets over IEEE 802.15.4 networks.

The network topology can be star (only one device

of type Router, which provide routing services to

Thread Devices in the network) or mesh (more than

one Router device). The theoretical limit in number

of addressable devices in a thread network is 16352

(32 routers + 511 end devices per router). The sup-

ported channels of the 2.4 GHz frequency band are

11-26 (the same as ZigBee), with O-QPSK, while the

transmission power follow the values presented for

ZigBee. (Lammle, 2020).

3.2.7 UWB

The ultra-wideband (UWB) is a technology with the

physical and media access control layers described

in the IEEE 802.15.4 and 802.15.6 standards, de-

ﬁned as an antenna transmission for which emitted

signal bandwidth exceeds the lesser of 500 MHz or

20 % of the arithmetic center frequency. In this

scenario, the UWB Alliance and FiRa organizations

are active players in the UWB operation, promo-

tion and certiﬁcation. Also, WiMedia works towards

the use of UWB for wireless USB and streaming

video applications. According to IEEE 802.15.6-

Comparative Analysis of Short-range Wireless Technologies for m-Health: Newborn Monitoring Case Study

103

2012, the UWB operates through 11 channels of

500 MHz in the corresponding frequency bands of

3.25 to 4.74 GHz and 6.24 to 10.23 GHz. The

UWB physical speciﬁcation deﬁnes two radio oper-

ation technologies. The Impulse Radio UWB (IR-

UWB), which supports the On-off keying (OOK),

Differential-BPSK (DBPSK) and Differential-QPSK

(DQPSK) modulation schemes. The Frequency Mod-

ulation UWB (FM-UWB), which uses Continuous

Phase Binary FSK (CP-BFSK) modulation over an-

other wideband FM modulation. The transmit power

levels are in the range of about 74 nW to 1 mW,

with time restrictions for the TX pulses. The wireless

USB and streaming video applications runs over the

UWB branch called high-rate ultra-wideband, which

is speciﬁed by ISO/IEC 26907 and WiMedia 1.5. The

high-rate UWB utilizes the 3.1 to 10.6 GHz spec-

trum divided into 14 channels of 528 MHz, uses

the MultiBand Orthogonal Frequency Division Mod-

ulation (MB-OFDM) scheme to transmit information

with data rates from 53.3 Mb/s until 1024 Mb/s. The

transmit power range in this case is 1 to 15 mW (IEEE

Std 802.15.4, 2020; Niemel

a et al., 2017; Ullah et al.,

2013; WiMedia Alliance, 2009).

3.2.8 Z-Wave

Extensive used in residential systems, Z-Wave oper-

ates over ITU-T G-9959 standard and Z-Wave Plus v2

speciﬁcation for the upper layers. The transmit power

level as well as the frequency operation in sub-1GHz

is country dependent, ranging from 865 MHz to 923

MHz through one, two or three channels. The Z-Wave

network operates in mesh and with a maximum of 232

nodes. The data rate is speciﬁed to a range of 9.6 kb/s

to 100 kb/s, being the frequency shift keying (FSK)

modulation scheme used for lower data rates, while

Gaussian frequency shift keying (GFSK) is used for

the 100 kb/s (ITU, 2015).

3.2.9 RFID

The radio-frequency identiﬁcation RFID has 4 ba-

sic point-to-point wireless technology types, low fre-

quency (LF) and high frequency (HF) passive, which

use magnetic coupling to transfer power and data,

while ultra high frequency (UHF) passive and active

are based on e-ﬁeld coupling. The devices speciﬁ-

cation are present along the ISO/IEC 18000 series,

being the LF passive operation frequency below 135

kHz, the HF at 13.56 MHz, the UHF passive in 868

and 950 MHz and UHF active in 433 MHz and 5.8

GHz. The RFID data rates are related to the carrier

frequency, ranging from 4 kb/s to 848 kb/s, while the

transmit power level is between 1 mW and 1 W (Lan-

daluce et al., 2020; Pardal and Marques, 2010).

4 DISCUSSION

Every short-range wireless technology has its own ad-

vantages and disadvantages depending on the applica-

tion scenario and consequently on the requirements.

Below is detailed all the requirements fulﬁlment and

in Table 2 is presented a summary of what require-

ments each technology is able to achieve.

Considering the presented application scenario

and the respective requirements, all the analysed tech-

nologies can reach the required level of transmitted

power of 80 mW, with some of them reaching the nW

or µW scale, UWB, Bluetooth and BLE, which rein-

force the prudent EMF exposure strategy suggested

by (Magiera and Solecka, 2020).

The network reliability, in contrast to industry sce-

nario evaluated by (Seferagi

c et al., 2020), for this

application scenario is highly based on the network

topology, since the transmitted power is bounded by

the safety constraint. Therefore, the link issues can

be addressed by the two-hop extension suggested in

(IEEE Std 802.15.6, 2012), by turning the terminal

and intermediate nodes into the relayed and relaying

nodes, while the hub into the target hub of the relayed

node.

In the study made by (Di Franco et al., 2014) with

ZigBee in a mesh topology, the experiments showed

that the use of off-body relay scheme offers the best

data reliability and network lifetime at all power lev-

els.

The multi-hop communication is intrinsic for

mesh networks, while for others topologies, like star,

it is not clear. The technologies that fulﬁl this require-

ment are BLE, ZigBee, Thread and Z-Wave.

The network performance in healthcare is related

to the measurements temporal dynamics and their im-

pact on the patient wellness. For the considered ap-

plication scenario, it was estimated the requirement

of 500 kb/s, which is supported by Bluetooth, BLE,

Wi-Fi, Wi-Fi direct, UWB and RFID.

However, if it is only sent an alarm when some

measurement deviation occurs, all the technologies

probably would support the demanded data rate.

Therefore, considering the overall requirements

(Table 2), the BLE stands out as the best ﬁtted short-

range wireless technology for the newborn monitor-

ing application scenario exempliﬁed in this work.

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104

Table 2: Fulﬁlment of requirements.

Safety Reliability Performance

Bluetooth

BLE

Wi-Fi

Direct

ZigBee

Thread

UWB

Z-Wave

RFID

5 CONCLUSIONS

The wireless technologies analysis are relevant sum-

marized knowledge that needs to be updated periodi-

cally due to the continuous evolution of the speciﬁca-

tions and radio devices.

In this way, this work brings physical layer details

of the 9 most used short-range wireless technologies

in healthcare, with the idea to contribute to the short-

range wireless technology selection not only for the

application scenario presented in this work, but also

contribute as a reference for other application scenar-

ios in the future.

Based on standards and scientiﬁc research, the

application scenario requirements were established.

These requirements were only fulﬁlled by the BLE

technology.

Obviously that layers other than the physical one

should be evaluated and it will be done in future

works. Also, it has to be remembered that differ-

ent protocols can be operated over the same physical

layer, therefore, a detailed understanding of the phys-

ical layer needs contributes to match the right upper

layers protocols for the development solution.

The next steps for this study are the layer expan-

sion in the comparative analysis and also the imple-

mentation of the BLE network of Tier-1 with the use

of multi-hoping and low transmitted power, in order

to validate the best node distribution for the WBAN

network of this case study.

ACKNOWLEDGEMENTS

This research leading to this result has received fund-

ing from Fundac¸

ao para a Ci

encia e a Tecnologia

(FCT) under grant PD/BDE/142935/2018.

REFERENCES

Abugabah, A., Nizamuddin, N., and Abuqabbeh, A. (2020).

A review of challenges and barriers implementing

RFID technology in the Healthcare sector. Procedia

Computer Science, 170:1003–1010.

Ahad, A., Tahir, M., Sheikh, M. A., Ahmed, K. I., Mughees,

A., and Numani, A. (2020). Technologies trend to-

wards 5g network for smart health-care using iot: A

review. Sensors (Switzerland), 20(14):1–22.

Albahri, A. S., Alwan, J. K., Taha, Z. K., Ismail, S. F.,

Hamid, R. A., Zaidan, A. A., Albahri, O. S.,

Zaidan, B. B., Alamoodi, A. H., and Alsalem, M. A.

(2021). IoT-based telemedicine for disease preven-

tion and health promotion: State-of-the-Art. Jour-

nal of Network and Computer Applications, 173(July

2020):102873.

Alliance, W.-f. (2020). Wi-Fi Direct ® Speciﬁcation.

Bluetooth SIG (2019). Bluetooth Core Speciﬁcation v5.2.

page 3256.

Calvente, I., V

azquez-P

erez, A., Fern

andez, M. F., N

nez,

M. I., and M

noz-Hoyos, A. (2017). Radiofrequency

exposure in the Neonatal Medium Care Unit. Environ-

mental Research, 152(3):66–72.

Chen, W., Oetomo, S. B., Feijs, L., Bouwstra, S., Ayoola,

I., and Dols, S. (2010). Design of an integrated sensor

platform for vital sign monitoring of newborn infants

at Neonatal Intensive Care Units. Journal of Health-

care Engineering, 1(4):535–554.

Culjak, I., Vasi

Z. L., Mihaldinec, H., and D

zapo, H.

(2020). Wireless body sensor communication sys-

tems based on UWB and IBC technologies: State-

of-theart and open challenges. Sensors (Switzerland),

20(12):1–32.

Di Franco, F., Tinnirello, I., and Ge, Y. (2014). 1 Hop or

2 hops: Topology analysis in Body Area Network. In

2014 European Conference on Networks and Commu-

nications (EuCNC), pages 1–5. IEEE.

European mHealth Hub (2020). Case Study: Overview of

mHealth Policies in Portugal. WP5 – Policy and Inno-

vation, 1(September):1–19.

Foster, K. R. and Moulder, J. E. (2013). Wi-Fi and health:

Review of current status of research. Health Physics,

105(6):561–575.

Garda

sevi

c, G., Katzis, K., Baji

c, D., and Berbakov, L.

(2020). Emerging wireless sensor networks and in-

ternet of things technologies—foundations of smart

healthcare. Sensors (Switzerland), 20(13):1–30.

IEEE Std 802.15.4 (2020). IEEE Standard for Low-Rate

Wireless Networks. IEEE Std 802.15.4-2020 (Revi-

sion of IEEE Std 802.15.4-2015), 2020:1–800.

IEEE Std 802.15.6 (2012). IEEE Standard for Local and

metropolitan area networks - Part 15.6: Wireless Body

Area Networks. IEEE Std 802.15.6-2012, pages 1–

271.

ITU (2015). G.9959 : Short range narrow-band digital

radiocommunication transceivers - PHY, MAC, SAR

and LLC layer speciﬁcations. ITU Recommendation.

Lammle, T. (2020). Network Fundamentals. CCNA Certiﬁ-

cation Study Guide, (May):1–28.

Comparative Analysis of Short-range Wireless Technologies for m-Health: Newborn Monitoring Case Study

105

Landaluce, H., Arjona, L., Perallos, A., Falcone, F., Angulo,

I., and Muralter, F. (2020). A review of iot sensing

applications and challenges using RFID and wireless

sensor networks. Sensors (Switzerland), 20(9):1–18.

Magiera, A. and Solecka, J. (2020). Radiofrequency elec-

tromagnetic radiation from Wi-ﬁ and its effects on

human health, in particular children and adolescents.

Review. Roczniki Panstwowego Zakladu Higieny,

71(3):251–259.

Maksimovi

c, M. and Vujovi

c, V. (2017). Internet of Things

Based E-health Systems: Ideas, Expectations and

Concerns.

Memon, S. F., Memon, M., and Bhatti, S. (2020). Wear-

able technology for infant health monitoring: A sur-

vey. IET Circuits, Devices and Systems, 14(2):115–

129.

Movassaghi, S., Abolhasan, M., Lipman, J., Smith, D., and

Jamalipour, A. (2014). Wireless Body Area Networks:

A Survey. IEEE Communications Surveys & Tutori-

als, 16(3):1658–1686.

Niemel

a, V., Haapola, J., H

ainen, M., and Iinatti, J.

(2017). An Ultra Wideband Survey: Global Regu-

lations and Impulse Radio Research Based on Stan-

dards. IEEE Communications Surveys and Tutorials,

19(2):874–890.

Pardal, M. L. and Marques, J. A. (2010). Towards the in-

ternet of things: An introduction to RFID technol-

ogy. Proceedings of the 4th International Workshop

on RFID Technology - Concepts, Applications, Chal-

lenges, IWRT 2010, in Conjunction with ICEIS 2010,

pages 69–78.

Philip, N. Y., Rodrigues, J. J., Wang, H., Fong, S. J., and

Chen, J. (2021). Internet of Things for In-Home

Health Monitoring Systems: Current Advances, Chal-

lenges and Future Directions. IEEE Journal on Se-

lected Areas in Communications, 39(2):300–310.

Qu, Q., Li, B., Yang, M., Yan, Z., Yang, A., Yu, J., Gan, M.,

Li, Y., Yang, X., Aboul-Magd, O., Au, E., Deng, D. J.,

and Chen, K. C. (2018). Survey and performance eval-

uation of the upcoming next generation WLAN stan-

dard - IEEE 802.11ax. arXiv, 1:1461–1474.

Roy, S. and Chowdhury, C. (2021). Remote health mon-

itoring protocols for IoT-enabled healthcare infras-

tructure. In Healthcare Paradigms in the Internet of

Things Ecosystem, pages 163–188. Elsevier.

Seferagi

c, A., Famaey, J., De Poorter, E., and Hoebeke,

J. (2020). Survey on wireless technology trade-offs

for the industrial internet of things. Sensors (Switzer-

land), 20(2):1–22.

Thomas, D., Wilkie, E., and Irvine, J. (2016). Compar-

ison of Power Consumption of WiFi Inbuilt Inter-

net of Things Device with Bluetooth Low Energy.

10(10):1693–1696.

Ullah, S., Mohaisen, M., and Alnuem, M. A. (2013). A re-

view of IEEE 802.15.6 MAC, PHY, and security spec-

iﬁcations.

Vidakis, K., Mavrogiorgou, A., Kiourtis, A., and Kyri-

azis, D. (2020). A Comparative Study of Short-Range

Wireless Communication Technologies for Health In-

formation Exchange. 2nd International Conference on

Electrical, Communication and Computer Engineer-

ing, ICECCE 2020, (June).

Vyas, A., Pal, S., and Saha, B. K. (2021). Relay-based

Communications in WBANs. ACM Computing Sur-

veys, 54(1):1–34.

Watson, A. R., Wah, R., and Thamman, R. (2020). The

value of remote monitoring for the COVID-19 pan-

demic. Telemedicine and e-Health, 26(9):1110–1112.

WiMedia Alliance (2009). Multiband Ofdm Physical Layer

Speciﬁcation. (1.5):204.

Yu-nan, H., Ying-hua, L., Jin-ling, Z., and Xiao-lu, Z.

(2006). The Interaction between PIFA for Bluetooth

applications and a High-Fidelity Human Body Model.

In The 2006 4th Asia-Paciﬁc Conference on Environ-

mental Electromagnetics, pages 331–335. IEEE.

Ziegelberger, G., Croft, R., Feychting, M., Green, A. C.,

Hirata, A., D’Inzeo, G., Jokela, K., Loughran, S.,

Marino, C., Miller, S., Oftedal, G., Okuno, T., van

Rongen, E., R

osli, M., Sienkiewicz, Z., Tattersall,

J., and Watanabe, S. (2020). Guidelines for Limiting

Exposure to Electromagnetic Fields (100 kHz to 300

GHz). Health Physics, 118(5):483–524.

Zigbee Alliance (2008). Zigbee Speciﬁcation. Zigbee Al-

liance website, pages 1–604.

Zradzi

nski, P., Karpowicz, J., Gryz, K., Morzy

nski, L.,

Mły

nski, R., Swidzi

nski, A., Godziszewski, K., and

Ramos, V. (2020). Modelling the inﬂuence of elec-

tromagnetic ﬁeld on the user of a wearable iot de-

vice used in a WSN for monitoring and reducing haz-

ards in the work environment. Sensors (Switzerland),

20(24):1–15.

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