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Survey on Smart Health Management using BLE and BLE Beacons

Authors:
978-1-7281-4177-0/19/$31.00 ©2019 IEEE
Survey on Smart Health Management using BLE
and BLE Beacons
Deepthi Rajamohanan
Amrita Centre for Wireless Networks &
Applications (AmritaWNA)
Amrita School of Engineering
Amritapuri,
Amrita Vishwa Vidyapeetham
India
deepthir@am.amrita.edu
Balaji Hariharan
Amrita Centre for Wireless Networks &
Applications (AmritaWNA)
Amrita School of Engineering
Amritapuri,
Amrita Vishwa Vidyapeetham
India
balajih@am.amrita.edu
K A Unnikrishna Menon
Amrita Centre for Wireless Networks &
Applications (AmritaWNA)
Amrita School of Engineering
Amritapuri,
Amrita Vishwa Vidyapeetham
India
kaumenon@am.amrita.edu
Abstract— Advances in Bluetooth technology focusing low
energy has brought into action the Bluetooth Smart for
wearable devices. Enhancement in Internet of Things due to
wearable devices has led to the concept of Ambient Assisted
Living (AAL). AAL is mainly devised to assist age old people to
carry on daily activities including healthcare without
dependencies. A survey to show the contribution of Bluetooth
Low Energy (BLE) technology in wearable devices is the main
focus of this paper. This paper also aims to give a good
overview of BLE and BLE Beacons as one of the successful
technologies focusing wearable healthcare applications and its
pros and cons compared to other existing wireless technologies.
Different applications of BLE included can be adapted to our
healthcare perspective for smart health management.
Keywords— BLE; BLE Beacons; Ambient Assisted Living;
Healthcare;
I. I
NTRODUCTION
Among many factors considered for evaluating progress
of a country, health conditions of its people is probably the
most important metric. Health of population is decided by
ten health indicators [1] and access to health services is one
among them. With the rural population contributing the
major chunk of the Indian population about 66.46% in 2017
(according to the World Bank collection of development
indicators) [2], monitoring their health and solving health
issues is of major concern. Currently, the available
healthcare facilities are clustered around cities, making its
reach to outskirts difficult and the unwillingness of
physicians to serve in the remote regions makes the situation
worse [3]. In such circumstances, came the idea of remote
patient monitoring system [4]. As a result, a system
integrating smartphones to healthcare devices emerged,
called Smartphone-based “Telemedicine”. It is categorized
into two: 1) online real time-based monitoring, 2) off-line
analysis based on critical parameters acquired from patient
[5].
Our daily life influenced by many miscellaneous
activities varies with person to person. In such scenario
monitoring health conditions continuously without restricting
their mundane activities and physical movement is essential.
Cost is another factor influencing rural areas to be deprived
of medical availabilities [6]. Thus, all these limitations gave
way to a new revolution in medical and engineering field
which came to be known as wearable devices. Evolution of
BLE made this dream come true[7].
These days almost all smartphones are equipped with
BLE. Increase in usage of smart phones in urban as well as
rural areas is a fact utilized for distance health analysis.
Smartphones can be used for different applications such as
messaging, voice calls, online tracking etc. [8]. So, we can
enhance our application blending all these facilities of
mobile and wearable healthcare gadgets to produce a smart
care health system [9].
This paper presents a survey of prior work in BLE and
BLE Beacons innovations in the wearable healthcare devices
domain. The recent trends in Ambient Assisted Living have
been utilized to propose an efficient system in health
perspective. Some other applications based on Smart
Bluetooth have also been reviewed to help researchers
integrate them for overall health management. There has
been constant effort to improve the performance parameters
like charging of battery [10] [11], received signal strength
(RSSI) etc.[12]-[14] of BLE. Current status of these
improvements along with comparisons with other wireless
technologies are also discussed in this paper.
This paper is divided into four sections. Section II talks
about application of BLE and BLE Beacons in medical field
presented in wearable form. Section III gives us the research
stand as of now in improving technical parameters of BLE
and also comparison of BLE with other wireless protocols.
II.
M
EDICAL
A
PPLICATIONS OF
BLE
AND
BLE
BEACONS
A. Background
In this section some of the common imbalances
associated with physical health conditions of common men
are discussed. Chronic conditions such as diabetes, cardiac
arrest, asthma, and problems related to old age are counted
among them. Life’s complicated schedules have made people
to ignore early symptoms associated with such slow
developing health ailments. So, to manage them easily many
accomplishments using BLE has evolved which is being
discussed here.
B. Diabetes self-management
Self-management of diabetic patients by checking blood
glucose (BG) levels and taking appropriate actions to keep
diabetes in control can improve quality of their lives. A
wearable system for measuring BG levels, heart rate, weight
and BP has been developed in [15] for real time observation
by integrating BLE with smartphones, which is first of its
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2019 Ninth International Symposium on Embedded Computing and System Design (ISED)
kind. BLE module’s light weight enabled it to be integrated
into wearable form. It also helps predict future risk of
getting diabetes. They have used multilayer perceptron
neural network as machine learning algorithm for future
predictions. [15]
Another study proposes photoplethysmogram (PPG)
technology for non-invasive measurement of BG, which is
easier than traditional way of pricking finger to get BG data.
Such a system could be of greater advantage when combined
with the work mentioned in[4].
C. Health monitoring in cardiac patients
Managing the existing vast healthcare system can be
simplified with e-health development which is already in
progress[16]
.
For initial diagnosis of cardiology a monitoring
system is mentioned in [5]. It uses multiple sensors to
measure various parameters such as heart rate, Blood
Pressure (BP) and body temperature, which is transmitted
through BLE to app. These three attributes are compared and
any deviation from normal functioning of heart is reported to
concerned doctor. The threshold can be set according to the
person who uses it. Even an alarm system is used which
cautions doctors in super speciality hospital at time of
emergency for immediate medical support by enabling GPS
for location tracking.[5]
Compared to the system in [5], analysis of ECG helps
early detection of heart diseases which when done remotely
can be of great advantage to reduce increasing death rates in
rural community[17]. A 5-lead ECG monitoring has been
developed by A. Vishwanatham, et.al, which transmits the
ECG via BLE to smartphone and is viewed in web page to be
monitored by doctor and patients in the preferred hospital .
As a next level contribution to this change, paper [16] gives
us a 3 lead wireless ECG monitoring system which is
capable of detecting uncommonness in heart in varied
sections of PQRST ECG waveform. 20 patients’ heart
conditions were successfully tested by comparing with
existing devices according to
P. L. Penmatsa and D. V. R. K.
Reddy [16].
In another similar work stated in [11], three textile
electrodes focusing on wearing comfort were introduced.
They have used FTPE (flexible polypyrrole textile
electrodes) as non-invasive electrodes. It is reusable, non-
irritable to skin, consumes very less power i.e., it can record
up to 30h continuously and conductivity is high compared to
other similar ECG wearable devices. Measurement of
electrical as well as mechanical capability of heart using
ECG and ICG sensors integrated in the wearable device is
mentioned in the literature [11]. Impedance cardiogram
(ICG) is important to be measured for cardiovascular
diseases along with ECG for better analysis. They have
made electrodes from gel type Ag/AgCl patch for knowing
ECG, ICG, heart rate, temperature and location of patient
[3]. Compared to battery life presented in [11] this system
runs for 24 hours on continuous monitoring which is less.
D. BLE in Daily physical activity
Obesity has become a major problem due to lifestyle
changes. People try to reduce their weight by following
many rigorous exercises without proper guidance from
experts. Thus, death due to cardiac arrests during extreme
physical exercise is observed to increase [18]. A wearable
ECG monitoring system can reduce this occurrence. An H-
health shirt fabricated with ECG electrodes used for accurate
ECG monitoring was fabricated in [19]. It can be used to
observe the heart rate of user running up to speed of
15km/hr. A high accuracy ECG algorithm capable of
detecting six types of unusual ECG signals is used. It is light
in weight and comfortable to wear during exercises. [19]
Thus wearing this shirt, physical conditions of normal as
well as abnormal people can be diagnosed while doing
physical exercise to detect exhaustion or sudden trauma
while doing exercises.
E. Intelligent Stethoscope
A wireless stethoscope referred in [20] speaks about
transferring heart sounds and ECG measurement through
BLE to be visualized in a mobile using APP. It uses single
lead for ECG measurement. As primary health check-up, it
can be utilized at homes. Another advantage is for doctors.
Doctors can distinguish heart sounds using traditional
stethoscope only through experience. So, for young doctors
this intelligent stethoscope can be a game changer to their
profession as it can help them detect irregularities more
accurately and enhance their auscultation skills.[20]
F. Emotional level diagnosis
A device having sensors such as EMG, PPG and 9 degree
of freedom (DOF) is integrated and made into wearable form
with BLE. Data generated is sent to smart phone to detect
emotional level of drivers. A trained support vector machine
(SVM) algorithm is used to determine current emotional
level of driver. It can be known if he is stressed, relaxed or
drowsy from the extracted data of sensors. The developers of
the module claim 99% accurate prediction. This device can
be worn at back of head with a cap comfortably[21]. Stress
related issues leading to depression have become common in
all age groups. Suicidal tendencies among students have
been increasing which can be detected earlier with this cap
type wearable emotional detector device[22].
BLE emitters are quite popular in various
applications due to its brevity, affordability, mountability,
stability, deployability, etc. Another attraction is beacon’s
low installation time and long battery life for ambient
intelligence at home and offices compared to other battery-
based technologies. Adaptive easiness and non-intrusiveness
make it more comfortable to ambient assisted living[13]. So,
BLE based devices to analyse diabetes, cardiac diseases and
other parameters can be integrated with BLE beacons.
G. For old age home management
A system for daily report collection is utilized in[23]
using BLE Beacons. Beacons are attached to the users which
are detected by scanners attached at various locations of their
building. The scanners help detect the area in which a
particular resident is staying without intruding the privacy of
the person. All the data collected by scanner is sent to main
server where report of activity by each individual is
automatically generated reducing the work of caretaker.
Beacon attached with accelerometer can support fall
detection can be done as future work in this case[23].
Reference [8] which is similar to above system has expanded
its ability for fall detection. Another application of BLE
beacons is indoor localization which can be used to track
Alzheimer’s or mentally imbalanced patients’ locomotion
[24]. Alerts can be issued if they go to some risky areas
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2019 Ninth International Symposium on Embedded Computing and System Design (ISED)
within surveillance saving them from injuries and even
death.
The combination of above systems makes overall
remote health management a reality.
III. T
ECHNICAL ENHANCEMENT RELATED TO
BLE
AND ITS
C
OMPARISONS
A. Technical Testing and Improvements in BLE
parameters
Energy harvesting technique in wireless implantable
device: BLE as from its name itself consumes low energy
compared to many other wireless protocols. Subcutaneous
solar energy collector along with BLE in implantable
electronics makes the referenced system energy efficient.
The given BLE in implantable electronics wakes for 5 sec in
which it works in low power and sleeps for 595 sec, thus
charging of 1 or 2 hours using subcutaneous solar energy
harvester keeps it on for a whole day. Currently this module
has a temperature sensor only. Extension of this work for
other body parameter measurement with more efficient solar
harvester can help solve energy issues in implantable as well
as non-invasive wearable devices[25].
Wireless Charging Using BLE: The work described here
in [18] uses Qi standard for wireless charging with the
principle of electromagnetic induction via BLE. This can be
explored to be implemented in various systems especially in
healthcare applications where battery replacements or
manual charging can be of great inconvenience for patients.
Emergency Situation Handling: Most of the wearable
devices designed have its gateway through smartphones to
web. If the smartphone is dead, there no communication
between our device and internet since BLE does not support
direct internet connectivity. This can be devastating at the
time of emergency. An adaptive network using 6LoWPAN
has been constructed to overcome this limitation in[26]. It
acts as a conversion gateway between BLE and Internet [27].
A system developed by W. Yoon, K. Kwon, M. Ha, and D.
Kim uses IPv6 technology applied through BLE and an
emergency protocol in advertising mode is enabled. It also
uses Raspberry Pi and a dongle for rest of the
communication[26].
Interference from other wireless modules: The robustness
of BLE from external signal interference is being tested in
this work. They did by introducing other BLE modules as
well as introducing Wi-Fi/ ZigBee signals creating a dense
environment [28].
RSSI Determination: Use of BLE in indoor positioning
applications is demanding especially in industrial as well as
healthcare fields. Determination of Received Signal Strength
Indicator (RSSI) is important to predict proper functioning of
BLE beacons which is stated to be complex. So, the
performance of RSSI of BLE in different environments
(Ideal and real) were tested by ray tracing methodology in
[12] and proved that these values are not precise since they
are heavily depended on the properties of the used BLE
beacon. Another work in [13] has presented an improved
version of RSSI (Received signal strength Indication) to get
desired location more precisely. They have obtained how
sampling rate and distance are correlated to determine RSSI
and also between variance and distance. The algorithm
developed for same is highly generalizable and accuracy for
proximity-based localization has improved to 9.14% of
existing similar systems.
In a similar work, an empirical solution was developed
with more than 3 million data samples which came to
conclusion that relation definitely exists between RSSI and
distance but per meter variation is very low. They also found
how surface material can have influence in signal strength
[14]. This fact can be inculcated for further research.
B. Comparison between other wireless connectivity
In this section, currently used and developed technologies
are compared to BLE to show pros and cons between them
and also how BLE system is superior to our current proposed
system.
A comparative study of BLE and Wi-Fi done shows BLE
consumes much less power compared to Wi-Fi. Signal
strength compared with BLE is much better in case of Wi-Fi
but by increasing number of Beacons in case of BLE it can
be improved. Installation cost per beacon is much lesser to
Wi-Fi [29].
Another study showed a hybrid model of BLE and Li-Fi,
where many features of Li-Fi offers potential solutions for
healthcare systems compared to BLE. But any obstacle
present in pathway will totally make our Li-Fi solution
meaningless. For time being a system only with Li-Fi is a
distant dream[30].
ANT which was mainly developed for health and sports
application is yet another promising solution to BLE [31]. It
is compatible with any topologies unlike BLE which can
only be used in star topology. But ANT+ has many
compatibility issues reported with smartphones when used in
applications. Above all that BLE holds good market value to
ANT+ hence services and familiarity for usage is more in
BLE [31].
An experimental comparison between UWB and BLE
has been conducted. As an indoor localization module BLE
shows superior properties to UWB with respect to tracking
mechanism, calibration process, antenna design, and
localization algorithm. However, accuracy is more in case of
UWB compared to BLE. Cost terms show BLE installation
cheaper to UWB. In terms of interferences both are affected
by obstacles. Operation range for UWB- 3.5 to 6.5Ghz and
BLE is 2.4GHz. [32]
Below Table.1 shows general parameter comparison of
wireless protocols BLE, Wi- Fi, Li-Fi and UWB taken from
[29]- [32].
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2019 Ninth International Symposium on Embedded Computing and System Design (ISED)
TABLE I. COMPARISON TABLE OF WIRELESS PROTOCOLS
CONCLUSION
The above study based on BLE and BLE Beacons and
ways to improve the technical hurdles can be used by
researches in various ways to create an efficient healthcare
system. The wearable device can be chosen according to the
requirement of subjected people at home. The wireless
charging methodology proposed by Qi using BLE, can
relieve one from checking the charge statuses of the device
in use. Thus, a system can be designed in which overall
management of health is possible from home for ages of all
people. From the above discussion and comparison with
existing wireless technologies we can see that BLE is the
most suitable protocol for smart health management, at
present.
A
CKNOWLEDGMENT
We are immensely grateful to our beloved Chancellor Shri.
Dr. Mata Amritanandamayi Devi for her inspiration and
Motivation.
R
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BLE Wi-Fi Li-Fi
UWB
Frequency/Wav
elength of
operation
2.4GHz –
2.48GHz
2.4GHz and
5GHz
380nm –
780nm
3.5GHz-
6.5GHz
Installation cost Very low High
compared to
BLE
Low High
Power
Consumption
Very less High Low High
Accuracy
Low
High
Depends on
light
intensity
and area of
exposure
High
Energy
Efficiency
1 year Continuously
charged
Comparativ
ely low
Few hours /
days
Smart Phone
Compatibility
Yes
Yes
Yes
Not with all
smartphone
s
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... With the advent of Bluetooth Low Energy [20] technology, the constraints of low-bandwidth connection in certain situations have been overcome. Smart biosensor advancement, psychological level diagnosis, falls, and geolocation of old individuals can be tracked using the BLE technology [21]. The outcome of the RFID and BLE technologies has enriched the services and scope of AAL. ...
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Full-text available
The adequate aging hypothesis seeks to help people live longer, healthy lives. Diabetic patients who stay remotely need an infrastructure to monitor them continuously and provide timely treatment. Ambient assisted living (AAL) encourages the establishment of solutions that may help optimize older people’s assistive environment while also reducing their impairments. The blood glucose levels of diabetic patients are continuously monitored by gold oxide sensors placed over the human body. The signals associated with the glucose levels in the human body are plotted over a spectrogram image using the short-time Fourier transform, which is further classified using the deep learning model based on finetuned AlexNet, which has employed random oversampling and batch normalization for better precision in the results. The model classifies the spectrogram images as low and high glucose levels and normal glucose levels. Thereby alarming the caretakers for effective treatment of the individuals. Body area networks (BANs) gather information from biosensors and send it to a domain controller to assist caretakers and physicians in recommending the physical exercises for their clients. Evaluation criteria such as sensitivity and specificity, precision, and Mathew’s correlation coefficient are used to assess the effectiveness of the proposed model in this current diabetes study. The cross-validation of the model at multiple folds is being evaluated to analyze the performance. It is evident from the obtained results that the proposed model has exhibited an acceptable performance in precisely sensing the individuals with abnormal glucose levels.
Chapter
The concept of sense arises in the smart environment, in which various kinds of sensors/devices integrated into daily objects. Then, infrastructure at the smart systems, such as at smart homes, is connected by network technologies to gather contextual information of vital signs and behavior of users via the sensors. The very common approaches for user monitoring are based on machine vision. However, other sensors (e.g., wearables, motion, radar, object pressure, and floor vibration sensors) are also used for the user’s health and behavior monitoring. The sensors can be connected to local devices to process raw signals and take decisions based on distinguished machine learning approaches. This chapter will focus on sensors and features for assisted living technologies.KeywordsSensorsDataFeatures
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Assisted living works are mostly focused on wearable sensors or have sometimes combined them with ambient sensors to facilitate independent living of the users. The data collection process using wearable sensors is usually easier than that using ambient sensors. However, wearable sensors have drawbacks that could strongly discourage the elderly people from adopting them. One major disadvantage of using wearable sensors is that the users can perceive them to be very cumbersome. Furthermore, there is a high possibility that some wearable sensors can generate an uncomfortable feeling during long-term skin attachment. Hence, wearable sensor-based technologies that are used to help elderly people live independently may face a high risk of rejection, especially at home. In contrast, external or ambient sensors should be highly accepted by the users, especially elderly or disabled. However, it is important to verify that the sensors collect accurate data from a distance. Moreover, wearable sensors may require professional adjustments on the body to collect accurate data, which indicates that a complex process may be necessary for installing the sensors. Thus, this chapter will discuss different datasets and experimental results. For instance, public datasets consisting of information from different data sources would be used to model different events (e.g., behavior) using different machine learning algorithms in assisted living.KeywordsDatasetWearable sensorsAmbient sensors
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The perpetual evolution of IoT continues to make cities smart beyond measure with the abundance of data transactions through expansive networks. Healthcare has been a foremost pillar of settlements and has gained particular focus in recent times owing to the pandemic and the deficiencies it has brought to light. There is an exigency to developing smart healthcare systems that make smart cities more intelligent and sustainable. Therefore, this paper aims to present a study of smart healthcare in the context of a smart city, along with recent and relevant research areas and applications. Several applications have been discussed for early disease diagnosis and emergency services with advanced health technologies. It also focuses on security and privacy issues and the challenges posed by technologies such as wearable devices and big healthcare data. This paper briefly reviews some enhanced schemes and recently proposed security mechanisms as countermeasures to various cyber-attacks. Recent references are primarily used to present smart healthcare privacy and security issues. The issues are laid out briefly based on the different architecture layers, various security attacks, and their corresponding proposed solutions along with other facets of smart health such as Wireless Body Area Network (WBAN) and healthcare data.
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Research on electronic healthcare (eHealth) systems has increased dramatically in recent years. eHealth represents a significant example of the application of the Internet of Things (IoT), characterized by its cost effectiveness, increased reliability, and minimal human effort in nursing assistance. The remote monitoring of patients through a wearable sensing network has outstanding potential in current healthcare systems. Such a network can continuously monitor the vital health conditions (such as heart rate variability, blood pressure, glucose level, and oxygen saturation) of patients with chronic diseases. Low-power radio-frequency (RF) technologies, especially Bluetooth low energy (BLE), play significant roles in modern healthcare. However, most of the RF spectrum is licensed and regulated, and the effect of RF on human health is of major concern. Moreover, the signal-to-noise-plus-interference ratio in high distance can be decreased to a considerable extent, possibly leading to the increase in bit-error rate. Optical camera communication (OCC), which uses a camera to receive data from a light-emitting diode (LED), can be utilized in eHealth to mitigate the limitations of RF. However, OCC also has several limitations, such as high signal-blockage probability. Therefore, in this study, a hybrid OCC/BLE system is proposed to ensure efficient, remote, and real-time transmission of a patient’s electrocardiogram (ECG) signal to a monitor. First, a patch circuit integrating an LED array and BLE transmitter chip is proposed. The patch collects the ECG data according to the health condition of the patient to minimize power consumption. Second, a network selection algorithm is developed for a new network access request generated in the patch circuit. Third, fuzzy logic is employed to select an appropriate camera for data reception. Fourth, a handover mechanism is suggested to ensure efficient network allocation considering the patient’s mobility. Finally, simulations are conducted to demonstrate the performance and reliability of the proposed system.
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Current technology provides an efficient way of monitoring the personal health of individuals. Bluetooth Low Energy (BLE)-based sensors can be considered as a solution for monitoring personal vital signs data. In this study, we propose a personalized healthcare monitoring system by utilizing a BLE-based sensor device, real-time data processing, and machine learning-based algorithms to help diabetic patients to better self-manage their chronic condition. BLEs were used to gather users’ vital signs data such as blood pressure, heart rate, weight, and blood glucose (BG) from sensor nodes to smartphones, while real-time data processing was utilized to manage the large amount of continuously generated sensor data. The proposed real-time data processing utilized Apache Kafka as a streaming platform and MongoDB to store the sensor data from the patient. The results show that commercial versions of the BLE-based sensors and the proposed real-time data processing are sufficiently efficient to monitor the vital signs data of diabetic patients. Furthermore, machine learning–based classification methods were tested on a diabetes dataset and showed that a Multilayer Perceptron can provide early prediction of diabetes given the user’s sensor data as input. The results also reveal that Long Short-Term Memory can accurately predict the future BG level based on the current sensor data. In addition, the proposed diabetes classification and BG prediction could be combined with personalized diet and physical activity suggestions in order to improve the health quality of patients and to avoid critical conditions in the future.
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In this paper, a wireless implantable sensor prototype with subcutaneous solar energy harvesting is proposed. To evaluate the performance of a flexible solar panel under skin, ex-vivo experiments are conducted under natural sunlight and artificial light sources. The results show that the solar panel covered by a 3 mm thick porcine flap can output tens of microWatts to a few milliWatts depending on the light conditions. The subcutaneous solar energy harvester is tested on different body parts, which suggests the optimal position for the harvester to implant is between neck and shoulder. A wireless implantable system powered by the subcutaneous energy harvester is presented, which consists of a power management circuit, a temperature sensor and a Bluetooth low energy (BLE) module. An application is developed for data visualization on mobile devices, which can be a gateway for future IoT-based healthcare applications. The entire device is embedded in a transparent silicone housing (38 mm × 32 mm × 4 mm), including a 7 mAh rechargeable battery for energy storage. The average power consumption of the implants is about 30 μW in a 10 minutes operation cycle. With the subcutaneous solar energy harvester, the self-powered operation of the implantable sensor prototype is demonstrated by long-term experimental results. Two worst-case scenarios (no exposure to light and battery depletion) are considered with ex-vivo experiment simulations.
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Ubiquitous penetration of Internet-of-Things (IoT) devices is promising to be an enabler in taking healthcare services to needy patients even in remote regions. In this paper, we present our wearable IoT remote health monitoring system that includes a photoplethysmograph (PPG) based device to measure physiological parameters such as pulse rate, blood oxygen, and respiratory rate (RR). We have conducted a pilot study of our system on 25 patients, and we report the comparative performance of different techniques for deriving RR from PPG signals. The best performing algorithms achieved a mean absolute error of 0.58 breaths/min, which exhibits the potential of PPG based sensors for automated detection of many cardiovascular and pulmonary diseases, particularly, pneumonia, sleep apnea, and acute respiratory distress syndrome.
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Global health which denotes equitable access to healthcare, particularly in remote-rural-developing regions, is characterized by unique challenges of affordability, accessibility, and availability for which one of the most promising technological interventions that is emerging is the Internet of Things (IoT) based remote health monitoring. We present an IoT based smart edge system for remote health monitoring, in which wearable vital sensors transmit data into two novel software engines, namely Rapid Active Summarization for effective PROgnosis (RASPRO) and Criticality Measure Index (CMI) alerts, both of which we have implemented in the IoT smart edge. RASPRO transforms voluminous sensor data into clinically meaningful summaries called Personalized Health Motifs (PHMs). The CMI alerts engine computes an aggregate criticality score. Our IoT smart edge employs a risk-stratified protocol consisting of rapid guaranteed push of alerts & PHMs directly to the physicians, and best effort pull of detailed data-on-demand (DD-on-D) through the cloud. We have carried out both clinical validation and performance evaluation of our smart edge system. The clinical validation on 183 patients demonstrated that the IoT smart edge is highly effective in remote monitoring, advance warning and detection of cardiac conditions, as quantified by three measures, precision (0.87), recall (0.83), and F1-score (0.85). Furthermore, performance evaluation showed significant reductions in the bandwidth (98%) and energy (90%), thereby making it suitable for emerging narrow-band IoT networks. In the deployment of our system in the cardiology institute of our University hospital, we observed that our IoT smart edge helped to increase the availability of physicians by 59%. Hence, our IoT smart edge system is a significant step towards addressing the requirements for global health.
Conference Paper
In wireless body area network (BAN) applications such as wearable computing, healthcare and sports, Bluetooth Low Energy (BLE) is a new and promising technology, which uses the unlicensed 2.4-GHz spectrum band for data transmission. Since there exist many wireless technologies operating in this frequency band, the issues of cross-technology interference and coexistence present a major challenge. In this work, we develop a testbed to conduct our experimental studies, focusing on BLE and its coexistence capabilities when being deployed in a dense environment, under possible interference from WiFi and ZigBee/IEEE 802.15.4. One scenario of interest is a network of several co-located BLE-based BANs, each of which is designed in a star topology with one gateway and multiple BLE sensor nodes. The second scenario represents a highly heterogeneous network where each BAN now carries both BLE and ZigBee sensors, while being exposed to interference from external WiFi transmission. Our results show that the performance of BLE is relatively robust to interference from other BLE transmissions as well as those from nearby ZigBee and WiFi devices.