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College of Technology



and Communication Engineering

College of Technology




Abstract—Personal Health Support System is specially designed to help the
elderly people, who are at home alone most of the time. The system is in the
form of a wearable device and continuously records the vital parameters of a
person. The vital parameter accessed includes SPO2, Heart rate and temperature.
The system sends an alert message if there is any critical change in the
parameters. The cost of the existing systems is at higher end and is not
affordable by the common people. The aim of this project is to develop a
cost-effective prototype of a wearable device that continuously monitors the
vital parameters such as temperature, heart rate and blood oxygen level. The
values are recorded and posted in the cloud. The system is calibrated according
to an individual as the parameters vary depending upon the age. The doctors can
directly access the details of the person through cloud for review immediately.

Keywords—Biomedical engineering, Heart rate,
Photoplethysmography(PPG), SPO2, Wearable sensors.

I.      Introduction

The rise of the average life expectancy of humans requires
continuous monitoring and on-going treatment for good long term health
conditions. The project “Personal Health Support System” aims at helping the
elderly people by serving as a wearable health monitoring and alert system.

Wearable sensor
technology is an emerging technology in recent times. Wearable sensors have been
widely used in many developmental areas. These sensors provide accurate results
on human’s health thereby providing very good environment to live in. It has
revolutionized the whole world with its reliability, smaller size and
durability. They are most widely used in medical sciences where there is a need
for continuous monitoring of patient’s health.

With the available systems that continuously monitor the health of a
person; the contribution of this project is to develop a prototype of a
wearable device that continuously records the vital parameters of a person such
as temperature, heart rate and blood oxygen level using a wearable sensor at a
low cost. It intimates an alert message if the parameter values are erratic.
The recorded values can be viewed at any point of time for future reference.
Thus, it serves the need of a doctor for continuous health monitoring for a
person’s wellness.

II.    System Architecture

The various processes involved in continuous health monitoring and
alert system is explained in the form of a block diagram as follows:

Fig. 1.   
System Block Diagram


The values are read from the corresponding registers of the sensor
with the help of I2C protocol which is the most widely used protocol for serial
communication. The values obtained are in the form of digital data is processed
and the necessary calculations are implemented with the help of CC3200
Launchpad which has an ARM Cortex processor. The parameter values thus obtained
are published in the cloud through the Network processor in the Launchpad. The
values can be seen from anywhere in the world by accessing the website. The
ranges of the parameters are fixed and the values are analyzed for the specific
conditions. In case of a critical change, the alert message is sent to the
mentioned phone numbers through the cloud.

A.    Software tools used

Energia is an open source and community-driven integrated
development environment (IDE) and software framework. Energia provides a
wonderful framework and simple coding facility to many of Texas Instruments
Launchpad with lots of inbuilt libraries. It also provides Wi-Fi libraries to
support cloud based applications.

IBM Bluemix a product of IBM provides storage facility in the Cloud.
It provides a lot of applications which allows the user not only to store data
but also to manipulate and give output in the preferred format. This IBM
Bluemix cloud is free of cost and provides a faster access with vast storage
capabilities. Since it supports many programming languages integration of the
processor and cloud via energia becomes a simpler task. Moreover task performance
is much more easier in Bluemix.

III.   Hardware Architecture

The Hardware architecture of the system consists of a Pulse Oximetry
and Heart Rate sensor (MAX30100), a bidirectional voltage level translator and
CC3200 ARM processor with an inbuilt Network processor. The MAX30100 sensor is
chosen for its unique features such as ambient light cancellation, analog
front-end and it can be used to measure heart rate, temperature and blood
oxygen level if configured accordingly. 
The sensor and the Launchpad operate at two different voltages and thus
a bi-directional level translator MAX3377E is used.  The Launchpad is programmed using the Energia
IDE and the values are published through Wi-Fi by using the Network processor
in the CC3200 Launchpad.  The hardware
architecture is as shown:

Fig. 2.    
Hardware Architecture

A.    MAX30100 –  Wearable sensor
for SPO2 and Heart Rate

The MAX30100, a wearable sensor much smaller in size is used to find
SPO2 and Heart Rate of a person. Photoplethysmography (PPG) is the principle
used over here.  It gives values based on
oxygen absorbed when RED and IR light rays are passed through body surface. It
is a very delicate sensor and so the current requirements should be taken with
special care.

B.    MAX3377E – Quad Low-Voltage Level Translator

The MAX3377E is a protected level translator which provides the
level shifting necessary to allow data transfer in a multi voltage system.
Externally applied voltages, VCC and VL, set the logic levels on either side of
the device. A low-voltage logic signal present on the VL side of the device
appears as a high-voltage logic signal on the VCC side of the device, and
vice-versa. The MAX3377E is a bidirectional level translator which utilizes a
transmission-gate-based design to allow data translation in either direction on
any single data line.

C.    CC3200 Launchpad

The CC3200 is a programmable Wi-Fi MCU that enables true, integrated
IOT development. the CC3200 device has the same Wi-Fi Network Processor(NWP)
sub-system as the CC3100 device. This NWP integrates all protocols for Wi-Fi
and Internet, greatly minimizing MCU software requirements. With built-in
security protocols, Simple Link Wi-Fi provides a robust and simple security
experience. The CC3200 host driver was designed to support embedded
applications using low-cost and low-power microcontrollers with reduced board

IV.   Software Architecture

The process involved in determining the parameter values is as

Software Architecture

A.    Heartrate Calculation

The heart rate mode is first enabled. The heart rate interrupt sets
after the sample is ready in the FIFO data register. Numerous manipulations
have to be implemented on the raw data before the necessary parameter values
are determined. The IR value is obtained from the FIFO data of the sensor. The
first two bytes of a sample in FIFO data represent the IR value. The IR value
has to be fixed within the particular threshold that is, the values would be
taken into account if the value falls within the range else the previous value
will be taken. The next step is the signal conditioning step. The data is then
differentiated to obtain the peaks. The number of peaks obtained for the IR
values in 10 seconds is noted. The number of peaks multiplied by 6 gives the
heart rate value in beats per minute.

B.    Temperature Calculation

The integer part of the temperature value is available in the
temperature register once when the temperature mode is enabled. The value can
be obtained by directly accessing the register.

C.    SPO2 Calculation

The SPO2 mode is enabled. The SPO2 interrupt sets after the sample
is ready in the FIFO data register. The first two bytes of a sample in the FIFO
data represents the IR value and the next two bytes represents the RED value.
Dividing the RED value by the IR value and converting it into percentage gives
the blood oxygen saturation level in percentage. Personal Health Support System
also sends an alert message from the IBM Bluemix cloud. The data from the
sensor is published in the cloud.

D.    Cloud Platform

IBM Bluemix is a cloud Platform as a Service (PaaS) developed by
IBM. It supports several programming languages and services as well as
integrated DevOps to build, run, deploy and manage applications on the cloud.
Bluemix is based on Cloud Foundry open technology and runs on Soft Layer
infrastructure. For the message facility, a temboo and a twilio account is
needed. With the help of twilio account the user can choose the contact numbers
to which the message has to be sent. Also, the user can get a number from which
the message has to be sent. For a single twilio account, there will be an API
(Application Programming Interface) which gives the unique id for the account.
Twilio account also helps us to make emergency calls if needed. The API key and
the numbers obtained from the twilio account is used in the temboo account to
complete the message module. With the following details the code for the
sending the message can be completed easily by connecting the CC3200 board with
the WIFI network which has internet access otherwise the message cannot be sent
via cloud.

V.    Results And Discussion

The code is uploaded to the CC3200 Launchpad and the forefinger is
kept on the sensor. The sensor returns the temperature, heart rate and blood
oxygen level as and when the configuration is enabled. The three parameters are
obtained at regular intervals and the values are updated to the cloud.

different ranges of the parameter values and their significance is explained
from the tables shown below:


Temperature Ranges and Conditions*



Range of Values


<35.00C (95.00F) Normal 36.5 – 37.50C (97.7 – 99.50F) Fever >37.5
or 38.30C (99.5 or 100.90F)


or 38.30C (99.5 or 100.90F)



SPO2 Ranges and


Range of Values


95 – 100%


90 – 94%


75 – 89%

Severe Hypoxemia

<75%   TABLE III Heart Rate Ranges and Conditions* Condition Range of Values Bradycardia <60 bpm Normal 60 – 100 bpm Tachycardia >100


*referred from paper “Mobile health and life science
detector” – Patent EP 1638453 A2

Validation for Heart

The heart rate of the same person
is measured by using an app S Health in Android phone. The value obtained
explains the accuracy of the system.

Value of heart rate in Personal Health
Support System: 60bpm

Value of heart rate in S
Health App(Samsung Mobile): 62bpm

Validation of SPO2 and

A Thermometer and Pulse Oximeter are used to measure the temperature
and blood oxygen level of the same person. The values obtained explain the
accuracy of the system.


Value of
temperature in Personal Health Support System: 35?C

Value of
temperature in thermometer: 95.8?F (or) 35.4?C


Value of SPO2 in
Personal Health Support System: 98%

Value of SPO2 in
Pulse Oximeter: 98%

To verify the proper working of the alert system, the
values of the parameters are intentionally changed to abnormal levels and the
alert messages to the specified numbers are obtained.

VI.   ConclusionThus, the prototype is implemented and the parameters such as blood
oxygen level, heart rate and temperature of a person are continuously
monitored. The alert message was forcefully created and checked. The data is
posted in the cloud and the parameters are successfully monitored. The
challenges faced during the development of the prototype include power supply
problems as the system needed low power which couldn’t be achieved easily in
the laboratory scale and the failure of the wearable sensor because of the
multiple power supply

The future work
includes the extension of the product to a wide range of applications without
restricting to a particular cause which includes stress level relation with
vital parameters and rate of pollution a person is exposed to etc., Power
supply stabilization should also be improved and the system should be designed
completely to be wearable.


Subhas Chandra Mukhopadhyay, “Wearable
Sensors for Human Activity Monitoring: A Review”, IEEE sensors journal, Vol.
15, No. 3, March 2015

Lara Gonz´alez-Villanueva
,StefanoCagnon and LucaAscari, “Design of a Wearable Sensing System for Human
Motion Monitoring in Physical Rehabilitation”, Sensors 2013

Shyamal Patel, Hyung Park,
Paolo Bonato, Leighton Chan and Mary Rodgers, “A review of wearable sensors and
systems with application in rehabilitation”, Patel et al. Journal of
NeuroEngineering and Rehabilitation 2012

Nuria Oliver and Fernando
Flores-Mangas, “A Real-time Wearable System for monitoring and analyzing
physiological signals – Health Gear”, European journal of scientific research

Ademola Philip Abidoye, Nureni
Ayofe Azeez, Ademola Olusola Adesina, Kehinde K. Agbele, Henry O. Nyongesa,
“Using Wearable Sensors for Remote Healthcare Monitoring System”, Journal of
Sensor Technology, 2011

David Seal, “ARM Architecture
Reference Manual,” Second Edition, Addison-Wesley Publication

Joseph Yiu, “Definitive Guide
to ARM Cortex – M3 and Cortex M4 Processors Pb”, Third Edition

I2C Guide Online.Available: www.

9     MAX30100Online.Available:


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