KeepSafe®

Wristband Device for Heart-rate Monitoring

Vitor Pinto

, Raquel Sousa

and Gil Gonçalves

Increase Time, Matosinhos, Portugal

Faculdade de Engenharia da Universidade do Porto, Porto, Portugal

Keywords: Bio-signals Monitoring, Mobile Devices, Photopletysmography, Heart Rate Estimation, Wristlet Monitor,

Mobile Application, Signal Processing.

Abstract: The goal of this project is to meet efficient and technological management solutions that allow to increase

life quality of elderly people and at same time reduce costs in the health sector. The KeepSafe® wristband

device will increase the safety of users since it will be able to continuously monitor vital signs and it will

generate dynamic alerts based on thresholds or manual alerts by pressing a SOS button. The device uses a

reflective PPG (Photoplethysmogram) technique using two green LEDs and a photodiode sensor on the

wrist to continuously estimate heart rate. Then this data is correlated with the activity data estimated by an

accelerometer and gyroscope. All data is sent to a smartphone via Bluetooth® Smart. The future goal is to

make the device autonomous by adding GSM communication capabilities.

1 INTRODUCTION

Nowadays, the ageing of population is one of the

biggest problems of our society. It´s predictable that

the number of elderly people will duplicate by the

middle of century. This demographic change will

cause an increase of health problems, in particular

heart diseases. In Portugal the rate of deaths caused

by heart diseases is above 30% (Instituto Nacional

de Estatística, 2012) and often a life could be saved

with a tele-monitoring system.

Continuously monitoring of vital signs and daily

activity information can help to promote better

healthcare and better quality of life. Clinical data is

obtained by specific equipment, mostly available in

hospitals, with several sensors, being necessary to

put into practice the concept of proximity to be able

to access in real-time health related information

wherever the patient is.

IncreaseTime is a technology-based company

whose activity is centred in ICT and wireless sensors

solutions to promote people’s life quality, especially

focused on patients with chronic diseases and elderly

people.

The KeepSafe® project intends to create a low-

cost and non-invasive device for daily use to

continuously monitor the heart rate and alert a

caregiver in case of an emergency episode. The

device is based on a wristband which is comfortable

for daily use and the wrist is the suitable place to

measure heart rate through the

photoplethysmography method.

Figure 1: KeepSafe wristband monitor.

Our monitoring system has three main

components: the KeepSafe® device, a mobile

application and a web application. The device uses

the sensor to measure the heart rate and sends it to

mobile application through Bluetooth® technology

that processes data locally and warns the caregivers

if the data exceeds the thresholds. Furthermore, the

device has an alert button on the wristband for

emergency situations which immediately establishes

Pinto V., Sousa R. and Gonçalves G..

KeepSafe

 - Wristband Device for Heart-rate Monitoring.

DOI: 10.5220/0005184500830087

In Proceedings of the International Conference on Biomedical Electronics and Devices (BIODEVICES-2015), pages 83-87

ISBN: 978-989-758-071-0

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

the communication between the patient and the

caregiver. This function could have a vital role in

people lives. After process data, the mobile device is

responsible for sending it to a remote server where

caregivers can follow up the health status of users

through a web application. This system takes

advantage from the communication interfaces and

processing power of handheld devices like a

smartphone to create a low cost and user-friendly

monitoring system.

The use of devices for personal health

monitoring systems is an emergent area of research.

Related to this work we can enumerate projects that

have some common goals and projects with a

broader scope. The eCAALYX project (Boulos et

al., 2011) inserted in the AAL programme offers

solutions for prevention and management of chronic

conditions in elderly people. This project is based on

a t-shirt with integrated biosensors and

communication of bio signals into a smartphone

application with a simple and intuitive interface. The

accessible parameters in the application are

respiratory rate, temperature and activity type

(walking, standing or lying).

Other work based on a t-shirt is the VitalJacket

(BioDevices S.A., 2008). This device uses wearable

technology for continuously monitoring heart rate

and ECG waves. The data is saved in the device

attached to the t-shirt and then analysed by a

physician. Another work with identical goals is the

WIHMD (Kang et al., 2006). The wrist-worn

integrated health monitoring device is a multi-

parameter wristlet that includes 5 bio-signals and a

fall detector. The bio-signals measured by WIHMD

are ECG (single lead), blood pressure, SPO2,

respiration rate, and body temperature. This device

communicates with a mobile phone giving to the

system tele-reporting functions to advise a caregiver

in emergency situations. The Oxitone device

(Oxitone Medical Ltd., 2013) is a wristband based

device developed by an Israeli Company to monitor

Heart Rate and oxygen saturation (SPO2). The

Oxitone device uses a PPG sensor to perform these

measures and has the ability of sending this data via

Bluetooth® to a given application. The application

performs data analysis and alerts the treating

physician.

Related to mobile applications there are a lot of

them in the market but the vast majority are focused

on fitness activities and doesn’t have the feature of

monitoring multiple bio-signals. Recently, some of

these applications are changing their focus for health

records like TactioHealth (Tactio Health Group,

2014). This application has connectivity to several

electronic health devices and is used to control a set

of parameters like weight, blood pressure, lifestyle,

heart rate, cholesterol and glucose.

The KeepSafe® system has similarities with the

presented works but we intend to differentiate it by

creating an innovative and complete system that

works autonomously (no other device or application)

and automatically alerts formal or informal

caregivers.

This article contains 3 more sections. In section 2

the method is explained describing the KeepSafe®

device, signal acquisition and required processing to

compute heart rate. Section 3 presents experimental

results and discussion. Finally, section 4 refers

conclusions and future work.

2 METHOD

In this section we will describe in detail the

KeepSafe® device and signal acquisition.

2.1 KeepSafe

Device

The device is composed mainly by 5 blocks:

accelerometer/gyroscope, a PPG sensor combined

with an analog front-end (AFE4490, Texas

Instruments, USA) for pulse oximeter applications, a

processor unit, an emergency button and a

Bluetooth® unit.

The selected accelerometer (MPU9150,

InvenSense, USA) has an integrated gyroscope too,

this component allows to perform activity

recognition tasks through patterns analysis. This was

important to correlate heart rate measurement with

activity level and it provides extra information about

user daily life. The accelerometer could also be

helpful to estimate the error in PPG signal. This

information makes possible to use adaptive filtering

techniques to improve signal-to-noise ratio.

The PPG sensor and front-end is one of the

central features once heart rate is the critical factor

to monitor. The analog front-end allows controlling

LEDs (Light-Emitting Diodes) to pulsate light,

periodically, through the wrist. Then the sensor will

capture the reflected light which is quantified by the

front-end. All the data is sent to the mobile

application using the Bluetooth® smart unit. Figure

2 illustrates the PPG sensor with the LEDs placed at

each side. The SOS button is an extra safety for the

user: in case of an emergency episode, users can

press the button and the alert will be sent by

Bluetooth®. All alerts (manual or dynamic) are

forwarded to the caregiver through the mobile

BIODEVICES2015-InternationalConferenceonBiomedicalElectronicsandDevices

application. The work is still in progress and the

next step is to add new features like GSM

communication and GPS antenna. These new

features will eliminate the smartphone requirement.

The mobile application (Sousa et al., 2012) is

responsible to collect, process and send data to the

remote server and it allows users to configure

parameters like personal data, thresholds for heart

rate and has an interface to visualize data in real-

time. The mobile application connects to a remote

server developed using the PlugThings® Framework

(FreedomGrow, 2011) which is very useful to

remote monitor users and follow up their health

status based on history monitoring data.

Figure 2: Heart rate sensor in KeepSafe device.

2.2 Bio-signal Acquisition

PPG is one of pulse wave detection methods which

consists in emitting light through vessels or arteries

and measure the amount of light that crosses the

tissue (transmissive PPG) or the amount of light that

reflects back (reflective PPG) (Tamura et al., 2014).

This technique uses as principle the variation in light

absorption when the blood is flowing to calculate the

pulse rate. In this particular case, we use the

reflective technique because it is more suitable for

measurements on the wrist. We use two LEDS for

emitting light (operating in the green wavelength –

520nm) and a correspondent wavelength photodiode

sensor. That wavelength is proved to be suitable for

PPG acquisition at wrist. Studies about different

wavelengths in reflective PPG have been done (Lee

et al., 2013). For the signal acquisition we use a

sample rate of 100 Hz once is good enough to get

pulse rate frequency and at the same time doesn’t

overload the processor leaving more processing

power for signal filtering, heart rate compute

algorithm and other tasks.

2.3 Bio-signal Processing

Since PPG signal is a low amplitude and noisy

signal it’s necessary to add extra signal processing in

order to improve signal quality and heart rate

estimation.

The first processing stage begins in the front-end

when the signal passes through a transconductance

amplifier. After that the signal is submitted to a

second stage amplifier and ambient light

cancellation and the final step is to submit the signal

to ADC converter to get a digital form signal. All

that processing is performed in the front-end.

The digital signal is then read from the master

processor and digital filters are applied to get the

desired frequency range and improve signal quality

eliminating some of the noise caused by movements.

The selected processor (ATXMEGA128A4U,

Atmel, USA) is a 16 bit processor which is

characterized by being low-cost and low power

consumption at sleep mode. Besides, that processor

provides enough computing power to deal with all

the tasks and signal processing.

The selected digital filter was a pass-band IIR

butterworth filter. The selected type was IIR since

the FIR type requires a high order filter to get the

desired behaviour which would demand more

processing power. An eight order IIR filter was used

and the selected range frequency was 0.6-4.5 Hz.

That frequency is enough to get pulse rate range

between 36 and 270 bpm without attenuation.

3 RESULTS

In this section it will be presented experimental

results regarding to PPG wave and heart rate

calculation.

The signal showed in figure 3 is an example of

the signal after applying the filters described in

previous section.

Figure 3: PPG signal obtained with KeepSafe device.

Heart rate estimation is calculated by extracting

KeepSafe®-WristbandDeviceforHeart-rateMonitoring

information from the filtered wave. We can clearly

identify the wave peaks in the image. The developed

algorithm is based on the peaks detection to

calculate the distance between each peak. In order to

detect peaks were used two adaptive threshold based

on the last two seconds of data. One high threshold

and a low threshold to avoid fake peaks. Each time

the wave crosses high threshold we are facing a

possible peak. At this time the value in x-axis (the

time axis) corresponding to local maximum is

stored. As soon as the wave crosses the low

threshold that peak is confirmed and the algorithm

starts looking for the next peak. Furthermore another

verification condition was to set a minimum distance

of 200 milliseconds between peaks.

The computed heart rate is sent to mobile

application where information is shown as illustrated

in the picture below. All user information can also

be consulted through the Web Application.

Figure 4: Main screen of mobile application.

Heart rate measurements obtained with the

KeepSafe

device were evaluated in comparison

with a conventional pulse oximeter (CMS50E,

Contec, China) which has an accuracy of ±2 bpm

according to manufacturer. The results were very

close, showing a deviation of ±2 bpm between both

devices which implies that KeepSafe

has a

maximum error of ±4 bpm. Tests were performed in

stationary conditions. It was observed that a

significant movement affects the PPG signal making

harder to get precision measurements. That will be

an aspect to improve in future with adaptive filters

bearing in mind the person movement.

4 CONCLUSIONS

During the project development we conclude that it

is possible to develop a user friendly and low-cost

mobile monitoring system. Reflective PPG at wrist

provides a good method to develop a comfort heart

rate monitor. However, it implies to have efficient

algorithms and a considerable processing power.

There is other similar wrist monitors but with

focus on sports activity. KeepSafe

intends to be

mostly used by elderly people and works as an

emergence device to increase user’s safety.

The future work involves the development of an

activity recognition algorithm to correlate this data

with heart rate monitor. This information will be

useful to apply adaptive filtering techniques that

leads to higher signal-to-noise ratio during motion.

The battery autonomy is another aspect to improve.

The use of management power techniques like sleep

mode of peripherals whenever they aren’t operating

will allow extend autonomy to encourage continued

use of KeepSafe® monitoring device.

Regarding hardware, a GSM and GPS modules

will be integrated in order to transform the

KeepSafe® bracelet in an autonomous device.

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BIODEVICES2015-InternationalConferenceonBiomedicalElectronicsandDevices

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KeepSafe®-WristbandDeviceforHeart-rateMonitoring