Heart Beat Monitoring Device with an Optical Sensor

Budiani Fitria Endrawati, Barokatun Hasanah, Vicky Mudeng, Kresna Prasetya Pamungkas, Ahmad

Maulana Rizki, Ramadhani and Ezekiel Miracle Bintang A.

Institut Teknologi Kalimantan

Keywords: Heart rate monitoring, Optical sensor, Fingertip, Wrist

Abstract: Heartbeat measurement system is an important issue to monitor the health condition of the human being. In

normal resting, heart rate will be beaten between 60 to 100 beats per minute (bpm) depending on the age

and physical condition. Through heart rate monitoring, several severe diseases can be discovered as

preventive action of mortality; for instance, heart failure. The work within this study presents a developed

heartbeat monitoring (HBM) using an optical proximity sensor to measure heart rate. It involves both the

measuring on the fingertip and wrist for comparison. The proposed HBM detects the blood flow through the

index finger, while the wrist measurement employs a pedometer in a smartwatch of Xiomi Mi Band 3. An

HBM consists of an optical sensor with a light source and detector, a microcontroller module of NodeMCU

ESP8266, and an organic light-emitting diode (OLED) display. The experimental tests measure the

heartbeat with two conditions, such as no activity and after activity states; and with three different ages. The

results indicate that proposed HBM is suitable for monitoring heart rate and obtained data that is possible to

provide via mobile and internet applications.

1 INTRODUCTION

The new efforts for developing mobile medical

devices with low production costs emerge to be a

new focus in the biomedical field. Health monitoring

is an important issue due to it can be discovered the

diseases, physical condition, blood pressure, and

heart health. The heart pulse can be monitored due

to there is a change in the blood density affected by

the heart pumping the blood to the whole body

(Arulananth, 2017).

The most common sensor to detect the heart rate

is pulse oximeter for measuring oxygen saturation in

the blood. It illuminates the skin and measures the

variation of the absorbed light (Jubran, 2015). It

applies a near infra-red (NIR) light with a

wavelength between 600 to 1000 nm; therefore the

light can be penetrated the tissue (Mudeng, 2018).

The designing of heart rate monitoring by

implementing the different microcontrollers have

been proposed for clinical trials. The combination of

the proximity sensor, including a light source and

detector with a signal extraction, pulse

amplification, as well as display circuit, generated

less time consuming and efficient cost in clinical

pulse detection (Hashem, 2010). A measurement

algorithm was applied in a microcontroller

interfacing with analog to digital converter (ADC)

and oximeter. Furthermore, this system utilized a

field-programmable gate array (FPGA) to produce a

control signal. With this system, the heart rate was

detected in the normal state of human activity and

had a low power dissipation (Keat, 2016).

A comparison of personal health monitoring

devices has been conducted. A sensor with a chest

strap, fitness tracker, smartwatch, and the

photoplethysmography (PPG) on the smartphone

feature was investigated to determine the highest

accuracy for each device. The chest strap showed

better accuracy due to the results were similar to the

recognized medical devices. On the other hand,

fitness trackers and the smartwatch had accurate

results in a little physical movement. The low

accuracy occurred when there were several

movements, particularly on the wrist. The light

intensity, in this case, will inaccuracy measure the

density of blood due to the change of scattered and

absorbed light through the skin. Fluctuation heart

rate measurement by employing PPG occurred even

in a little activity (Pessemier, 2017). The multi-

measurement system, with an average of a set of

data, is a proper option to be investigated for

Endrawati, B., Hasanah, B., Mudeng, V., Pamungkas, K., Rizki, A., Ramadhani, . and Bintang A., E.

Heart Beat Monitoring Device with an Optical Sensor.

DOI: 10.5220/0009445102210225

In Proceedings of the 1st International Conference on Industrial Technology (ICONIT 2019), pages 221-225

ISBN: 978-989-758-434-3

221

yielding precise results in the heartbeat sensing

system.

In addition, a tiny pressure sensor but with

efficient measurement and flexible shape developed

to cope with comfortable and low-cost solutions in a

mobile medical device (Shu, 2015). An idle heart

rate, compared to the threshold heart rate, was

presented to determine the heart condition using the

collected data, which was stored in the database. The

apparatus collected data from an analog sensor, then

transfer them to the database via the internet (Farin,

2016). With new technology, the heart rate detection

can be extracted by ultra-wideband (UWB) impulse

radar without touching and placing the sensor

around the body (Cho, 2018). The telemonitoring

analyzing with heart rate sensor node was

demonstrated for wireless body sensor networks

(WBSNs) (Fouad, 2017), as well as continuous

monitoring applied bandpass filter (BPF) based on

light-dependent resistor (LDR) as a signal receiver

and light-emitting diode (LED) as a light transmitter

(Cohen, 2017).

In this study, we present the heartbeat monitoring

(HBM) by implementing a non-invasive heart rate

sensor with a wavelength of 609 nm involving an

infra-red (IR) LED and a photodetector. The heart

pulse, then processed by the NodeMCU ESP8266

microcontroller module. Based on the data obtained

from the proposed device, we compare them with a

pedometer in a smartwatch of Xiomi Mi Band 3 to

verify the heartbeat in no activity and after activity

conditions.

2 METHODS

2.1 Designed System

Estimating the heart condition through the

placement of the sensor on the index finger is the

aim of HBM. The sensor has embedded a filter and

amplification circuits. Therefore, it can be interfaced

directly to the microcontroller module. Also, it was

provided in a sensor pair packaging composed of

two primary components, namely an IR LED and a

photodetector.

The low power IR LED is capable of penetrating

the skin of the human body due to it has a

wavelength of NIR. The NIR light penetrates inside

the fingertip, hence some of the light will be

scattered and absorbed. The blood pumping from the

heart induces the variation in light intensity: the

higher blood velocity, the higher heart bpm, and vice

versa. The photodetector has to receive the light

returning from inside the fingertip accurately. Figure

1 depicts the illustration of an index finger on the

sensor to determine the heart rate.

Figure 1: Illustration of HBM fingertip measurement.

The sensor counted the pulse when fingertip of

the index finger touching well it. As can be seen in

Figure 1, the blood pressure analog data in the artery

representing by the red line will be converted to the

heart rate in the embedded algorithm inside the

microcontroller. This mechanism drove us to

develop medical apparatus in HBM purposes.

Besides, we discovered that ischaemic heart disease

contributed to reducing the expectancy of men

respecting women is 0.84 years (World Health

Organization, 2019).

We designed the system with a pulse heart rate

sensor, NodeMCU ESP8266 microcontroller

module, and an organic LED (OLED) display to

interpret an HBM device, as shown in Figure 2. As

explained previously, the data from the sensor was

transferred directly to the microcontroller, and there

was an ADC processing with the counting processes

of the raw data from the sensor to be a bpm. Next,

the bpm and waveform displayed in OLED.

PulseHeart

RateSensor

XD‐58C

NodeMCU

LoLinV3

OLED

128x64

HeartBeat

bpm

Figure 2: The proposed full system.

For detecting the heart rate, not all pins of

NodeMCU was used. The sensor and OLED needed

3 volts for the power source, which was provided by

two pins of NodeMCU. Additionally, only one pin

in the microcontroller was necessary for connecting

the signal (S) pin on the sensor to the A0 pin. SCL

and SDA pins on OLED were interfaced to D0 and

D1, respectively. Figure 3 shows the wiring diagram

of HBM. We tried to design the measurement

system with minimum electronic components for

considering in the future work to provide efficient,

low cost, tiny, portable, and mobile HBM

instruments.

The used system can be modified in the data

transmission due to NodeMCU is a microcontroller

module equipped by the Wifi module. It enables to

ICONIT 2019 - International Conference on Industrial Technology

222

send the obtained data from the sensor to the

planned database; therefore, not only the person who

is worn, and this device can monitor the heart

condition, but also the others.

RST

VIN

NodeMCU

S+

‐

OLED

128x64

PulseHeartRate

SensorXD‐58C

GND

VCC SCL SDA

Figure 3: The schematic of HBM.

2.2 Algorithm

In this work, the software implementation was

applied in the microcontroller. The flowchart for

HBM is shown in Figure 4. First, analog data from

START

HeartBeat

=Value

BeatComplete?

Time=Time+1

Display

bpm

Value<LowerThreshold

(500)

Value>UpperThreshold

(550)

Time=0

Time=Time+1

END

YES

NodeMCUOFF?

YES

bpm=60/(Value/1024)

YES

Figure 4: Flowchart for HBM.

The sensor will become the input for the

microcontroller. The input indicates a heartbeat in a

digital signal due to the role of ADC. We count the

time was 0 for the initial condition. Then, we

determined two threshold values, for instance, 500

as lower and 550 as upper thresholds, respectively.

In each process, the algorithm will increase the time

by one. The NodeMCU has 10 bit ADC or 1024 in

decimal; hence, the digital data has to be divided by

1024. Afterward, bpm is obtained from



/

. These processes are existed to

measure the heart rate in our HBM.

3 RESULTS

We compared the designed measurement system

with a smartwatch made by Xiomi Mi Band 3. The

experimental set up conducted by no activity and

after activity states. Further, we invited three

volunteers to participate in the tests. An adolescent

14 years old and two adults with 20 and 49 years old

were investigated using two devices simultaneously.

Our HBM was placed on the fingertip of the index

finger while the smartwatch was worn on the wrist.

To ensure the test results, we monitored the heart

beat for the right hand and left hand, alternately with

three times data retrieval.

The HBM and smartwatch first put on the right

hand in the no activity state. Then, we monitored the

heartbeat and comparing two of a set of data from

HBM and smartwatch. In the state of after activity,

we restricted only in a little movement of ran on the

spot for 10 seconds. Nonetheless, we allowed the

resting times for 10 to 15 minutes to proceed to the

next trial tests.

Figure 5 demonstrates the HBM system for

measuring the heart rate. Figure 5 (a) depicts the

sensing on the left hand with two devices on the no

activity state. The left figure of Figure 5 (b) shows

the index finger illuminated by the light source from

the sensor. Moreover, the right figure in Figure 5 (b)

indicating the measured heart rate is 82 bpm.

Table 1 shows the comparison between HBM

and smartwatch results for 14, 20, and 49 years old

with no activity and after activity condition on the

right hand. The delta measurement of HBM and

smartwatch maximum was 10 bpm with no activity

occurred for 14 years old and 49 years old on the

third data retrieval. The difference maximum

measurement data was at 14 bpm for 14 years old

after activity on similar data retrieval.

Heart Beat Monitoring Device with an Optical Sensor

223

Table 1: Results of the right hand.

Activity HBM Smart Watch

Heart Rate 1

(bpm)

Heart Rate 2

(bpm)

Heart Rate 3

(bpm)

Heart Rate 1

(bpm)

Heart Rate 2

(bpm)

Heart Rate 3

(bpm)

None

14 years old 71 70 69 73 70 79

20 years old 69 66 77 72 66 72

49 years old 82 64 84 88 64 74

After

14 years old 74 86 88 74 86 74

20 years old 83 84 84 73 67 79

49 years old 94 74 87 98 64 84

Table 2: Results of the left hand.

Activity HBM Smart Watch

Heart Rate 1

(bpm)

Heart Rate 2

(bpm)

Heart Rate 3

(bpm)

Heart Rate 1

(bpm)

Heart Rate 2

(bpm)

Heart Rate 3

(bpm)

None

14 years old 73 71 71 71 73 79

20 years old 71 68 75 73 68 74

49 years old 80 64 85 89 64 77

After

14 years old 76 84 90 76 89 76

20 years old 85 87 86 78 69 79

49 years old 93 72 89 99 64 86

(a)

(b)

Figure 5: HBM hardware on a view of (a) left hand and (b)

zooming in the index finger with showing bpm and

waveform.

Table 2 shows the comparison between HBM

and smartwatch on the left hand. The delta

measurement of HBM and smartwatch maximum

was 9 bpm with no activity occurred for 49 years old

on the first data retrieval? The difference maximum

measurement data was at 18 bpm for 20 years old

after activity on the second data retrieval.

The considerable results were generated by the

proposed HBM. The result variations were possible

due to the sensitivity of photodetector. Nevertheless,

it has a similar potentiality comparing with the

commercial smartwatch.

4 CONCLUSIONS

In this study, a competitive HBM system has been

proposed in measuring the heart rate. Farther, the

future work is considered to improve the

performance of proposed HBM through the

packaging model, and data transmission system via

mobile and internet applications wirelessly.

According to the experimental results, they indicate

that HBM is feasible to be a secondary wearable

medical apparatus to check the data of heart rate for

preventive action in the mortality caused by health

problems, especially heart failure or disease. Over

and under the results of HBM comparing to the

smartwatch, results were occurred and could not be

accurately determined; however, it remains effective

ICONIT 2019 - International Conference on Industrial Technology

224

for heart rate screening. Hereafter, the results can be

initial progress for intensifying the development of

HBM as the medical device.

ACKNOWLEDGMENT

This research was financially supported by the

Ministry of Research, Technology, and Higher

Education of the Republic of Indonesia through

grant 007/SP2H/LT/DRPM/2019.

REFERENCES

Arulananth.T. S, B. Shilpa, 2017. Fingertip based Heart

Beat Monitoring System Using Embedded Systems. In

International Conference on Electronics,

Communication and Aerospace Technology. IEEE.

Cho, H. S., Y. J. Park, 2018. Detection of Heart Rate

through a Wall Using UWB Impulse Radar. Journal of

Healthcare Engineering, Vol. 2018, No. 4832605.

Cohen, Z., Shyqyri Haxha, 2017. Optical-Based Sensor

Prototype for Continuous Monitoring of the Blood

Pressure, IEEE Sensors Journal, Vol. 17, No. 13.

Farin N. J., S. M. A. Sharif, I. Mobin, 2016. An Intelligent

Sensor Based System for Real Time Heart Rate

Monitoring (HRM). Intelligent Control and

Automation, Vol. 7, No. 2.

Fouad, H., H. Farouk, 2017. Heart Rate Sensor Node

Analysis for Designing Internet of Things

Telemedicine Embedded System, Vol. 4, No. 1.

Hashem, M. M. A., R. Shams, Md. A. Kader, Md. A.

Sayed, 2010. Design and Development of a Heart Rate

Measuring Device Using Fingertip. In International

Conference on Computer and Communication

Engineering. IEEE.

Jubran, Amal, 2015. Pulse Oximetry. Critical Care, Vol.

19, No. 1.

Keat, L. C., A. B. Jambek, U. Hashim, 2016. Heart-rate

Monitoring System Design and Analysis Using a Nios

II Soft-core Processor. International Journal of

Electronics and Telecommunications, Vol. 62, No. 3.

Mudeng, Vicky, Y. Priyanto, A. Giyantara, 2018. Image

Reconstruction for Frequency-Domain Diffuse Optical

Tomography. Turkish Journal of Electrical

Engineering and Computer Sciences, Vol. 26, No. 5.

Pessemier, T. D., L. Martens, 2017. Measuring Heart Rate

with Mobile Devices for Personal Health Monitoring.

In the 12th International Conference on Internet and

Web Applications and Services. IARIA.

Shu Y., C. Li, Z. Wang, W. T. Mi, Y. X. Li, T. L. Ren,

2015. A Pressure Sensing System for Heart Rate

Monitoring with Polymer-Based Pressure Sensors and

an Anti-Interference Post Processing Circuit, Vol. 15,

No. 2.

World Health Organization, 2019. World Health Statistics

Overview 2019: Monitoring Health for the SDGs,

Sustainable Development Goals, World Health

Organization. Geneva.

Heart Beat Monitoring Device with an Optical Sensor

225