Simple Measurement System for Biological Signal Using a Smartphone

International Journal of Electrical and Computer Engineering (IJECE)
Vol. 8, No. 6, December 2018, pp. 4157~4163
ISSN: 2088-8708, DOI: 10.11591/ijece.v8i6.pp4157-4163  4157
Journal homepage: http://iaescore.com/journals/index.php/IJECE
Simple Measurement System for Biological Signal Using a
Smartphone
Ryoichi Miyauchi1
, Koichi Tanno2
, Hiroki Tamura3
1
Interdisciplinary Graduate School of Agriculture and Engineering, University of Miyazaki, Japan
2
Department of Electrical and Systems Engineering, University of Miyazaki, Japan
3
Department of Environmental Robotics, University of Miyazaki, Japan
Article Info ABSTRACT
Article history:
Received Mar 20, 2018
Revised Jun 12, 2018
Accepted Jun 30, 2018
This paper describes simple measurement system for biological signal using
smartphone. The proposed system consists of an instrumentation amplifier, a
filter and an AC/DC converter. The biological signal is converted to the
digital data through the microphone terminal with A/D converter in the
smartphone. In many cases, the circuits require the power sources such as the
cell batteries, however, the proposed system is supplied the power through
the earphone terminal of the smartphone. Therefore, the proposed system no
require the batteries. The software of this system parallelizes the processing
so that the earphone output and the microphone terminal can be executed at
the same time. The proposed system was verified through the measurement
of surface electromyogram using discrete parts and iOS. Results of
experimentation, the proposed system was operating correctly.
Keyword:
AC/DC converter
Biological signal
Signal conditioning
Smartphone
Copyright © 2018 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Koichi Tanno,
Department of Electrical and Systems Engineering,
Institute of Education and Research for Engineering, University of Miyazaki,
1-1 Gakuenkibanadai-Nishi, Miyazaki 889-2192, Japan.
Email: tanno@cc.miyazaki-u.ac.jp
1. INTRODUCTION
In recent years, improving the quality of life and increasing healthspan is become global concern
and challenges [1]-[5]. For this reason, management of health on a daily basis is very important, and
measuring the own vital data, such as heartbeats, pulses etc, using various equipment are essential. On the
other hands, wearable devices, which evolves at a rapid pace, are one of the equipment to measure the
biological signal. In the future, own health management would become almost equal to management by
personal trainers by analyzing measured data using AI and deep learning [6], [7]. However, it is difficult to
realize the above system because the system requires the many functions and the cost will become high.
Therefore popularization of the wearable devices is delayed.
On the other hands, biological signals, such as Electromyogram (EMG), Electrooculogram (EOG),
Electroencephalogram (EEG), Electrocardiogram (ECG), are well known as the vital data. In general,
KHz). In order to implement the biological signal measurement system, not only an analog circuit such as the
amplifier, filter, Analog to Digital (A/D) converter, but also a digital circuit such as processor and memory
are required. In addition, the general wearable devices are consists of a measurement terminal, a display
terminal, and a wireless communication block, etc. That is to say, these kind of systems become complex and
high cost.
In this research, in order to realize the system simply and reduce the cost, a new architecture for
biological measurement system using a smartphone is proposed. The proposed system consists of an
instrumentation amplifier, a filter and an AC/DC converter and these circuits are supplied the power through

 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 6, December 2018 : 4157 - 4163
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the earphone terminal of the smartphone. Therefore, the proposed system no require the batteries. The
proposed system was realized by using discrete parts and verified through the measurement of surface EMG
(s-EMG). The experimental results are shown in this paper.
2. CONVENTIONAL MEASUREMENT SYSTEM
Figure 1 shows example of the stationary type measurement system. The stationary type
measurement system is constructed by analog front end (AFE), and PC. In addition, AFE and PC are
connected by USB, therefore, this system is one of the wired system. AFE consists of an amplifier, a filter
and an A/D converter.
The stationary type measurement system is often used for medical, and this system has some
advantages; this system has high accuracy and multi input channels and can be monitored measured data on
real time. On the other hands, this system has an disadvantage of low portability.
Figure 1. Stationary type measurement system
Figure 2 shows example of the wearable type measurement system. The wearable type measurement
system consists of AFE, PC, memory, communicator and battery. And this system is one of the wireless
measurement system. The advantage of the wearable type measurement system is high portability, however,
it requires many function and high cost.
Figure 2. Wearable type measurement system

Int J Elec & Comp Eng ISSN: 2088-8708 
Simple Measurement System for Biological Signal Using a Smartphone (Ryoichi Miyauchi)
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3. PROPOSED MEASUREMENT SYSTEM
3.1. System Architecture
Figure 3 is proposed measurement system, and we call this system Signal Conditioner. The
proposed system consists of three circuit blocks; the instrumentation amplifier (IA), the filter and AC/DC
converter. The IA is amplified input signal from sensor because the amplitude of biological signals very
small. In this system, we adopted the IA, which has very high input impedance and CMRR. Furthermore,
gain of the IA can be choose by the selecting a resistor. The low pass filter (LPF) is adopted in this system
for eliminating the noise other than the target signal. Because the frequency of the biological signal is
relatively low in general, the cutoff frequency of the LPF is less than 1000 Hz in this system. The AC/DC
converter of the last block is used for generating the DC power supplies. The audio signals, which are the
sinusoidal waves, are generated by the application program in the smartphone, and the generated audio
signals are outputted through earphone terminal of the smartphone. And then, these audio (sinusoidal) signals
are converted to DC by the AC/DC converter. This DC signals are used for the power sources for operating
the circuits in the proposed system.
Comparing the conventional stationary type measurement system shown in Figure 1, the proposed
system can remove the A/D converter because the smartphone can receive analog signal directly through the
microphone terminal, and the A/D converter is implemented in the smartphone. In addition, comparing the
conventional wearable type measurement system, the proposed system can remove the A/D converter, the
communicator and the battery.
Figure 3. Proposed measurement system
3.2. System Realization
Figure 4 shows the system realization using discrete parts. RG is resistor for selecting the gain of IA
which is given by equation 1. In equation 1 is constant value which depends on the device (decided by
register network in IA), and selecting small RG can be obtained high gain if we need.
𝑔𝑎𝑖𝑛 = 1 +
𝛼
𝑅 𝐺
(1)
RF1 and CF1 constitute of the LPF, and this LPF is necessary for reducing the noise in this system.
The main noise in this system is the ripple which is occurred from AC/DC converter, and the frequency of
this noise is more than a few kHz. In the actual realization, we adopted a first order LPF with the cut-off
frequency is approximately 600Hz.
AC/DC converter shown in Figure 4 is the sinusoidal wave to DC converter with voltage doubler,
which outputs both positive and negative voltages. In the biological signal measurement system, analog
circuit blocks need positive and negative voltage sources because the bias voltages is not added to the input
signal from sensor. Furthermore, the output voltage from the earphone terminal is not generally so high,
therefore we employed the AC/DC converter with voltage doubler in order to operate all circuit blocks.

 ISSN: 2088-8708
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D1 and C2 constitute the well-known half-wave rectifier circuit [8][9]. The AC/DC converter with
voltage doubler can be realized by adding to D2 and C1. By adding D2 and C1, the negative half cycle of the
input signal from the earphone terminal charge C1 and the next positive half cycle charge C2 with adding the
voltage of C1. As the results, the positive voltage doubler can be achieved. In the same way, the circuit of the
bottom side in AC/DC converter shown in Figure 4 also operates as the negative voltage doubler because the
circuit has complementary structure of upper side one.
Figure 5 shows activity diagram of proposed system. This system has to execute input and output at
the same time. In addition, input program and output program always have to work continuously. Therefore,
that is realized using multi-thread programming. And, some button is required for user interface(UI).
Figure 4. System realization
Figure 5. Activity diagram of proposed system

4161
4. EXPERIMENTAL AND COMPARISON RESULTS
Figure 6 and Table 1 show photograph of overall of the proposed system and experimental
condition, respectively. From Figure 6, it is clear that smartphone and the signal conditioner are connected
only one wire. Gain of IA and cut-off frequency of LPF are configured 51 times and 605 Hz, respectively.
And, the output signals of the earphone terminal consists of the amplitude of 1.5 V with the frequency of
10 kHz.
Figure 6. Photograph of overall of the proposed system
Table 1. Experiment Condition
Item Value
Smartphone Ipod touch 4th Gen.
Instrumentation Amplifier INA118 [10]
D1–D4 1N4148 [11]
C1–C4 4.7 F
RG 1 k
RF1 560 
CF1 0.47 F
In this experiments, we employed the s-EMG signal as the biological signal. Figure 7 and Table 2
show results of s-EMG measurement. In Figure 7, waveform, which are viewed on the display of the
smartphone, shows results of the FFT analysis for the measured s-EMG signal. From Figure 7, we can
confirm that the waveforms in the case of neutral, pronation and grip are different. Furthermore, we could
confirm that FFT results were changed according as moving the arm. And, Table 2 shows experimental result
for each examinee, and it is indicated that the proposed system could use generally. From these experimental
results, the proposed system can be operated correctly.

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Figure 7. Photograph of overall of the proposed system
Table 2. Experimental Result for Each Examinee
Examinee Right Arm Left Arm
A ○ ○
B ○ ○
C ○ ○
D ○ ○
E ○ ○
Table 3 shows comparison result between the proposed and conventional systems. From Table 3, the
proposed system could realize battery-less and low costs. However, comparing the wearable type
measurement system, portability is decreasing by using wired connection. And comparing the stationary type
measurement system the number of channels is only one in this situation. However, this disadvantage will be
able to overcome the signal multiplexing techniques, which were proposed in the past [12], [13].
Table 3. Comparison Result
Item Proposed Stationary Wearable
Connection type wired wired wireless
Battery not require not require require
Costs (Number of Item) Low High High
Portability Mid. Low High
Resolution depends on smartphone High Mid.
Number of channels 1*
multi 1
* The number of channels can expand by using the signal multiplexing techniques
5. CONCLUSION AND FUTURE WORKS
In this paper, very simple and battery-less biological measurement system, which consists of IA,
filter and AC/DC converter, has been proposed. We could confirmed that the proposed measurement system
operated correctly through the experiment with implemented system using the discrete parts and the
smartphone. Comparing the conventional systems, the proposed system has advantages which are battery-less
and low costs. In summary, the proposed system can be achieved the advantages by using implemented
functions of the smartphone positively. The future works are as follows; 1) expanding the number of
channels, 2) implementing the integrated circuit of the signal conditioner by using references [14]-[16], and
3) comparing and evaluating the proposed system with marketed products.
REFERENCES
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[7] Z. Che, Y. Liu, ''Deep Learning Solutions to Computational Phenotyping in Health Care'', 2017 IEEE International
Conference on Data Mining Workshops, pp. 1100-1109, 2017.
[8] T. Lehmann, Y. Moghe, ''On-Chip Active Power Rectifiers for Biomedical Applications,'' IEEE International
Symposium on Circuits and Systems, Vol.1, pp. 524-527, 2005.
[9] D. Karolak, et al., ''Design Comparison of Low-Power Rectifiers Dedicated to RF Energy Harvesting,'' IEEE
International Conference on Electronics, Circuits, and Systems, pp. 524-527, 2012.
[10] INA118, Precision, Low Power Instrumentation Amplifier, Texas Instruments Inc., Dallas, Sep. 2000[Online],
available from http://www.ti.com/product/ina118, accessed on March 5, 2018.
[11] 1N4148, High Conductance Fast Diode, On Semiconductor Inc., Phoenix, June 2015[Online], available from
http://www.onsemi.com/PowerSolutions/product.do?id=1N4148, accessed on March 5, 2018.

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[12] K. R. Moghaddam, et al., ''A 24-channel implantable neural recording based on time and frequency-division
multiplexing'', Analog Integrated Circuits and Signal Processing, Vol. 79, Issue 3, pp. 493-506, June, 2014.
[13] X. Zhao, et al., ''Analog Signal Compression and Multiplexing Techniques for Healthcare Internet of Things'', IEEE
International Conference on Mobile Ad Hoc and Sensor Systems, pp. 398-406, 2017.
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Energy Harvesting'', IEEE Applied Power Electronics Conference and Exposition, pp. 2844-2851, 2013.
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BIOGRAPHIES OF AUTHORS
was born in Kagoshima, Japan, on March 3rd, 1986. He received B. E. and M. E. degrees from
Faculty of Engineering, University of Miyazaki, Miyazaki, Japan, in 2008 and 2010,
respectively. He is currently studying to get Dr. Eng. degree at University of Miyazaki. From
2010 to 2015, he joined the Hitachi ULSI Systems Co., Ltd., Tachikawa, Japan. He was engaged
in development of application software for Windows and development of voice recognition
system for car navigation system. His research interests are biological signal measurement
system and analog integrated circuit.
was born in Miyazaki, Japan, on April 22, 1967. He received B. E. and M. E. degrees from the
Faculty of Engineering, University of Miyazaki, Miyazaki, Japan, in 1990 and 1992,
respectively, and Dr. Eng. degree from Graduate School of Science and Technology, Kumamoto
University, Kumamoto, Japan, in 1999. From 1992 to 1993, he joined the Microelectronics
Products Development Laboratory, Hitachi, Ltd., Yokohama, Japan. He was engaged in research
on low-voltage and low-power equalizer for read channel LSI of hard disk drives. In 1994, he
joined University of Miyazaki, where he is currently a Professor in the Department of Electrical
and Systems Engineering. His main research interests are in analog integrated circuit design and
multiple-valued logic circuit design. Dr. Tanno is a member of IEEE.
received the B. E. and M. E. degree from Miyazaki University in 1998 and 2000, respectively.
From 2000 to 2001, He was an Engineer in Asahi Kasei Corporation, Japan. In 2001, He joined
Toyama University, Toyama, Japan, where He was a Technical Official in Department of
Intellectual Information Systems. In 2006, He joined Miyazaki University, Miyazaki, Japan,
where He was an Assistant Professor in Department of Electrical and Electronic Engineering. In
2012, He is currently a Professor in the Department of Environmental Robotics. His main
research interests are Neural Networks and Optimization Problems. In recent years, He has the
interest in Biomedical Signal Processing using Soft Computing.

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