Body Monitoring System Design Based on Android Smartphone

Weibo Song, Hong Yu, Ce Liang, Qihua Wang1, Yunfeng Shi1

School of Information Engineering, Key Laboratory of Ocean Information Technology of Liaoning Province,

1Educational Technology and Computing Center, Dalian Ocean University,

Dalian, China e-mail:swb@dlou.edu.cn

Abstract— Based on android smartphone, body monitoring system is a hot area of research [1]. At present, there are some shortcomings of human body monitoring equipment such as single function and expensive, in order to solve the problems, this paper mainly designed a body monitoring system based on android smartphone. The operator can observe the information on a mobile screen. The design is a combination of new brainwave capture sensor, a novel electrocardiogram (ECG) acquisition sensor, human temperature detection, network transmission, smartphone application. This paper analyzes the key technologies employed in the system. Theory and method proposed in the paper are tested by experiments. The results of experiments have proved that the system is correct and feasible.

Keywords- Android; Smartphone; Infrared thermometer; Electrocardiogram; Bluetooth; Brainwave

I. INTRODUCTION With the development of smartphone, it has formed a

smartphone-based body monitoring system with a combination of the advantages of network technology and multiple sensor fusion technology. Body monitoring system greatly improves the operational capability of health care, such as remote operations, wireless health care so on.

There has been a growing concern with technology of medical care which has developed rapidly and plays an increasingly important role in our life.

Traditional health care technologies mostly are confined to hospitals and other specific place, which is not convenient for the user’s movement. It may also take lots of money. At present, several proposals, such as IMEC [2] and AliveCor [3], have been used to concentrate to this issue. But they also suffer from some limitations mainly concerning single function of equipment and the potential radiation hazards by mobile phone direct contacting with the body. In order to solve the purpose of mobile medical care, we can use android smartphone as a component of this system. Android mobile phone can not only receive the data collected by our hardware device but also can transmit these data to remote server in time.

This method not only simplifies and speeds up the process of information acquisition, processing and analysis, but also declines costs of equipment; therefore, researchers have become more interested in wireless health care.

In the present paper, we report on a preliminary study of human body monitoring equipment including three main

functions such as brainwave capture, ECG acquisition and human temperature detection, furthermore detail the usage of the key sensors.

The paper is organized as follows. After this introduction, section 2 describes the system architecture. Then we discuss key technologies of this system in section 3. Section 4 provides results of experiment, and followed conclusion and acknowledgment.

II. SYSTEM ARCHITECTURE OVERVIEW Our system is composed of software and hardware. The

main functions of this system are detecting human’s temperature, electrocardiogram, electro-encephalogram (EEG) by different hardware. These data which are gathered by hardware are sent to the Bluetooth receiving device of android smartphone over the Bluetooth transmission equipment which is fixed on our device. They are analyzed and then saved into SD card which is inserted in the android smartphone.

• Software includes: Application programs of android platform based on the java language can be implemented and tested by eclipse. These application programs were eventually packaged in an apk file which is installed on the android smartphone. The installed software can start the Bluetooth on your android smartphone to receive information from the hardware.

• Hardware includes: The single chip microcomputer system (SCMS), an infrared thermometer detecting human temperature module--ZTP-135SR, an electrocardiogram detection module--BMD101, an electro-encephalogram detection module--TGAM, a wireless Bluetooth devices, an android smartphone. Fig. 1 provides a flow chat to describe the body monitoring system design based on android smartphone.

Figure1. Body monitoring system design based on android smartphone

1147978-1-4673-4805-8/12/$31.00 c©2012 IEEE

III. KEY TECHNOLOGIES

A. Android Android platform [4] can provide extensive application-

programming interface (API) [5] to fulfill wireless transmission of data between Bluetooth devices. Communication between Bluetooth devices includes four steps: set up a Bluetooth device, looking for possible matching devices on the local area network (LAN), connection device, data transfer between devices. Some of the basic classes are required to establish a Bluetooth connection interpreted in table I [6]. The operating environment of software shows in Fig. 2 [7] [8].

TABLE I. BASIC CLASSES FOR ESTABLISH A BLUETOOTH CONNECTIONS

Class Mental states and conditions

BluetoothAdapter A local Bluetooth adapter

BluetoothDevice A remote Bluetooth device

Bluetoothsocket A Bluetooth socket interface

Blueboothserversocket Open the connection of service to listen for connection requests that may come

Bluetoothclass General features and capabilities of a Bluetooth device

Figure 2. Operating environment of software

B. TGAM The TGAM (see Fig. 3) is a BCI-based brainwave sensor

with a chip which is developed by the NeuroSky Company in USA [9] [10]. TGAM just uses a single and comfortable non-intrusive dry electrode sensor contacting on the operator’s forehead and makes that acquisition of brainwave data no longer confined to laboratory. It is easy to interpret your current state of mind on the analysis of data gathered by TGAM and then transmitted by Bluetooth device in real time. Mental states described as attention and meditation

levels using eSense meters output by TGAM are comprised of a complex combination of artifact rejection and data classification methods. The connection method of TGAM shows in Fig. 4[11].

(a) (b)

Figure 3. TGAM (a:front) (b:back)

(a) (b)

(c)

Figure 4. (a):Forehead dry electrode wire, (b): Ear clip, (c):TGAM connection method

Along with the ability to record raw EEG data, TGAM can acquire highly sensitive brainwave data which are captured in each frequency band interpreted in table II [12].

TABLE II. EEG FREQUENCY BANDS AND RELATED BRAIN STATES

Brain type Frequency range Mental states and conditions

Delta 0.1Hz to 3Hz Deep, dreamless sleep, non-REM sleep, unconscious

Theta 4Hz to 7Hz Intuitive, creative, recall, fantasy, imaginary, dream

Alpha 8Hz to 12Hz Relaxed, but not drowsy, tranquil, conscious

Low Beta 12Hz to 15Hz Formerly SMR, relaxed yet focused, integrated

Midrange Beta 16Hz to 20Hz Thinking, aware of self &

surroundings High Beta 21Hz to 30Hz Alertness, agitation

Certain eSense meters of mental state is output with a

number in a scale from 0 to 100 for each captured state. By using these data we may group operator’s attention and meditation levels [13] [14].

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C. ZTP-135SR In our system we have used a kind of thermopile sensor

which is non-contact surface temperature measuring. It can generate voltage signals and shows a stable response to DC radiation. The ZTP-135SR model [15] (see Fig. 5) is consisted of thermo-elements, flat IR filter, and device for temperature compensation. This device adopted small chip and wide diaphragm in order to enhance sensitivity. The standard IR filter is suitable to the spectral range above 5 um wave length. This thermopile sensor [16] can provide the customer with optimal solution for each application.

This design connects with single chip microcomputer system which is the core controller of the system mainly including a STC series chip with 40-pin and a crystal oscillator with 12MHz to obtain more stable clock frequency and reduce measurement tolerances.

(a)

(b)

Figure 5. (a:ZTP-135SR) (b: bottom view)

Principle of infrared temperature sensor [17]: Due to thermal motion of molecular, molecular radiate electromagnetic waves into the surroundings including infrared wavelengths. The relationship of radiation energy density and temperature of the object is in Planck's law. The radiated energy related to the temperature of an object. Measuring principle is to obtain E using (1).

Ε=δε(Τ4− Τ40) (1)

Where E is the radiant exitance, W•m-3; is the Stephen-Boltzmann constant, 5.67×10-8 W•m-2•K-4; is Object radiation rate; T is the temperature of an object, K; T0 is ambient temperature around the object, K. The sensor transmitting waveform shows in Fig. 6.

Figure 6. Sensor transmitting waveform

Figure7. Relationship between output voltage and detecting temperature of

ZTP-135SR

Because the human body temperature is usually measured in the range of 34 - 42°C, sensor output voltage range for 0.7-1.5mV, there is a linear relationship between temperature and voltage as shown in Fig. 7 [18].

This system with infrared sensor just absorbs human body infrared radiation and don’t emit any ray to the human body. So the system is safe to human health.

D. BMD101 Chip BMD101 [19] (see Fig. 8) is the third generation of

biological monitoring and signal processing chip which is developed by the NeuroSky Company in USA. It has advanced analog front end circuit and powerful digital signal processing architecture. Bio-signal can be collected from uV to mV by BMD101, and then processed by the Neurosky's patented algorithm.

The BMD101 has very low system noise and control of gain, it can be effective monitoring of biological signal and use 16 - bit Analog - Digital Converter with high precision and turn them into digital signals. The analog front end

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includes a detection circuit of sensor-off. The function of BMD101 pins can be interpreted in table III [20].

In the world currently, BMD101 is the smallest ECG testing chip which is embedded on the PCB board of the mobile device only taking up very little space. This system based on the BMD101 chip are easy to use, you can complete the ECG sampling just with two fingers. An apk application is installed in mobile phones for the analysis and display of ECG signals which are transferred by Bluetooth device. System implementation circuit of BMD101 shows in Fig. 9 [21].

Figure 8. BMD101 top view

TABLE III. FUNCTION OF BMD101 PINS

Pin Name Function

1 CS Power up or down control of LDO, input

2 SEP Positive ECG analog input, input

3 SEN Negative ECG analog, input

4 RX UART RX, input

5 TX UART TX, output

6 RESET System reset pin, input

7 GND Ground,Supply

8 VDD 3.3Vpwoer supply, Supply

Figure 9. System implementation circuit of BMD101

E. Bluetooth Bluetooth is a proprietary open wireless technology

standard for exchanging data over short distances from fixed and mobile devices. It can connect several devices, overcoming problems of synchronization. With the characteristic of full-duplex communication of Bluetooth devices, the body sensor network system can be designed successfully [22].

Our system uses HC-05 (see Fig. 10) embedded Bluetooth serial communication module which has two work modes: order-response work mode and automatic connection work mode. And there are three work roles (Master, Slave and Loopback) at the automatic connection work mode. When the module is at the automatic connection work mode, it will follow the default way set lastly to transmit the data automatically. When the module is at the order-response work mode, user can send the AT command to the module to set the control parameters and sent control order. The work mode of module can be switched by controlling the module PIN (PIO11) input level.

Figure 10. Bluetooth module

IV. EXPERIMENT Several experiments have achieved the goal to study this

body monitoring system. An apk application is installed in mobile phones for the analysis and display of ECG, brainwave, and human body temperature signals which are transferred by Bluetooth device. The first experiment focused on detecting operator’s brainwave to group operator’s attention and meditation levels (see Fig. 11). The second experiment aimed at detecting human temperature (see Fig. 12). The third experiment proved electrocardiogram collection (see Fig. 13). The fourth experiment showed that the stability of Bluetooth device.

Figure 11. Attention and meditation levels

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Figure 12. human temperature detection

Figure 13. Electrocardiogram collection

V. CONCLUSION In this paper we designed a body monitoring system

design by using android smartphone. Through the testing of the software programming, results shows that the android smartphone can achieve to send and receive data, which is an important reference value to the mobile medical care. Although experimental results have shown that our approach is both general and practical, they are just simple realization of each part, the further works will mainly focus on optimization of this system as follows:

First, software programs will be improved such as memory consumption, user interface and comprehensive service. Second, the value of eSense changes quickly, so we need to study how to exercise for reducing such instability. Third, telemedicine is implemented by sending the collected information to doctors or medical services systems.

VI. ACKNOWLEDGMENT This research was supported in part by Plan of Liaoning

Science and Technology Department of China (No.2010216008), Plan of Dalian Municipal Science and Technology Bureau of China (No.2011A16GX057).

Thanks for my colleague’s help to complete final experiments, particularly, partners of this paper.

REFERENCES [1] Guangxian Ji, “Applied Prospect and Development Research Under

the Android System Environment”, Software. vol.32(10), 2011, p.50-51.

[2] “http://www.imec-tw.tw/be_en/press/e-newsletter.html”. [3] “http://www.alivecor.com/”. [4] “http://code.google.com/android/intro/hello-android.html”. [5] Shicheng Zhang, “Development and Research of Application Based

on Goole Android”, Computer Knowledge and Technology, Vol.5(28), October, 2009, pp.7959-7962.

[6] Yunchen Jiang, “Android system principle and practice” [M], Beijing Institute of Technology Press, 2011.

[7] Zhilong Yu, Third Edition of “Google Android SDK development paradigm encyclopedia” [M], Posts & Telecommunications Press, 2011.

[8] Liang Zhao, “Research and Design of Interface Based on Android Technolog”, Computer Knowledge and Technology, Vol.5(29), October, 2009, pp.8183-8185.

[9] Genaro Rebolledo-Mendez, “Assessing NeuroSky’s Usability to Detect Attention Levels in an Assessment Exercise”, 13th International Conference on Human-Computer Interaction. vol.5610, 2009, p. 149-158.

[10] Yoshitsugu Yasui,“A Brainwave Signal Measurement and Data Processing Technique for Daily Life Applications”, Journal of Physiological Anthropology, Vol.28, 2009, p.145-150.

[11] NeuroSky, Inc, January27, 2011-specifications- TGAM. [12] NeuroSky, Inc, December15, 2009- White Paper- Brain Wave Signal

(EEG). [13] Katie Crowley, “Evaluating a Brain-Computer Interface to Categorise

Human Emotional Response”, 10th IEEE International Conference on Advanced Learning Technologies. vol.81, 2010, p. 276-278.

[14] Weibo Song, “Teleoperation Robot Control System Based on Mindband Sensor”. 4th International Conference on Intelligent Human-Machine Systems and Cybernetics. vol.2, 2012, p.264-267.

[15] Data Sheet: of infrared Thermopile temperature sensor ZTP135SR of GE company, http://www.gc.con/.

[16] Guili Peng, “Research and Application of ZTP135S-R InfraredSensor Compensation Algorithm”, Journal of Southwest University of Science and Technology, vol.23(4), 2008, p.68-72.

[17] Guili Peng, “Application of ZTP135S-R sensor in thermometer”, International Electronic Elements, 2006.4, p.38-40.

[18] Guili Peng, “The Design of Infrared Thermomete”, Control& Automation. vol.22(14), 2006, p.67-69.

[19] NeuroSky, Inc, 2011-Data Sheet: BMD101. [20] NeuroSky, Inc, 2011-BMD100 Module Brochure. [21] NeuroSky, Inc, June 14, 2012-Application Note-BMD101 Integration

Reference Design/Schematic. [22] Guangzhou HC Information Technology Co. Ltd. Product Data

Sheet:HC-05.

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