research article implementation of intelligent...

Research ArticleImplementation of Intelligent Electronic Acupuncture SystemUsing Sensor Module

You-Sik Hong1 Baek-Ki Kim2 and Bong-Hwa Hong3

1 Department of Computer Science Sangji University Wonju 220-702 Republic of Korea2Department of Information amp Telecommunication Engineering Gangneung-Wonju National UniversityWonju 220-711 Republic of Korea

3 Department of Digital Media Engineering Kyung Hee Cyber University Seoul 130-739 Republic of Korea

Correspondence should be addressed to Baek-Ki Kim bkkimgwnuackr and Bong-Hwa Hong bhhongkhcuackr

Received 30 August 2013 Accepted 2 February 2014 Published 9 March 2014

Academic Editor Young-Sik Jeong

Copyright copy 2014 You-Sik Hong et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Conventional electronic acupuncture can stimulate only one acupuncture point and patients have to decide the time and thestrength by themselves In order to solve these problems intelligent electronic acupuncture using biometric sensors and fuzzytechnology was developed in this paper And wireless electronic acupuncture system using sensor modules was developed in thispaper We used the sensor modules to obtain a patientrsquos diagnosis signals These sensor modules consist of 5 parts The signalswere analyzed to make instructions for the treatment and the sensing pad for electronic acupuncture was designed In additionadaptive wireless acupuncture system was developed to adjust strength and time of acupuncture and several acupuncture pointsof patients by using fuzzy technology We implemented efficient wireless electronic acupuncture system to get acupuncture easilyusing intelligent diagnosis system

1 Introduction

The electronic acupuncture is different from the traditionalacupuncture in their shape and treatment method But itsbasic principle of treatment is the sameMore than 60 percentof the electronic acupunctures developed in the countryuse low frequency and the rest is developed using instanta-neous electro stimulation Existing low-frequency therapeu-tic apparatuses are simple frequency generator (16sim32Hz)which attaches electrodes to patientrsquos diseased area Patientcannot be treated effectively because it does not providedetailed frequency Furthermore it cannot find acupuncturepoints since it has no consideration of the patientsrsquo sex ageweight illness and so forth And it causes a problem thatsome children and elderly people are bruised or woundedafter getting electronic acupuncture due to inappropriateacupuncture time and strength [1]

Intelligent electronic acupuncture means that theacupuncture system can treat a patient automatically withacupuncture adapted voltage current and frequency Toperform this electronic acupuncture the system has function

of sensing and treatment simultaneously And the systemrequires an accurate analysis and processing technique oflogical and statistical data using fuzzy [2 3]

The pulse is considered an important factor in orientalmedicine because a personrsquos pulse rate may reflect his or herhealth condition For example if a patientrsquos heart stops itis a very serious situation and this situation can be judgedby pulse Oriental doctors have considered pulse rates asimportant data in diagnosis But the existing blood pressurepulse analyzers have some problems It is uncertain whetherthe blood pressure pulse analyzing sensor is located preciselyon the radial artery and it is also difficult to diagnose pulseexactly depending on the thickness of forearm Furthermorethe analogue type of blood pressure pulse analyzers hasproblems with quantification of the blood pressure pulseAlthough some people may have the same forearm lengthbut the thickness of their blood vessel may differ Thereforethere is no set of data that is considered reliable enough tojudge the accuracy of blood pressure pulse rates Orientaldoctors should not only judge the basic biological signalssuch as the pulsersquos size strength and speed but should also

Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2014 Article ID 238502 7 pageshttpdxdoiorg1011552014238502

2 International Journal of Distributed Sensor Networks

Body signal parts

∙ Blood pressure sensing

∙ Skin conductivity sensing

∙ ECG signal sensing

∙ Oxygen saturation signal sensing

∙ Body temperature sensing

Signal analyzing and treatment system

∙ Electronic acupuncture part

Monitoring and DB generating

Figure 1 Whole system diagram of the intelligent electronic acupuncture system

consider the basic and quantitative analysis of the pulse inorder tomake an accurate diagnosis Also the doctors shouldconsider physical characteristics such as the thickness ofthe skin and blood vessels in order to reach an accurateconclusion Therefore measurement of the blood flow rate isa vital indicator in understanding the blood pressure rate andhow the substances in the blood are transported [4ndash6]

The method of exiting diagnosis has a problem whichcannot diagnose the old and the infirm exactly because thepatientrsquos condition including gender age skin is not takeninto consideration To solve this problem we analyzed thefine distinction considering thickness of skin and blood ves-sels and pulse whether they are big or small strong or weakand fast or slow We proposed the algorithm that diagnosesthe condition of a patient optimally using intelligent fuzzytechnique [7 8]

Adaptive wireless acupuncture system was developedin this paper by using pulse diagnosis system to adjuststrength and time of acupuncture and several acupuncturepoints of patients to whom intellectual fuzzy technology is

applied Conventional electronic acupuncture cannot findthe acupuncture points at once However SW which canstimulate multiple acupuncture points and calculate thetime of the electronic acupuncture was developed in thispaper Conventional electronic acupuncture only stimulatesthe acupuncture point but the electronic acupuncture withKIT (SW + HW) developed in this paper made remote orself-diagnosis possible using the conditions of the patientsand disease reasoning function Doctorsrsquo help is neededto find the acupuncture point with conventional electronicacupuncture Intelligent electronic acupuncture that easilycalculates optimal acupuncture time considering the patientsrsquohealth condition with smart phones was developed in thispaper

Figure 1 shows thewhole systemdiagramof the intelligentelectronic acupuncture system It consists of 4 parts The firstpart is a sensor module the second part is a main part whichanalyzes the transferred signals and generates the treatmentsignalsThe third part is an electronic acupuncture partwhichapplies electronic acupuncture according to treatment signals

International Journal of Distributed Sensor Networks 3

from the main partThe last part is a program for monitoringand generating DB

The composition of this paper is as follows Section 2is about a sensor module for electronic acupunctureand Section 3 is about intelligent pulse diagnosis algo-rithm Section 4 deals with implementation of the electronicacupuncture system Finally the conclusion is made inSection 5

2 Sensor Module for Electronic Acupuncture

We used several sensor modules to obtain a patientrsquos diagno-sis signals These sensor modules consist of 5 parts and theydetect and analyze the abnormal signals from human body

Figure 2 shows the sensor modules for electronicacupuncture system The measured signals from the eachsensor of modules are transferred to main the part

(1) Pulsimeter module It measures pulse rate It mea-sures the data from the finger connected to the fingersensor

(2) EGC module It measures electrocardiogram(3) SPO2 module It measures oxygen saturation of

blood(4) Skin conduction module It measures conductivity of

palmar skin(5) Body temperature module It measures temperature

of human body

3 Intelligent Pulse Diagnosis Algorithm

The intelligent pulse diagnosis system is composed of threeparts The first part is composed of the sensor to detect theconductance which is appropriate for injured part of humanbody and reference signal generator to adjust the signalgenerated from the patients The second part is composed ofDSP (Digital Signal Processor) board in which the signals aremeasured and classified using fuzzy algorithm The last partis composed of a computer system that displays the signalfrom DSP board to the monitor and analysis software todiagnose the patients Figure 3 shows the whole diagram ofphysical signal data network for electronic acupuncture Thealgorithm consists of 3 parts First step is sensing methodsthe second step is indexing methods and the third step isclassification methods

Pulse is beat-wave pattern of chest wall and great arteriesaccording to heartbeat The main purpose of pulse is toobserve cardiomotility and blood movement Recently studyusing physical characteristics shows that pulse wave patterncan change depending on condition of blood vessels andblood circulation The pulse wave pattern can be obtainedby second differentiation of digital plethysmogram usingphysical specific status such as uncertain inflection pointsIn this paper we classified a patientrsquos physical condition intothree categories as dangerous ordinary and normal condi-tion adapting pulse diagnosis algorithm using accelerationpulse wave pattern [9]

Fuzzy rules are generally presented with IF-THEN for-mat Fuzzy inference is procedures that infer new relationsor facts from the given rules and max-min reference is used

Input 119909 is 1198601015840 AND 119910 is 1198611015840

1198771 IF 119909 is 1198601 AND 119910 is 1198611 THEN 119911 is 1198621OR 1198772 IF 119909 is 1198602 AND 119910 is 1198612 THEN 119911 is 1198622

OR 119877119899 IF 119909 is 119860119899 AND 119910 is 119861119899 THEN 119911 is 119862119899Conclusion 119911 is 119862

Combination Function of Trust Value 1 and 2 type of fuzzycreation rule reduced from type of 5 and 6 can come to thesamenode and conclusion through different inference path toinfer fuzzy In this node the same conclusion reached two ofmore different trust value In this case combination functionof trust value is used to recalculate trust value of conclusion[2 8]

120573

119888= 120573comb (120573119888 120573

old119888) = max (120573

119888 120573

old119888) (1)

Here 120573old119888

is trust value of the conclusion reached throughinference path already 120573

119888is trust value of other conclusion

reached through another inference path If the 4 patientsrsquo (ab c d) illness condition is end-stage the value is displayed as08ndash10 shown in the left in case of the middle stage the valueis 04ndash07 and in case of the first stage the value is displayedas 01ndash03 The value in the middle shows patientrsquos physicalcondition For example if the patientrsquos height is 150 cm andweight is lower than 45 kg the value is displayed as 01ndash03

When the patientrsquos height is between 151 and 170 cm andthe weight is between 46 kg and 70 kg the value is displayedas 04ndash07 and when the height is 171 cmndash200 cm and weightis 71 kgndash130 kg the value is displayed as 08ndash10 In Figure 3the process to calculate fuzzy correction factor according topatientrsquos physical condition is shown

4 Implementation of the ElectronicAcupuncture System

Electronic acupuncture system with built in multi pad whichcan find out the condition of the patients automatically andtreat the patients simultaneously The system includes thefunction that can treat the patients with acupuncture andadjust voltage current frequency oscillation automaticallyaccording to their physical conditions To perform the func-tion the system senses and treats acupuncture simultane-ously and requires logical and statistical data processingtechnique using fuzzy and exact analysis Installing the 5round pads underneath the palm we can change the signaland then adaptive acupuncture treatment can be given

At this point measurement of the signal uses the wirelesstype instead of cable type Because the wireless type hasadvantage of convenience to get acupuncture reduction ofnoise by using cable connected to a computer system andprevention of electric shock depending on abrupt high-tension electricity [10 11]


Pulse sensor

Blood pressure and sugar sensor

ECG sensor

Hmote 2420

Infrared temperature

(a) Sensor module parts considering patientrsquos physical conditions

Bloodpressure

Bloodpressure

sensor

REF

PGAAMP AD

CC2430

USB to serial

BAT and DCDC

15

PGAAMP CC2430

USB to serial

BAT and DCDC

13

EGC3

Notchfilter AD

CC2430

USB to serial

BAT and DCDC

EGC2

EGC1

11

Photodiode

AMPLED

AD

DA

PGAAMP PIC18F85

USB to serial

BAT and DCDC

1

2

30

AD

MOSFET

TRarray

TFTLCD

UART

SD slop

DCDC

SSPV210(cortex-A8)

SDRAM

Nand flash

CPLDdecoder

AudioALC5622USB host

20

ZigBee

Ethernet

WiFi

Bluetooth 20

20

16bit

24bit24bit

10M

512MB

256MB

2G

(b) Block diagram of Sensor modules

Figure 2 Sensor modules for electronic acupuncture system

In order to treat acupuncture it is important not only toget information from the human body but also to learn agessexes height and weight of the patients To do this controlvariables using fuzzy algorithm are made before treatment ofacupuncture

Figure 4 shows Circuit of the acupuncture signal Thepart of sensing pad and contact point of the fingertipmade of stripe array type to distribute contact point areaevenly after being plated with gold to reduce electric resis-tance


RF channel 11Group ID

Hmoto2420 sender

Hmoto2420 sender

Hmoto2420 sender

Hmoto2420 senderHmoto2420 sender

Hmoto2420 receiver

Hmoto2420 receiver

Hmoto2420 receiver

Hmoto2420 receiverHmoto2420 receiver

0 times 05

RF channel 11Group ID 0 times 01 RF channel 11

Group ID 0 times 03

RF channel 12Group ID 0 times 01


2405Mhz2410Mhz

2415Mhz

Figure 3 Whole diagram of physical signal data network for electronic acupuncture

PWM-2

TX

B_DIR-2

A_DIR-2B_DIR-1

A_DIR-1

D_DIR-2D_DIR-1C_DIR-2C_DIR-1

RX

A_DIR-1A_DIR-2PWM-1

LOAD

PWM-1

Load

C11104

C15104

C16 C17104

U3MAX232

1381110

134526

129147

1615

R1INR2INT1INT2IN

C+

C2+

V+

R1OUTR2OUTT1OUTT2OUT

VCC

GN

D

+

C4

+

C8

+

C5

+C10

R1220

Q1C1011

23

R8

R5 R7

R3

R6

+

U52

36

81

C13104

C18104

C12104

C14104

LS1Buzzer

+

+C3

U1AT89C2051

1

10

1213141516171819

20

23678911

54

RSTVPP

GN

D

P10AIN0P11AIN1

P12P13P14P15P16P17

P30RXDP31TXDP32INTOP33INT1P34T0P35T1P37

XTAL1XTAL2

R4

D1 1N4007

C718P(CH) +

C9

R2

C618P(CH)

C2104

X-TAL1

U232

1

VINVOUT

AD

J

C1 104

U4

L6203

4

5

3

8

1

6

2

9

711

10

+VIN

+BOOST

+CURLIM

+SENSE

REF

LIM

DIM

D2

1N4148

GND

Output module-CH1

C1minus

C2minus

Vminus

Data A

Data B

10uf25V

10uf25V

10uf25V

10uf25V

10uf25V

+5V

+5V

+5V

+5V

+5V

110592m

82K

minus

minus

1 uF16 V

22uF16V

minusVINminusBOOST

minusCURLIM

minusVOUT

1K

1K

2K

10K 20K

20K

Output CH1

Output CH1

VCC

VCC

VCC

Figure 4 Circuit of the acupuncture signal

In this paper we designed the optimal algorithm whichcould judge the remote medical diagnosis using fuzzy logicand fuzzy inference rules and we simulated the process tocalculate the optimal acupuncture time of the body conditionof patients We produced the wireless communication partto transmit condition of patientsrsquo pulse skin conductanceand oxygen saturation data to userrsquos terminal or remotemedical terminal and to receive the control signal fromuserrsquosterminal or remote medical terminal

To do this we made the sensing pad the circuit of AMPand acupuncture signal wireless communicationmodule and

charging circuit for storage battery And also we proposed thesoftware including algorithm of analysis and control usingfuzzy technique Existing acupuncture system using DSPhas a complex structure uses up a lot of electricity and itrsquosbig and expensive But the adaptive wireless acupuncturesystem proposed in this paper is simple inexpensive andsafe Figure 5 shows simulation of the glove type electronicacupuncture

To implement wireless system we used the way of RFdata modem for wireless communication using NarrowbandFSK The feature of this way is robust to noise and it can


Figure 5 Simulation of the glove type electronic acupuncture

Figure 6 Data transmitter and receiver using RF communication

transmit data easily by simple communication protocol Andthis system is adapt to designmulti type data communicationsystem and can be designed by low power one 3V batteryin case of short distance We considered not only resistancemeasurement but capacitive component to reduce errordepending on several conditions of human body To do thiswe applied the pulse wave DC 50Vsim200V 500 uAsim1500 uAintermittent stimulation of 5Hzsim5KHz to the main pad andfingertip andmeasured the voltage peak and phase frequency[12 13]

We used 470MHz band frequency and designed thesystem to change 21 physical frequency And logical addressof a channel corresponding to each adaptive acupuncture wasassigned using polling technique and then calledThe systemsupports half duplex communicationThis way is suitable forthe system because the system requires low data and uses rel-atively low speed communicationThe output power of wire-less signal using button type battery is 1mW and it is adequateto transmit data without noise The speed of transmissionis 1200sim9600 bps and wireless encoding uses a way of Bi-phase Manchester code Communication between notebookcomputer and wireless modem uses RS232C Figure 6 showsthe data transmitter and receiver using RF communicationFor remote medical treatment the transmitter acquires data

Figure 7 Transmitreceive system for ubiquitous network

Figure 8 Analysis of electro stimulation to fingertips

Figure 9 Output of electronic acupuncture needle time simulationusing FIS matlab

from 4 sensors and then transmit the data to receiver usingRF communication

In Figure 7 the system consists of transmit andreceive system parts for ubiquitous network It is madeof MSP240CPU and CC2420 RF chip Figure 8 showsanalysis of electro stimulation to fingertips using padsTo obtain signal we send a reference signal to palm andthen decide body condition of patients on the basis of dataobtained from pre-investigation using sensing pads andMCU attached to fingertips As soon as signal processingis completed electric stimulation signal generated by fuzzyalgorithm is transmitted to sensing pads

Table 1 explains fuzzy inference of a variety of patientswith the same disease according to varying blood pressurecondition Heart rate condition and vascular aging condi-tion In other words Table 1 clearly shows that the systemcalculate varying time of acupuncture for different patientsphysical conditions

Figure 9 shows the Output of electronic acupunctureneedle time simulation using Fuzzy Inference SystemMatlabIt explains how the system calculates the output condition


Table 1 Electronic acupuncture needle time simulation

Patient biometric information Optimal acupuncture needle timeInput data (minutes)

Blood pressure condition Heart rate condition Vascular aging condition Conventional IntelligenceMedium Medium Small 10 12Big Big Big 10 06Big Big Medium 10 08Medium Medium Medium 10 11Medium Big Big 10 07Medium Medium Small 10 10Small Big Big 10 07Small Medium Big 10 06Small Small Small 10 05

of the time for acupuncture from the input data of the 3conditions of patient physical conditions

5 Conclusion

In this paper we implemented intelligent electronic acupunc-ture system using sensor modules We used the sensormodules to obtain a patientrsquos diagnosis signals These sensormodules consist of 5 parts These sensor modules detect andanalyze the abnormal signals from human bodyWe analyzedthe signals to make instructions for the treatment And thenwedesigned the sensing pads for electronic acupuncture Andwe also developed adaptive wireless acupuncture system toadjust strength and time of acupuncture and several acupunc-ture points of patients by using fuzzy technology We madethe sensing pads the circuit of AMP and acupuncture signalWe implemented efficient electronic acupuncture system toget acupuncture easily using intelligent diagnosis systemThe intelligent acupuncture system proposed in this paperis simple inexpensive and safe compared with conventionalacupuncture systems

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITSWCreative research program supervised by the NIPA (NationalIT Industry Promotion Agency)rdquo (NIPA-2013-H0502-13-1112)

References

[1] Y S Hong H K Kim and B K Kim ldquoImplementation of adap-tive electronic acupuncture system using intelligent diagnosissystemrdquo International Journal of Control and Automation vol5 no 3 pp 141ndashl52 2012

[2] H K Baruah ldquoThe theory of fuzzy sets beliefs and realitiesrdquoInternational Journal of Energy Information and Communica-tions vol 2 no 2 pp 1ndash22 2011

[3] J Jeong ldquoThe development of web-based decision tree programfor the analysis of clinical information ideas constitutionrdquoKorea Institute of Oriental Medicine vol 12 pp 81ndash87 2008

[4] Y J Lee J Lee H J Lee H H Yoo E J Choi and J Y KimldquoStudy on the characteristics of blood vessel pulse area usingultrasonicrdquo Korea Institute of Oriental Medicine Researches vol13 no 3 pp 111ndash119 2007

[5] P A Shaltis A T Reisner and H H Asada ldquoCuffless bloodpressure monitoring using hydrostatic pressure changesrdquo IEEETransactions on Biomedical Engineering vol 55 pp 1775ndash17772008

[6] National College of Oriental MedicineDiagnostics Saint Func-tionality of Medicine St Functional Medicine 2008 GunjaPublisher 2007

[7] Department of Medical Sciences College of Oriental MedicineKyung Hee University ldquoMedical practice materialsrdquo 2007

[8] O P Verma and S Singh ldquoA fuzzy impulse noise filter based onboundary discriminative noise detectionrdquo Journal of Informa-tion Processing System vol 9 no 1 2013

[9] S-S Lee M-C An and S-H Ahn ldquoA new measurementmethod of a radial pulse wave usingmultiple hall array devicesrdquoJournal of Magnetics vol 14 no 3 pp 132ndash136 2009

[10] S Haykin Modem Wireless Communication Prentice-Hall2003

[11] A Swami andH YaWireless Sensor Networks Signal Processingand Communications John Wiley amp Sons 2007

[12] J K-Y Ng ldquoUbiquitous healthcare healthcare systems andapplications enabled by mobile and wirelessrdquo Journal of Con-vergence vol 3 no 2 2012

[13] A Sinha and D K Lobiyal ldquoPerformance evaluation of dataaggregation for cluster-based wireless sensor networkrdquoHuman-Centric Computing and Information Sciences vol 3 article 132013

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Active and Passive Electronic Components

Control Scienceand Engineering

Journal of



RotatingMachinery


Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design



Shock and Vibration


Civil EngineeringAdvances in

Acoustics and VibrationAdvances in



Electrical and Computer Engineering

Journal of

Advances inOptoElectronics


Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of


Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014


Chemical EngineeringInternational Journal of Antennas and

Propagation




Navigation and Observation



DistributedSensor Networks



Body signal parts

∙ Blood pressure sensing

∙ Skin conductivity sensing

∙ ECG signal sensing

∙ Oxygen saturation signal sensing

∙ Body temperature sensing

Signal analyzing and treatment system

∙ Electronic acupuncture part

Monitoring and DB generating

Figure 1 Whole system diagram of the intelligent electronic acupuncture system

consider the basic and quantitative analysis of the pulse inorder tomake an accurate diagnosis Also the doctors shouldconsider physical characteristics such as the thickness ofthe skin and blood vessels in order to reach an accurateconclusion Therefore measurement of the blood flow rate isa vital indicator in understanding the blood pressure rate andhow the substances in the blood are transported [4ndash6]

The method of exiting diagnosis has a problem whichcannot diagnose the old and the infirm exactly because thepatientrsquos condition including gender age skin is not takeninto consideration To solve this problem we analyzed thefine distinction considering thickness of skin and blood ves-sels and pulse whether they are big or small strong or weakand fast or slow We proposed the algorithm that diagnosesthe condition of a patient optimally using intelligent fuzzytechnique [7 8]

Adaptive wireless acupuncture system was developedin this paper by using pulse diagnosis system to adjuststrength and time of acupuncture and several acupuncturepoints of patients to whom intellectual fuzzy technology is

applied Conventional electronic acupuncture cannot findthe acupuncture points at once However SW which canstimulate multiple acupuncture points and calculate thetime of the electronic acupuncture was developed in thispaper Conventional electronic acupuncture only stimulatesthe acupuncture point but the electronic acupuncture withKIT (SW + HW) developed in this paper made remote orself-diagnosis possible using the conditions of the patientsand disease reasoning function Doctorsrsquo help is neededto find the acupuncture point with conventional electronicacupuncture Intelligent electronic acupuncture that easilycalculates optimal acupuncture time considering the patientsrsquohealth condition with smart phones was developed in thispaper

Figure 1 shows thewhole systemdiagramof the intelligentelectronic acupuncture system It consists of 4 parts The firstpart is a sensor module the second part is a main part whichanalyzes the transferred signals and generates the treatmentsignalsThe third part is an electronic acupuncture partwhichapplies electronic acupuncture according to treatment signals











of human body





Input 119909 is 1198601015840 AND 119910 is 1198611015840




120573

119888= 120573comb (120573119888 120573

old119888) = max (120573

119888 120573

old119888) (1)

Here 120573old119888









Pulse sensor


ECG sensor

Hmote 2420



Bloodpressure

Bloodpressure

sensor

REF

PGAAMP AD

CC2430

USB to serial

BAT and DCDC

15

PGAAMP CC2430

USB to serial

BAT and DCDC

13

EGC3

Notchfilter AD

CC2430

USB to serial

BAT and DCDC

EGC2

EGC1

11

Photodiode

AMPLED

AD

DA

PGAAMP PIC18F85

USB to serial

BAT and DCDC

1

2

30

AD

MOSFET

TRarray

TFTLCD

UART

SD slop

DCDC

SSPV210(cortex-A8)

SDRAM

Nand flash

CPLDdecoder


20

ZigBee

Ethernet

WiFi

Bluetooth 20

20

16bit

24bit24bit

10M

512MB

256MB

2G







Hmoto2420 sender

Hmoto2420 sender

Hmoto2420 sender


Hmoto2420 receiver

Hmoto2420 receiver

Hmoto2420 receiver


0 times 05


Group ID 0 times 03



2405Mhz2410Mhz

2415Mhz


PWM-2

TX

B_DIR-2

A_DIR-2B_DIR-1

A_DIR-1


RX

A_DIR-1A_DIR-2PWM-1

LOAD

PWM-1

Load

C11104

C15104

C16 C17104

U3MAX232

1381110

134526

129147

1615

R1INR2INT1INT2IN

C+

C2+

V+


VCC

GN

D

+

C4

+

C8

+

C5

+C10

R1220

Q1C1011

23

R8

R5 R7

R3

R6

+

U52

36

81

C13104

C18104

C12104

C14104

LS1Buzzer

+

+C3

U1AT89C2051

1

10

1213141516171819

20

23678911

54

RSTVPP

GN

D

P10AIN0P11AIN1

P12P13P14P15P16P17


XTAL1XTAL2

R4

D1 1N4007

C718P(CH) +

C9

R2

C618P(CH)

C2104

X-TAL1

U232

1

VINVOUT

AD

J

C1 104

U4

L6203

4

5

3

8

1

6

2

9

711

10

+VIN

+BOOST

+CURLIM

+SENSE

REF

LIM

DIM

D2

1N4148

GND

Output module-CH1

C1minus

C2minus

Vminus

Data A

Data B

10uf25V

10uf25V

10uf25V

10uf25V

10uf25V

+5V

+5V

+5V

+5V

+5V

110592m

82K

minus

minus

1 uF16 V

22uF16V

minusVINminusBOOST

minusCURLIM

minusVOUT

1K

1K

2K

10K 20K

20K

Output CH1

Output CH1

VCC

VCC

VCC























5 Conclusion




Acknowledgment


References
















RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation



















of human body





Input 119909 is 1198601015840 AND 119910 is 1198611015840




120573

119888= 120573comb (120573119888 120573

old119888) = max (120573

119888 120573

old119888) (1)

Here 120573old119888









Pulse sensor


ECG sensor

Hmote 2420



Bloodpressure

Bloodpressure

sensor

REF

PGAAMP AD

CC2430

USB to serial

BAT and DCDC

15

PGAAMP CC2430

USB to serial

BAT and DCDC

13

EGC3

Notchfilter AD

CC2430

USB to serial

BAT and DCDC

EGC2

EGC1

11

Photodiode

AMPLED

AD

DA

PGAAMP PIC18F85

USB to serial

BAT and DCDC

1

2

30

AD

MOSFET

TRarray

TFTLCD

UART

SD slop

DCDC

SSPV210(cortex-A8)

SDRAM

Nand flash

CPLDdecoder


20

ZigBee

Ethernet

WiFi

Bluetooth 20

20

16bit

24bit24bit

10M

512MB

256MB

2G







Hmoto2420 sender

Hmoto2420 sender

Hmoto2420 sender


Hmoto2420 receiver

Hmoto2420 receiver

Hmoto2420 receiver


0 times 05


Group ID 0 times 03



2405Mhz2410Mhz

2415Mhz


PWM-2

TX

B_DIR-2

A_DIR-2B_DIR-1

A_DIR-1


RX

A_DIR-1A_DIR-2PWM-1

LOAD

PWM-1

Load

C11104

C15104

C16 C17104

U3MAX232

1381110

134526

129147

1615

R1INR2INT1INT2IN

C+

C2+

V+


VCC

GN

D

+

C4

+

C8

+

C5

+C10

R1220

Q1C1011

23

R8

R5 R7

R3

R6

+

U52

36

81

C13104

C18104

C12104

C14104

LS1Buzzer

+

+C3

U1AT89C2051

1

10

1213141516171819

20

23678911

54

RSTVPP

GN

D

P10AIN0P11AIN1

P12P13P14P15P16P17


XTAL1XTAL2

R4

D1 1N4007

C718P(CH) +

C9

R2

C618P(CH)

C2104

X-TAL1

U232

1

VINVOUT

AD

J

C1 104

U4

L6203

4

5

3

8

1

6

2

9

711

10

+VIN

+BOOST

+CURLIM

+SENSE

REF

LIM

DIM

D2

1N4148

GND

Output module-CH1

C1minus

C2minus

Vminus

Data A

Data B

10uf25V

10uf25V

10uf25V

10uf25V

10uf25V

+5V

+5V

+5V

+5V

+5V

110592m

82K

minus

minus

1 uF16 V

22uF16V

minusVINminusBOOST

minusCURLIM

minusVOUT

1K

1K

2K

10K 20K

20K

Output CH1

Output CH1

VCC

VCC

VCC























5 Conclusion




Acknowledgment


References
















RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










Pulse sensor


ECG sensor

Hmote 2420



Bloodpressure

Bloodpressure

sensor

REF

PGAAMP AD

CC2430

USB to serial

BAT and DCDC

15

PGAAMP CC2430

USB to serial

BAT and DCDC

13

EGC3

Notchfilter AD

CC2430

USB to serial

BAT and DCDC

EGC2

EGC1

11

Photodiode

AMPLED

AD

DA

PGAAMP PIC18F85

USB to serial

BAT and DCDC

1

2

30

AD

MOSFET

TRarray

TFTLCD

UART

SD slop

DCDC

SSPV210(cortex-A8)

SDRAM

Nand flash

CPLDdecoder


20

ZigBee

Ethernet

WiFi

Bluetooth 20

20

16bit

24bit24bit

10M

512MB

256MB

2G







Hmoto2420 sender

Hmoto2420 sender

Hmoto2420 sender


Hmoto2420 receiver

Hmoto2420 receiver

Hmoto2420 receiver


0 times 05


Group ID 0 times 03



2405Mhz2410Mhz

2415Mhz


PWM-2

TX

B_DIR-2

A_DIR-2B_DIR-1

A_DIR-1


RX

A_DIR-1A_DIR-2PWM-1

LOAD

PWM-1

Load

C11104

C15104

C16 C17104

U3MAX232

1381110

134526

129147

1615

R1INR2INT1INT2IN

C+

C2+

V+


VCC

GN

D

+

C4

+

C8

+

C5

+C10

R1220

Q1C1011

23

R8

R5 R7

R3

R6

+

U52

36

81

C13104

C18104

C12104

C14104

LS1Buzzer

+

+C3

U1AT89C2051

1

10

1213141516171819

20

23678911

54

RSTVPP

GN

D

P10AIN0P11AIN1

P12P13P14P15P16P17


XTAL1XTAL2

R4

D1 1N4007

C718P(CH) +

C9

R2

C618P(CH)

C2104

X-TAL1

U232

1

VINVOUT

AD

J

C1 104

U4

L6203

4

5

3

8

1

6

2

9

711

10

+VIN

+BOOST

+CURLIM

+SENSE

REF

LIM

DIM

D2

1N4148

GND

Output module-CH1

C1minus

C2minus

Vminus

Data A

Data B

10uf25V

10uf25V

10uf25V

10uf25V

10uf25V

+5V

+5V

+5V

+5V

+5V

110592m

82K

minus

minus

1 uF16 V

22uF16V

minusVINminusBOOST

minusCURLIM

minusVOUT

1K

1K

2K

10K 20K

20K

Output CH1

Output CH1

VCC

VCC

VCC























5 Conclusion




Acknowledgment


References
















RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation











Hmoto2420 sender

Hmoto2420 sender

Hmoto2420 sender


Hmoto2420 receiver

Hmoto2420 receiver

Hmoto2420 receiver


0 times 05


Group ID 0 times 03



2405Mhz2410Mhz

2415Mhz


PWM-2

TX

B_DIR-2

A_DIR-2B_DIR-1

A_DIR-1


RX

A_DIR-1A_DIR-2PWM-1

LOAD

PWM-1

Load

C11104

C15104

C16 C17104

U3MAX232

1381110

134526

129147

1615

R1INR2INT1INT2IN

C+

C2+

V+


VCC

GN

D

+

C4

+

C8

+

C5

+C10

R1220

Q1C1011

23

R8

R5 R7

R3

R6

+

U52

36

81

C13104

C18104

C12104

C14104

LS1Buzzer

+

+C3

U1AT89C2051

1

10

1213141516171819

20

23678911

54

RSTVPP

GN

D

P10AIN0P11AIN1

P12P13P14P15P16P17


XTAL1XTAL2

R4

D1 1N4007

C718P(CH) +

C9

R2

C618P(CH)

C2104

X-TAL1

U232

1

VINVOUT

AD

J

C1 104

U4

L6203

4

5

3

8

1

6

2

9

711

10

+VIN

+BOOST

+CURLIM

+SENSE

REF

LIM

DIM

D2

1N4148

GND

Output module-CH1

C1minus

C2minus

Vminus

Data A

Data B

10uf25V

10uf25V

10uf25V

10uf25V

10uf25V

+5V

+5V

+5V

+5V

+5V

110592m

82K

minus

minus

1 uF16 V

22uF16V

minusVINminusBOOST

minusCURLIM

minusVOUT

1K

1K

2K

10K 20K

20K

Output CH1

Output CH1

VCC

VCC

VCC























5 Conclusion




Acknowledgment


References
















RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation


























5 Conclusion




Acknowledgment


References
















RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation











RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation









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