M00196

整合式居家健康管理平台

INTEGRATED IN-HOUSE HEALTH MANAGEMENT

PLATFORM

沙丹尼 鍾文耀 蔡育秀

Daniel Santoso1, Wen-Yaw Chung1, and Yuh-Show Tsai2

1_{中原大學電子工程學系}

1_{Department of Electronic Engineering, Chung-Yuan Christian University, Chung-Li, Taiwan, R.O.C. 32023}

2_{中原大學生物醫學工程學系}

2

Department of Biomedical Engineering, Chung-Yuan Christian University, Chung-Li, Taiwan, R.O.C. 32023

Abstract

This paper introduces an integration platform based on 8051 compatible microcontroller which can accommodate body parameters measurement and has wireless communication module based on CC2500 to transmit the measurement results to a PC. The transmitted data is then stored in a database system. Using certain protocol, the data is further analyzed to yield health advices to keep subject’s body in fit condition. The body parameters cover body weight, body height, total body water, body fat, and muscle mass. The first two items will be utilized to derive Body Mass Index (BMI). The last three items are estimated based on the Bioelectrical Impedance Analysis (BIA). In addition, the system also equipped with fingerprint module to facilitate automatic personal recognition. Preliminary prototype has been developed and the performance has been evaluated.

Keywords: Integrated home care, BMI, BIA, Wireless, Microcontroller

INTRODUCTION

The system is actually one of the implementation of Distributed Diagnosis and Home Healthcare (D2H2) paradigm. D2H2 is a new healthcare delivery

paradigm where electronic health information systems, smart software, ubiquitous computing and communications and affordable, easy-to-use, portable devices enable patients to take a more central role in their healthcare management [1].

Senior citizens like the rest of society are becoming heavier. Between 1982 and 1999 obesity among senior citizens doubled. Obesity can be defined as a disease in which excess body fat has accumulated such that health maybe adversely affected [2]. Regardless of its cause, obesity may be associated with a variety of risks. In particular, obesity is associated with the development of type-II diabetes mellitus or non-insulin dependent diabetes mellitus (NIDDM), coronary heart disease [CHD], respiratory complications, dyslipidaemia, gout,

osteoarthritis of large and small joints, sleep apnea and other degenerative conditions associated with higher mortality [3]. Obesity has been implicated as a risk factor in the development of hypertension [HT] [3]. It is also associated with an increased incidence of certain forms of cancer [3].

In recent years, the BMI has become the medical standard used to measure overweight and obesity. BMI can be considered to provide the most useful, albeit crude, population-level measure of obesity. In cross-sectional comparisons, BMI does not directly measure percent of body fat, as a result some people such as athletes who are muscular have a high BMI, due to muscle weighing more than fat, and will have BMI within the overweight range, even though they are not fat. Therefore, the system also furnished with BIA which allows the determination the percentage of total body water, body muscle, and ultimately the body fat. Based on the assessment result composition, the system can generate a brief advice to the subject to bring his/her health status to ideal condition.

DESIGN CONSIDERATION

System overview

Fig. 1 Overall block diagram

The second block, home gateway is simpler than its counterpart. It consists of two parts, the PC and wireless module along with the microcontroller. The microcontroller is required to bridge wireless communication module and PC since normally PC is not equipped with Serial Peripheral Interface (SPI). The primary database along with the printed advice generator program resides in this block.

The system is designed to be independent each other, means if somehow the connection to the home gateway cannot be established, the stand-alone block remains fully functional. The general flowchart for the system on operational mode is illustrated in illustrated in figure 2.

Fingerprint verification

Recognized?

Display the user ID and age

Y

N Weight & Height Measurement

Measurements in progress

Display the user ID, measurement

results, advices

Turn off automatically update

Connected?

Memory status?

Store in the internal memory Notify the

user

Purge the oldest data, replace with recent data Available

Y

N

Near full Full

Display the Weight & Height results

Weight Height Body Fat Total Body Water Body Muscle Identity Timestamp

Fig. 2 General system flowchart

A user who wants to perform a complete assessment is required to register his/her fingerprint and birthday on the stand-alone system. The system is then assign a number as a unique ID. The fingerprint is required to enable the automatic personal recognition feature while the birthday is

used to calculate the subject’s age. The user registration is further can be completed on the home gateway PC by preserving the ID obtained from the stand-alone system.

Weight and height scale

Integration of weight and height scale offers great advantage since weight and height are the most simple and commonly used measures. A number of weight-of-height indices have been developed of which the BMI (defined as kg/m2) is the most commonly used measure of overall obesity. Figure 3 illustrates the side view of the platform.

D

H L

Fig. 3 Weight and height scale platform

The weight scale is built based on the widely known principle yet effective, strain gages array. A strain gage is a conducting wire whose resistance changes by small amount when it is lengthened or shortened. The strain gage is bonded to a structure (load cell) so that the percent change in length and structure are identical. There are four identical load cells bonded at each corner of bottom side of measurement board, illustrated in figure 4.

This kind of arrangement is commonly known as half bridge temperature-compensated network. It grants more sensitivity due to load, less sensitivity due to temperature. The weight force applied to the board surface changes the resistance in working gages. This resistance change then causes the voltage shift between node S+ and S- which can be expressed in equation 1.

2

2

R

R

S

S

E

E

R

R

R

+

₋

−

₌

Δ

_{• ≈}

Δ

_•

+ Δ

… ……Eq.1

The potential variation due to weight force is further processed using ADC and become a digital word that is intelligible for microprocessor. The weight scale has maximum capacity of 150 kg with 100 gram resolution.

The height scale is built based on reflection of sound wave. If the speed of sound in the medium is known and the time taken for the sound wave to travel the distance from the source to the subject and back to the source is measured, the distance from the source to the subject can be computed accurately. Here the medium for sound wave is air, and the sound wave is ultrasonic. Assuming that the speed of sound in air is C m/s and the measured time taken for the sound wave to travel the distance from the source to the subject and back to the source is Δt seconds, the distance D is computed by formula D = C x Δt meter. Since the sound wave travels twice the distance between the source and the subject, the actual distance between the source and the subject will be D/2. It is obvious from figure 3 that the ultrasonic transceiver module as a source is fitted at a certain height above the subject’s head so that the subject’s body height (H) is equal to L – (D/2). L is platform’s height, designed to be 2.5 m from weight measurement surface.

Bioelectrical impedance analysis

Body offers two types of resistance (R) to an electrical current: capacitive R (reactance) and resistive R (resistance). The capacitance arises from cell membranes and the R from extra- and intra-cellular fluid. Impedance is the term used to describe the combination of two. A circuit that is commonly used to represent biological tissues in vivo is one in which the R of extra-cellular fluid is arranged in parallel to the second arm of the circuit, which consists of capacitance and R of intra-cellular fluid in series. This model is known as Fricke’s circuit [4], as illustrated in figure 5.

At low frequency, the current does not penetrate the cell membrane, which acts as an insulator and therefore the current passes through the extra-cellular fluid. At high frequency the capacitor

behaves as near perfect conductor and therefore the total body R reflects the combined of both intra-cellular and extra-cellular fluid.

Fig. 5 Load cells arrangement and placement

The constant current (i) is injected through the electrode pads under the front of each foot and the voltage (v) measured by the electrodes under the heel. The impedance is then calculated from v over i. By using certain BIA equations, the calculated impedance is further interpreted to percentage of body fat, total body water, and body muscle.

In summary, the BIA instrument in this system is categorized as non-invasive, multi-frequency, tetra-polar. The low frequency is tuned at 5 kHz while the high frequency is tuned at 50 kHz. The injected current is set to 0.035 mA RMS. The physical measured impedance can have range from 300 – 600 Ω.

Fingerprint recognition and wireless module

Fingerprint recognition refers to the automated method of verifying a match between two human fingerprints. This method is chosen because it is reliable, cost effective, and widely used for personal identification. This module provides automatic personal identification feature so that the system become more convenient to be used.

The fingerprint recognition is achieved by utilizing LTT-ASM, Area sensor Stand Alone Module, product of LighTuning Tech. Inc. The product offers complete solution since it has incorporated sensor, ADC, and Digital Signal Processor (DSP) in single module. The sensor is categorized as capacitive, area sensor type. This kind of sensor eliminates the need for clean, undamaged epidermal skin and a clean sensing surface. Figure 6 shows this fingerprint recognition module.

At least 50 templates can be stored directly in the module’s internal flash memory. This sub-system is integrated to the host microcontroller through RS-232 interface with simple protocol.

In order to establish wireless communication between stand-alone system and home gateway, the CC2500 RF transceiver chip is chosen as a solution. The CC2500 is a low cost true single chip 2.4 GHz transceiver designed for very low wireless applications. The circuit is intended for the ISM (Industrial, Scientific, and Medical) and SRD (Short Range Device) frequency band at 2400 – 2483.5 MHz [6]. It supports a configurable data rate up to 500 kbps. The device boasts of its low current consumption at 13.3 mA.

The CC2500 is configured via a simple 4-wire SPI compatible interface. This interface is also used to read and write buffered data. GDO2 is configured as a flag to notify the microcontroller whenever one data packet is completely transmitted / received. The connection diagram is shown in figure 7.

Fig. 7 Microcontroller and transceiver chip connection

The SPI speed is configured at 86.4 kHz. The packet is transmitted wirelessly at 2433 MHz frequency using MSK (Minimum Shift Keying) modulation, with data rate 250 kbps.

RESULTS AND DISCUSSION

The preliminary prototype of this health station has been built and tested. The prototype has integrated weight scale and BIA device. The raw measurement data is then transmitted wirelessly to the home gateway to be processed using certain formula (not covered in this paper) to yield human readable weight reading (kg) and BIA reading (%).

For BIA device, the input for height, age, weight, and gender is still performed manually to maintain the flexibility of experimentation since the improvement is ongoing.

There are two hardware modules are awaiting to be integrated, height scale and fingerprint recognition. Those modules are already fully functional and tested. Figure 8 shows graphical user interface (GUI) developed for home gateway. The GUI is still for the experimentation purpose, not the final version.

Fig. 8 Graphical user interface on home gateway

CONCLUSION

The Health Station for Home Use has been partially developed and implemented, but the results are not yet accurately verified. The successful data reception on home gateway and plausible reading has given a significant encouragement that the overall system can be completed this year.

Nevertheless, the designer is also aware of the problems that might be encountered during the completion of project. The first problem concerns the BIA device. It’s quite difficult to develop device that accurately estimates body composition since recently the BIA research still lacking of standard. The second problem is the system complexity is rather high and integrates various measurements, yet the resources are limited. Therefore, extra caution is necessitated in design efficiency and effectiveness.

REFERENCES

[1] C.C. White, D. Fang, E.H. Kim, W.B. Lober, and Y.Kim, (2006) “Improving Healthcare Quality Through Distributed Diagnosis and Home Healthcare (D2H2),” 1st D2H2 Conference, pp.

168-172.

[2] P.G. Kopelman (2000), “Obesity as a medical problem,” Nature, 404:635-643.

[3] A. Mukhopadhyay, M. Badra, and K. Bose (2005), “Human obesity : a background,” Human Ecology Special Issue, 13:1-9.

[4] U.G. Kyle, I. Bosaeus, A.D. De Lorenzo, P. Deurenberg, M. Elia, J.M. Gomez, B.L. Heitmann, L.K. Smith, J.C. Melchior, M. Pirlich, H. Scharfetter, A.M.W.J. Schols, C. Pichard (2004), “Bioelectrical impedance analysis – part I : review of principles and methods,” Clinical Nutrition, 23:1226-1243. [5] LTT-ASM Area sensor Stand-alone Module Datasheet, 2005.