a mobile care system with alert mechanism · taiwan, r.o.c. (e-mail: [email protected]). c.-l....

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TITB-00046-2006.R2 (October 10, 2006)

Copyright © 2006 IEEE. Personal use of this material is permitted.

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Abstract—Hypertension and arrhythmia are chronic diseases

which can be effectively prevented and controlled only if the physiological parameters of the patient are constantly monitored, and the health education and professional medicine care is fully supported. In this paper a role-based intelligent mobile care system with alert mechanism in chronic care environment is proposed and implemented. The roles in our system include patients, physicians, nurses, and health care providers. Each of the roles represents a person that uses a mobile device such as a mobile phone to communicate with the server set up in the care center so that he or she can go around without restrictions.

For commercial mobile phones with Bluetooth communication capability attached on chronic patients, we have developed physiological signal recognition algorithms that were implemented and built-in in the mobile phone without affecting its original communication functions. It is thus possible to integrate several front-end mobile care devices with Bluetooth communication capability to extract patients’ various physiological parameters (such as blood pressure, pulse, SpO2 and ECG), to monitor multiple physiological signals without space limit, and to upload important or abnormal physiological information to health care center for storage and analysis or transmit the information to physicians and health care providers for further processing. Thus the physiological signal extraction devices only have to deal with signal extraction and wireless transmission. Since they don’t have to do signal processing, their form factor can be further reduced to reach the goal of microminiaturization and power saving.

An alert management mechanism has been included in back-end health care center to initiate various strategies for automatic emergency alerts after receiving emergency messages or after automatically recognizing emergency messages. Within the time intervals in system setting according to medical history of a specific patient, our prototype system can inform various health care providers in sequence to provide health care service with their reply to ensure the accuracy of alert information and the completeness of early warning notification to further improve the health care quality. In the end, with the testing results and performance evaluation of our implemented system prototype, we conclude that it is possible to set up a complete intelligent health

Manuscript received April 8, 2006; revised August 18, 2006 and October 5,

2006. This work was supported by the National Science Council of the Republic of China, Taiwan, under Contract NSC94-2627-E-002-001 and NSC94-2213-E-027-012.

R.-G. Lee is the corresponding author of this paper. He is with the Department of Electronic Engineering, National Taipei University of Technology, Taipei 10643, Taiwan, R.O.C. (e-mail: [email protected]).

K.-C. Chen is a Ph.D. candidate at the Graduate Institute of Computer and Communication Engineering, National Taipei University of Technology, Taipei 10643, Taiwan, R.O.C.

C.-C. Hsiao is with the Department of Computer Information and Network Engineering, Lunghwa University of Science and Technology, Taoyuan 33306, Taiwan, R.O.C. (e-mail: [email protected]).

C.-L. Tseng is with the Department of Electrical Engineering, National Taipei University of Technology, Taipei 10643, Taiwan, R.O.C. (e-mail: [email protected]).

care chain with mobile monitoring and health care service via the assistance of our system.

Index Terms—Mobile care, mobile phone, Bluetooth, alert, ubiquitous, JAVA programming.

I. INTRODUCTION N RECENT years, health care for elderly people has been an important research topic. The commonly seen chronic

diseases for elderly people include hypertension and arrhythmia. The current health care for such diseases are still mainly in form of outpatient services. Due to the development of information and communication technology (ICT), the feasibility of home tele-care has been highly raised. In the literature, the tele-care services were first provided by utilizing traditional public switched telephone network (PSTN). Lee et al. used cable television (CATV) network to transmit electrocardiogram (ECG) data to health care center and to provide function of video conversation between health care providers and patients [1]. Because of the fast development and popularity of Internet, the tele-care medical applications to provide long-term monitoring and health care by transmitting personal physiological information via Internet have become highly feasible [2]. Guillén et al. have proposed a telehomecare multimedia platform utilizing videoconferencing standards H.320 and H.323, and standard TV set based on integrated services digital network (ISDN) and Internet protocol to let patients upload their physiological information to health care center and to provide home tele-care services such as tele-consultations [3]. Besides, to provide a safer and more comfortable inpatient and resident health care environment and to achieve the purpose of illness prevention, it has been another trend for development of home tele-care system to integrate various miniature flexible noninvasive biosignal sensors inside patients’ clothing for ease of everyday dressing and for long- term monitoring and vital signs extraction of the patients [4].

However, the above-mentioned health care systems have restricted the activity area of patients to be within medical health care institute or within residence area. To provide more freedom to patients, it is important to integrate wireless communication technology for modern health care systems [5]–[11]. Lin et al. [5] have utilized personal digital assistant (PDA) to monitor and collect the physiological parameters extracted by physiological signal module attached on patients. The physiological information is then immediately transmitted to a remote central management unit for analysis by medical personnel via wireless local area network (WLAN). Home

A Mobile Care System With Alert Mechanism Ren-Guey Lee, Member, IEEE, Kuei-Chien Chen, Chun-Chieh Hsiao, and Chwan-Lu Tseng

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tele-care service has been further extended to become mobile care service [6]–[11] due to the ubiquity of global system for mobile communications (GSM) and general packet radio service (GPRS). Anliker et al. [6] have proposed a wearable multiparameter medical monitoring and alert system AMON (Advanced care and alert portable telemedical MONitor). In their system front-end wrist-worn monitoring device is connected to back-end telemedicine center via GSM mobile network such that health care service to patients is not restricted to specific areas. Rasid and Woodward [7] designed a Bluetooth telemedicine processor to first process extracted physiological signal and then transmit the processed physiological information wirelessly to a Bluetooth mobile phone which then uploads the physiological information to back-end medical health care institute via GPRS mobile network. It has also been broadly applied to design of health care system to utilize GSM/GPRS mobile network to provide health care service with functions of emergency alerts and early warning messages [6], [8]–[11]. All of the above-mentioned GSM/GPRS communication parts are designed and implemented by using commercial modules such that the user-end health care devices are of larger form factor which subsequently reduces the desire of patients to carry the devices and increases the power consumption. Popularity of mobile phones has highly increased recently. For example, in US, the popularity of mobile phones was 70% up to 2005 with expected popularity of 87% in 2010. While in 2002, the popularity of mobile phones in Taiwan was already near 100% [12]. It thus becomes feasible to use commercial mobile phones as platforms for physiological signal processing. Moreover some mobile phones provide Java programming design environment and Bluetooth interface. This can reduce the form factor of user-end physiological signal extraction devices and save power and thus increase the patient’s desire of usage. The health care services of emergency notification messages can also be realized by utilizing the commercial mobile phones’ GSM/GPRS communication capabilities.

Hence this paper proposes to utilize Bluetooth commercial mobile phones as physiological signal processing platforms to construct a ubiquitous mobile care system to increase the feasibility of mobile care services and to increase the desire of users. As described above, this paper focuses on the advantages of mobile devices and utilizes Bluetooth mobile network to integrate multiple front-end physiological parameter extraction devices. It also refers to the alert mechanism of Kafeza et al. [8] to extend to each role of tele-care to construct an intelligent mobile care platform to actively provide health care services to multiple parties of patients and health care providers without spatial and temporal limitations and thus improve the quality of health care.

The rest of the paper is organized as follows. Section II outlines the system analysis and health care scenarios. Section III depicts the system architecture. Section IV describes the design of system software. Section V gives the system implementation results. Overall system performance and

experiments are evaluated and described in Section VI. Finally, Section VII provides some discussions and conclusions based on the implemented mobile care system.

II. SYSTEM ANALYSIS AND HEALTH CARE SCENARIOS Our proposed health care system mainly takes care of chronic

patients who can live normally when the health condition is stable while are in desperate need of help and assistance to reduce the probability of deteriorating health conditions or even death when patients’ physiological conditions become abnormal or when the patients fall ill . Such chronic patients can perform some simple self health care and monitoring functions via mobile phones through our proposed system when health condition is stable. When the patient’s health condition becomes abnormal, the proposed system can automatically inform physicians or health care providers to further provide medical and health care services and can thus effectively reduce the cost of health care.

In general, a health care scenario includes different roles such as patients and various health care providers. Analysis on information exchanged between different roles can induce an alert which can be implemented via short message technology in mobile communication networks [10]. Through implementation of alert mechanism, our mobile health care system provides a general information transmission service to achieve various intelligent health care functions. We use two health care scenarios to demonstrate the function of our proposed system. One is “patients do not upload physiological parameters on schedule” and the other is “the result of measurement is abnormal and our system automatically informs care providers”.

A. Patients Do Not Upload Physiological Parameters on Schedule In the first health care scenario, the subject is a patient with

hypertension or with cardiac diseases. The patient falls asleep at noon. In this health care process, the alert message transmission process of the alert system is as shown in Fig. 1(a) and is described as follows.

1) The patient does not upload blood pressure/ECG data on schedule.

2) The care center automatically sends an urgent alert to notify the patient.

3) The patient does not receive the alert or does not reply to it for some reason.

4) The care center raises the urgency level of the alert and resends the alert to notify the health care provider.

5) The health care provider goes to the location of the patient to provide necessary health care services.

6) The health care provider replies with the result of alert processing.

B. Result of Measurement Is Abnormal and Our System Automatically Informs Care Providers

Take the chronic patient with hypertension as an example. Wherever the patient goes, he or she will carry a mobile phone


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and a Bluetooth hemadynamometer. When the patient’s condition is not good, he or she will feel uncomfortable, for example he or she might have a headache or feel dizzy. In this health care process, the alert message transmission process of alert system is as shown in Fig. 1(b). The process of health care giving is described as follows. 1) The blood pressure of a hypertension patient increases for

some reason and causes headache and dizziness. 2) The Bluetooth hemadynamometer measures the

physiological parameters such as blood pressure and pulse rate and then transmits the data to the mobile phone wirelessly.

3) The mobile phone uploads the physiological data to the database in health care center server in hospital.

4) If some abnormal conditions are identified by the simple programs run in the mobile phone, the mobile phone can send short messages immediately to the physicians or the other health care providers.

5) If some abnormal conditions are identified by professional judgment via the health care center server, related personnel such as local officers are informed instantly or an ambulance is dispatched immediately to perform necessary rescue in the location of the patient.

III. SYSTEM ARCHITECTURE The system architecture deployment diagram of our proposed

mobile health care platform is as shown in Fig. 2. The whole system architecture mainly consists of front-end personal mobile device and back-end care center server.

The front-end personal mobile device comprises physiological parameter extraction device and mobile phone integration device. The physiological parameter extraction device consists of various physiological parameter extraction devices for blood pressure and pulse and ECG with wireless Bluetooth module. Mobile phone needs to receive and integrate data from various physiological parameter extraction devices and to provide communication link between patients and health care center server. The mobile phone supports JAVA 2 Micro Edition (J2ME) [13] in software and Bluetooth and GSM/GPRS modules in hardware to integrate functions on personal mobile-end. The software includes two major software package modules: blood pressure and pulse monitor module and ECG monitor module. Back-end health care center server consists of a GSM/GPRS module that can transmit and receive short messages, and a care center host. The GSM/GPRS module and personal computer (PC) with Internet connection are used to develop functions needed for health care center server.

Fig. 1. Alert message transmission diagram for (a) not uploading physiological parameters on schedule and (b) automatic notification of abnormal conditions.


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IV. SYSTEM SOFTWARE DESIGNS The software modules in personal mobile phone is analyzed

and designed with an object-oriented method, and represented by using Unified Modeling Language (UML) [14]. The design phases are as follow: requirement analysis, object model design, code implementation for software model, simulator execution, and upload to real mobile phone Nokia 7610 [15] for final test. While for health care center host, Borland C++ Builder 6.0 software is used to develop window application programs. ADO components are used to access ACCESS database and AT Command instruction set is used to control GSM module to transmit and receive short message. The function and design of each software module is introduced as follows.

A. Blood Pressure and Pulse Monitor Software Module Blood pressure and pulse monitor software module provides

a way for mobile phone to utilize Bluetooth wireless connection to integrate with Bluetooth hemadynamometer to control the Bluetooth hemadynamometer to measure and extract blood pressure and pulse. The measurement result can also be displayed directly on the mobile phone and transmit short messages to physicians or other heath care providers to provide proper health care. The use case diagram for this blood pressure and pulse monitor software module is as shown in Fig. 3(a).

The physiological parameter measurement application program of blood pressure and pulse monitor module provides three functions. The first function is to provide a user graphical user interface (GUI) to let the patient operate mobile phones and hemadynamometers easily, and display information such as physiological parameter measurement values and alert notices. The second function is Bluetooth application programming interface (BT API) to let application programs to utilize Bluetooth functions. The last function is short message service

(SMS) API [16] to let application programs transmit and receive short messages containing physiological parameter measurement values and alert notices.

To extract the physiological parameters measured with front-end Bluetooth hemadynamometer, our presented system uses Bluetooth mobile phone with JAVA APIs for Bluetooth Wireless Technology (JABWT) to develop client application program MIDlet [17] to control and use Bluetooth hemadynamometer to realize the physiological parameter extraction function on patient ends. MIDlet utilizes JABWT to control hemadynamometer to accomplish commands such as blood pressure measurement and parameter setting.

The methods for interface DiscoveryListener in javax.bluetooh API have to be implemented in programs to let MIDlet receive RemoteDevice and ServiceRecord found by DiscoveryAgent. Connection address attributes in remote device service records are used to setup connection to utilize services provided by remote devices. Since RFCOMM is provided in Bluetooth hemadynamometer, the API of Javax.microedition.io’s StreamConnection interface can be used to set up connection (btspp://). After the connection has been set up, mobile phone application programs can easily use serial port transmission protocol to communicate with Bluetooth hemadynamometer to transmit control commands and receive physiological parameter measurement data. Finally, the data can be transmitted to physicians or other health care providers with short messages.

B. ECG Monitor Software Module ECG monitor software module utilizes wireless Bluetooth

function to integrate with front-end ECG physiological parameter extraction devices as a mobile health care device for cardiac patients. The use case diagram of ECG monitor software module is as shown in Fig. 3(b).

Fig. 2. System architecture deployment diagram.


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Patients use MIDlets for ECG monitoring to control and extract ECG data from front-end ECG extraction device, to transmit measured ECG data to mobile phones via Bluetooth after segmentation, and to calculate real-time variation of heart rate (HR) according to R point positions automatically computed by using ECG detection techniques. If the calculated variation of HR is lower than the threshold (typically 10%) set by health care providers according to different patients’ conditions, the abnormal ECG data will be transmitted with

multimedia short messages (MMS) via GPRS to physicians, health care providers, or health care center to provide further health care and treatment. The ECG monitor software module provides three major functions: GUI API to display ECG, HR calculated values, and to let patients operate and control ECG extraction devices; BT API to set up Bluetooth connection between the ECG extraction device and the mobile phone; SOCKET API to upload ECG data to the health care center server via Socket connection.

ECG detection techniques in ECG monitor MIDlet application programs utilize “Modified So and Chan” R-wave detection algorithm [18] which needs little computation and is capable of adjusting adaptation detection parameters.

C. Health Care Center Server Program Design The health care center server provides following functions:

alert mechanism setting, role and alert monitoring, and physiological parameter uploading. The use case diagram of health care center server is as shown in Fig. 3(c). The alert mechanism setting function provides managers a GUI to let the managers set the selected monitored roles and set the alert mechanism. Three functions are provided: display results of queries and status of matching; select candidates of monitored roles; edit content of data tables.

Fig. 3. Use case diagrams for (a) blood pressure and pulse monitor software module, (b) ECG monitor software module, and (c) health care center server.

TABLE I STRATEGY TABLE FOR DIFFERENT LEVELS OF URGENCIES

Urgency Level Strategy Normal E-mail Urgent SMS to Patients’ Mobile Phone Critical SMS to Care Providers’ Mobile Phone

Very Critical Ambulance with Approval of Care Provider

TABLE II PRIORITY TABLE FOR THE ROLE OF HEALTH CARE PROVIDERS

Name Priority Kevin 1 Jacky 2 Evans 3


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Role monitoring and alert monitoring functions are the core of the health care center server software [8], [10]. To execute strategy matching module, the strategies to be executed should be set beforehand as shown in Table I. The scenario of health care in Fig. 1(a) can be used to demonstrate the strategies corresponding to different levels in Table I. The urgencies are classified into four levels with corresponding strategies. If urgency level is normal, E-mails will be used for notification. If the urgency level is urgent, short messages will be transmitted to patients’ mobile phones. If urgency level is critical, short messages will be transmitted to patients’ care providers to assist the patients. If the urgency level is very critical, with the approval of care providers, ambulances will be notified to perform emergent rescues. Note that since the physiological information of each patient is different, the system setting such as related parameters of emergency conditions and health care services provided in different layers are set by care providers according to personal condition and medical history of each patient.

Each strategy sets the roles to be notified first and then execute role matching. The role matching first has to define different priorities for each person of the same role as shown in Table II and then transmits messages according to the priority. The current urgency level can be changed by priority urgency module according to the elapsed time. The relationship between urgency level and elapsed time can be formulated as priority urgency level function as follows.

+++<<++++<<+

+<<≤

=

32121

211

1

,,

,,

)(

dtdtdtTtdtdtTCriticalVerydtdtTtdtTCritical

dtTtTUrgentTtNormal

tU (1)

In the priority urgency level function, t, T, dt1, dt2, and dt3 represent the elapsed time after alert is transmitted, the default deadline, the urgent deadline, the critical deadline, and the very critical deadline respectively.

The complete operation procedure of alert mechanism is depicted as follows. To start alert mechanism, the strategy matching module has to be executed first to find adequate

strategy and subsequently notify corresponding roles. The role matching module is then executed to transmit notification messages to different persons according to different priorities in this role. Finally, priority urgency module is executed to change urgency levels according to priority urgency level function after specified deadline. The operation procedure of alert mechanism can then be restarted all over again.

The physiological parameter upload module mainly provides two methods to let mobile-end patients to upload physiological parameters, namely to use Socket to upload and to use SMS to upload. If SMS is used to upload physiological parameters and a proposed acknowledgement (ACK) message format is followed, the alert can be easily replied and the physiological parameters can be easily uploaded using ordinary mobile phones.

V. SYSTEM IMPLEMENTATION The hardware of our prototype system consists of three main

portions: 1) front-end wireless mobile care devices including the Bluetooth hemadynamometer [9] and wireless ECG extraction device [11] that we designed and implemented. The core microcontrollers used in the two devices are Atmel Corp.’s ATmega169V and Texas Instruments (TI) Corp.’s MSP430- F449 respectively. Both devices use NIETZSCHE Corp.’s UB1-1112 as Class-2 Bluetooth communication modules with a maximum communication range of 10 m; 2) a commercial mobile phone, Nokia 7610; 3) a health care center server which is a PC with an Intel Celeron 2.4 GHz CPU, 512 MB random access memory (RAM) and developed under Borland C++ Builder 6.0 windows application programming environment.

The MIDlet application programs in personal mobile phones are first developed on a PC, then executed with a simulator, and finally installed and tested on a mobile phone Nokia 7610 via wired transmission or wireless Bluetooth transmission. The test results of the two software modules in the mobile phone: blood pressure and pulse monitor module and ECG monitor module, and the model of health care center server alert mechanism are described in the following subsections.

Fig. 4. Sequence diagrams of (a) operation procedure and (b) automatic short message transmission for blood pressure and pulse monitor module.


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A. Implementation of Blood Pressure and Pulse Monitor Software Module in the Mobile Phone The sequence diagram of operation procedure for the blood

pressure and pulse monitor module is as shown in Fig. 4(a). After MIDlet application programs start, patients can give

various commands to mobile phones. The patients can use bluetoothDiscovery() command to search for Bluetooth devices within communication area. If a Bluetooth hemadynamometer is found, the patient can use startServiceSearch() command to search for RFCOMM services provided by the Bluetooth hemadynamometer. The patient can then use bloodPressureDetect() command to utilize the found service to set up connection and transmit control commands to Bluetooth hemadynamometer to measure

blood pressure. sendSMS() command can be used to transmit short messages after the physiological parameters have been measured. One sample test result of developed and downloaded application programs in NOKIA 7610 is as shown in Fig. 5. The results of measurement for systolic pressure, diastolic pressure, and pulse are 116, 63, and 75 respectively, and can be transmitted via short messages to physicians’ or health care providers’ mobile phones to provide further health care service.

Beside the function of manual short message transmission to physicians or health care providers after the measurement, functions for automatic short message transmission can also be selected. The thresholds for blood pressure can be set with five levels: too high (Highhigh), high (High), normal (Normal), low (Low), and too low (Lowlow) according to each patient’s condition. The care provider can set the blood pressure threshold level and then store the record. The rest of blood pressure measurement procedure is the same as previously described. The sequence diagram of automatic short message transmission is as shown in Fig. 4(b). The result of automatic judgment via set threshold will trigger the transmission of short messages to health care provider’s mobile phone to display warning messages such as “Diastolic is low!!” warning that the blood pressure of the patient is too low.

B. Implementation of ECG Monitor Software Module in the Mobile Phone The activity diagram of operation procedure for ECG

monitor software module is as shown in Fig. 6. ECG monitor software module utilizes Bluetooth to receive

ECG data [19]. The operation and functioning of Bluetooth connection is the same as blood pressure and pulse software module. After Bluetooth connection is set up, we can start receiving ECG data. Two normal heart beats can be shown in a default display. The sample rate is 360 points/s and each ECG

Fig. 7. Display of simulator execution for ECG monitor module.

Fig. 5. Display of a sample test result of blood pressure and pulse monitor module.

Fig. 6. Activity diagram of operation procedure for ECG monitor software.


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data contains 500 points. The received ECG data is shown on the monitor one after another and at the same time R-wave is detected via R-wave detection algorithm. The HR is then

calculated and displayed on the monitor. The display of execution of ECG monitor module simulator [20] is as shown in Fig. 7.

C. Implementation of Monitor Software Module in Health Care Center Server To execute health care center host software, first the

monitored role has to be selected and the alert deadline has to be set. The software then executes record table query and display the query results in matching status groups on windows. The display of setting for health care center server is as shown in Fig. 8. The activity diagram of operation procedure for role monitor software is as shown in Fig. 9.

After the role monitor is initiated, timers will also be initiated. If the physiological parameters have been uploaded before the timers’ default deadlines, role monitor will continue normally. However if the data has not been uploaded before the deadline, then the alert module will be initiated. After the initiation of the alert module, the role monitor will continue if it has not ended yet or will terminate otherwise. The alert monitor will be initiated after the role monitor module initiates the alert module. Activity diagram of operation procedure for the alert monitor software is as shown in Fig. 10. The alert monitor will first execute strategy matching. Appropriate persons are then found according to the role result of strategy matching. Alert notifications are subsequently transmitted according to each person’s priority. After the transmission of alerts, the system will wait for acknowledgements to the corresponding alerts. If there are no acknowledgements, then the urgency level for the current strategy will be checked to see whether it ends or not. If the urgency level has not ended yet, then the alert will be retransmitted according to priority role matching. If the urgency level of current strategy has ended, then the urgency level will be lifted and strategy matching algorithm will be executed again until any acknowledgement of the alerts has been received.

If short messages are used to upload the data and the proposed short message format is followed to input short

Fig. 9. Activity diagram of operation procedure for role monitor software.

Fig. 10. Activity diagram of operation procedure for alert monitor software.

Fig. 8. Display of setting of health care center server.

Fig. 11. Display of short message data upload to health care center server.


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message, then the display of received short message on health care center server can be as shown in Fig. 11.

VI. SYSTEM PERFORMANCE EVALUATION Since an intelligent mobile health care system with alert

mechanism is constructed in this paper to automatically transmit information to the right persons at the right time in order to achieve the function of intelligent health care, evaluation to the time needed to transmit necessary information must be performed. Besides, the accuracy of extraction and recognition of physiological signal of mobile care devices attached on patients are also tested and evaluated in this section.

A. Evaluation of testing of time delay of alert message passing The alert message produced when the physiological signal of

a patient is abnormal is set by medical personnel in health care center according to the patient’s medical history. The sequence to notify different health care providers to provide the emergency health care the patient needs is also set by the medical personnel according to the health care service levels justified by the health care center.

Take the health care scenario in Fig. 12 as an example. Assume that there are three health care providers to provide health care services in different levels for some chronic patient. The time analysis of alert message transmission can be performed in two cases: the best case and the worst case. The best case (tbest) is that the patient does not upload data on schedule however after the health care center automatically notifies the patient by using alert the patient acknowledges and uploads physiological parameters right away. The formula for time calculation is as follows.

( ) ( )smslatencyurgentpbestsmslatencyp TTTtTT ×++<<×+ 22 (2)

where Tp is the system execution time, Turgent is the alert interval of the emergency alert, and Tsmslatency is the average delay to transmit short messages.

The worst case (tworst) takes place when the number of health care providers to provide different emergency health care services (n = 3) as shown in Fig. 12. That is, the health care center transmit alerts according to the priority to notify the patient, the health care provider with priority set to 1, and the health care provider with priority set to 2. The patient and the first two notified health care providers do not acknowledge to the alert for some reason. The health care center does not receive ACK message until the third health care provider is notified with the alert and the patient’s condition is confirmed.

( ) ( ) ( )[ ]

( ) ( ) ( )[ ]smslatencycriticalurgentp

worst

smslatencycriticalurgentp

TnTnTTnt

TnTnTTn

×++×++×+<<

×++×−++×+

21

211 (3)

where n as described above is the number of health care providers to provide different emergency health care service in different levels, and Tcritical is the alert interval of critical alert automatically initiated by the system to reduce the notification time to health care providers in following levels if first level heath care providers do not respond to health care center within Turgent.

Fig. 12. Health care scenario for multiple health care providers.

TABLE III EXPERIMENTAL RESULTS OF AVERAGE LATENCY OF SHORT MESSAGE

TRANSMISSION

Test circumstance Average transmission time* (s) A1 (same TC/same BS) 6.40 A2 (same TC/same BS) 4.36 B (same TC/different BSs) 13.08 C (different TCs/different BSs) 17.36

*Average transmission time of 10 times experiments. A represents same telecom company (TC) with same base station (BS). A1: Chunghwa Telecom A2: KG Telecom B represents same TC with different BSs. C represents different TCs with different BSs.


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Table III lists the experimental results of short message transmission time for different telecoms and different base stations [10]. The results show that the best and worst time latency of Tsmslatency is 4.36 s and 17.36 s respectively. Take the three health care providers in different emergency levels in Fig. 12 as an example and assume the related parameters as Tp: 1 s, Turgent: 10 min and Tcritical: 3 min. From (2) and (3) we can derive that the patient can get health care as soon as 9.72 s after the alert is initiated and the back-end health care center can receive response messages from the first level health care provider within 10 min and 9.72 s. The patient will receive health care no later than 17 min and 30.8 s after the alert is initiated and the back-end health care center will receive related response messages from health care providers in the third level within 20 min and 30.8 s.

B. Evaluation of measurement accuracy of mobile care devices The front-end mobile care devices in our proposed mobile

care system include wrist-worn wireless Bluetooth hemadynamometer and ECG signal extraction devices. The extracted physiological signals are transmitted to the Bluetooth mobile phone carried by the patient via Bluetooth modules and are then processed by the simple built-in symptom recognition software module in mobile phone described in Section IV to differentiate whether it is abnormal to proceed with following system work flow. The accuracy of blood pressure measurement of Bluetooth hemadynamometer and the correctness of R-wave detection used in HR recognition are thus crucial for the reliability of the whole mobile care system.

For the accuracy of Bluetooth hemadynamometer that we designed and implemented, the average accuracy compared to traditional hemadynamometer is 4.125 mmHg and 3.967 mmHg for the systolic and dialectic pressure respectively [9]. The “Modified So and Chan” R-wave detection algorithm used in HR recognition has also been verified by [18] which shows that the average correctness of R-wave detection is 95%. With the accuracy of Bluetooth hemadynamometer and the correctness of R-wave detection algorithm, the reliability of the whole system can be further raised by reducing the probability of false emergency alert messages.

C. Questionnaire Survey and Evaluation of System Costs To further verify the feasibility of our mobile care system, the

prototype system is initially set up in Taipei Municipal Wan Fang Hospital, a medical center in Taipei city, Taiwan. Twenty-one professional medical personnel have used our system for testing. The measured average transmission latency for alert messages is 6.5 ± 2 s (with same telecoms and same base stations and n = 1). Furthermore, via the questionnaire survey to the twenty-one professional medical personnel [9], 95% of the medical personnel agree to collect and monitor the physiological information by using mobile care devices since it can reduce the usage and thus the cost of medical resources, and to provide reference basis for further medical treatment and provide long distance health care services.

As for the cost of our system, if we take the mobile care system prototype for hypertension patients implemented in this paper as an example, the cost for Bluetooth wireless hemadynamometer is NT$3,000 (about US$91). Nokia 7610 mobile phone costs only NT$2,000 if bundled with a two-year contract with a specific telecom. With the month fee of NT$200 for unlimited sending SMS within the same telecom network, the capital cost for the system set up is about NT$5,000 and the operating cost is only NT$200. Therefore using our proposed system can increase additive value of personal mobile care service without sacrificing original communication capability of mobile phones and without increasing financial burden to the patients.

VII. DISCUSSIONS AND CONCLUSIONS It is usually necessary to monitor and record multiple

physiological parameters (such as variation and abnormal conditions of percentage saturation of haemoglobin (SpO2), blood pressure, and HR) of chronic patients as the base data for analysis and tracking of the patients’ conditions and for provision of medical treatments. For users of our devices, due to the high probability of a cardiovascular disease lead by irregularity in HR, it is necessary to monitor the users’ ECG signals in long term. Similarly, for patients with cardiopulmonary diseases, it is necessary to monitor the patients’ SpO2 values by using oximetry. It is usually the case that patients self health care or go to the hospital after the patients feel uncomfortable which often highly increases the possibility of accidents. In addition, currently most health care devices are of large form factor and are for limited health care area which would reduce the desire of usage and quality of everyday life of the patient. The concept of mobile care service is thus to overcome the foregoing restrictions to reduce the volume of health care devices and to prevent interfering with patients’ daily life and still be able to provide long-term monitoring health care services. We thus propose to use a commercial mobile phone as the processing core for symptom recognition and alert message generation in collaboration of physiological signal extraction devices with wireless transmission capability and back-end health care center as a platform for message processing and data storage to construct an intelligent mobile care system with alert mechanism.

This paper proposes a role-based mobile health care system for chronic patients with an integration of multiple physiological parameter extraction devices. For the personal mobile device construction as mobile health care system front-end, physiological parameter extraction devices and mobile phones as personal mobile gateways are designed and constructed separately. The separation in design leads to three major advantages: high flexibility in architecture; good expandability in functions; and simplicity in hardware design. By using mobile phones as integration devices and utilizing program to design software modules with various functions, personal mobile devices not only are powerful and flexible in functions but also provide a shortcut to the goal. It reduces both the time and cost needed for system development.


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The alert mechanism and management constructed in health care center let health care providers be able to actively provide health care services any time anywhere compared to the traditional way in waiting for patients passively in hospitals or in health care centers. If something emergent happens, health care providers can assist instantly, and can provide further service of rescue and medical treatment if necessary. Alert mechanism supports different urgency levels and provides different priorities to multiple health care providers to utilize automatic alert urgency strategy to automatically notify the right persons at the right time in sequence which could ensure the accuracy of information and the completeness of notification. This can save the medical resource without sacrificing any need of health care to the patient. By utilizing alert mechanism, our system becomes an omnibearing intelligent mobile health care system to improve the quality of health care and to construct a complete intelligent health care chain. To verify the performance of our proposed architecture, we implement a prototype system for testing and evaluation. The results of our experiments show that our proposed system architecture can indeed provide tele- and mobile health care services, and are thus feasible and practical.

ACKNOWLEDGMENT The authors would like to thank the reviewers for helpful

comments, and Mr. Ming-Shiu Liu and Mr. Chun-Chung Chen for their help in the system implementation of this paper. The authors also wish to thank Dr. Yu-Chuan Li, vice-president of Taipei Municipal Wan Fang Hospital, Taipei, Taiwan, R.O.C., for his clinical advice and help.

REFERENCES [1] R.-G. Lee, H.-S. Chen, C.-C. Lin, K.-C. Chang, and J.-H. Chen, “Home

telecare system using cable television plants—an experimental field trial,” IEEE Trans. Inform. Technol. Biomed., vol. 4, no. 1, pp. 37–44, Mar. 2000.

[2] A. I. Hernández, F. Mora, G. Villegas, G. Passariello, and G. Carrault, “Real-time ECG transmission via Internet for nonclinical applications,” IEEE Trans. Inform. Technol. Biomed., vol. 5, no. 3, pp. 253–257, Sept. 2001.

[3] S. Guillén, M. T. Arredondo, V. Traver, J. M. García, and C. Fernández, “Multimedia telehomecare system using standard TV set,” IEEE Trans. Biomed. Eng., vol. 49, no. 12, pp.1431–1437, Dec. 2002.

[4] F. Axisa, P. M. Schmitt, C. Gehin, G. Delhomme, E. McAdams, and A. Dittmar, “Flexible technologies and smart clothing for citizen medicine, home healthcare, and disease prevention,” IEEE Trans. Inform. Technol. Biomed., vol. 9, no. 3, pp. 325–336, Sept. 2005.

[5] Y.-H. Lin, I.-C. Jan, P. C.-I. Ko, Y.-Y. Chen, J.-M. Wong, and G.-J. Jan, “A wireless PDA-based physiological monitoring system for patient transport,” IEEE Trans. Inform. Technol. Biomed., vol. 8, no. 4, pp. 439– 447, Dec. 2004.

[6] U. Anliker, J. A. Ward, P. Lukowicz, G. Tröster, F. Dolveck, M. Baer, F. Keita, E. B. Schenker, F. Catarsi, L. Coluccini, A. Belardinelli, D. Shklarski, M. Alon, E. Hirt, R. Schmid, and M. Vuskovic, “AMON: a wearable multiparameter medical monitoring and alert system,” IEEE Trans. Inform. Technol. Biomed., vol. 8, no. 4, pp. 415–427, Dec. 2004.

[7] M. F. A. Rasid and B. Woodward, “Bluetooth telemedicine processor for multichannel biomedical signal transmission via mobile cellular networks,” IEEE Trans. Inform. Technol. Biomed., vol. 9, no. 1, pp. 35– 43, Mar. 2005.

[8] E. Kafeza, D. K. W. Chiu, S. C. Cheung, and M. Kafeza, “Alerts in mobile healthcare applications: requirements and pilot study,” IEEE Trans. Inform. Technol. Biomed., vol. 8, no. 2, pp. 173–181, June 2004.

[9] R.-G. Lee, C.-C. Hsiao, C.-C. Chen, and M.-H. Liu, “A mobile-care system integrated with Bluetooth blood pressure and pulse monitor, and cellular phone,” IEICE Trans. Inform. Syst., vol. E89-D, no. 5, pp. 1702– 1711, May 2006.

[10] R.-G. Lee, C.-C. Hsiao, K.-C. Chen, and M.-H. Liu, “An intelligent diabetes mobile care system with alert mechanism,” Biomed. Eng. Applicat., Basis Commun., vol. 17, no. 4, pp. 186–192, Aug. 2005.

[11] R.-G. Lee, C.-C. Lai, S.-S. Chiang, H.-S. Liu, C.-C. Chen, and G.-Y. Hsieh, “Design and implementation of a mobile-care system over wireless sensor network for home healthcare applications,” in Proc. 28th Annu. Int. Conf. IEEE-EMBS, New York, Aug. 30–Sept. 3, 2006, pp. 6004–6007.

[12] Weekly of Business Next Digital Times. [Online]. Available: http://www. bnext.com.tw

[13] Q. H. Mahmoud, Learning Wireless Java, Sebastopol, CA: O'Reilly, 2002.

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Ren-Guey Lee (M’06) was born in 1965. He received the M.S. degree from Department of Electrical Engineering, National Chen Kung University (NCKU), Taiwan, in 1989, and the Ph.D. degree from Department of Electrical Engineering, National Taiwan University (NTU), in 2000. Since 2002, he has been with the Department of Electronic Engineering and Graduate Institute of Computer and Communication Engineering, National Taipei University of Technology (NTUT), where he is currently an Associate Professor. His research

interests include medical informatics, telecare and mobile care system, and wireless sensor network for biomedical applications.

Kuei-Chien Chen received the B.S. and M.S. degrees in electrical engineering form the National Taiwan University of Science and Technology (NTUST) in 1985 and 1990 respectively. In 2004, he joined the Ph.D. program in the Graduate Institute of Computer and Communication Engineering at the National Taipei University of Technology (NTUT), Taipei, Taiwan. He is currently a lecturer in the Lunghwa University of Science and Technology (LHU), Taoyuan, Taiwan. His research interests include Bluetooth technology,

sensor network design, and telemedicine applications.


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Chun-Chieh Hsiao received the M.S. degree in Electrical and Computer Engineering from State University of New York at Buffalo, USA in 1990. During 1991-1993, he stayed in Computer and Communication Laboratory (CCL), Industrial Technology Research Institute (ITRI) of Taiwan to focus on the research and development of advanced computer graphics systems. From 1993 to 2003, he was with Department of Electrical Engineering in

Lunghwa University of Science and Technology (LHU). Since 2003, he has been with Department of Computer Information and Network Engineering in LHU. His research interests include telecare and mobile-care system, wireless sensor network for biomedical applications, and advanced computer systems.

Chwan-Lu Tseng graduated from the National Taipei Institute of Technology in 1985 and received the M.S. and Ph.D. degrees from National Taiwan University (NTU) in 1991 and 1995, respectively, both in electrical engineering. Since 2000, he has been an Associate Professor in the Department of Electrical Engineering, National Taipei University of Technology (NTUT). His research interests include signal processing, automation, robust control theory and its applications. He is a member of the Phi Tau Phi Scholastic Honor Society at NTU.

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