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. 2013 Dec 2;13(12):16451-73.
doi: 10.3390/s131216451.

Mobile cloud-computing-based healthcare service by noncontact ECG monitoring

Ee-May Fong  1 , Wan-Young Chung
Affiliations

Mobile cloud-computing-based healthcare service by noncontact ECG monitoring

Ee-May Fong et al. Sensors (Basel). .

Abstract

Noncontact electrocardiogram (ECG) measurement technique has gained popularity these days owing to its noninvasive features and convenience in daily life use. This paper presents mobile cloud computing for a healthcare system where a noncontact ECG measurement method is employed to capture biomedical signals from users. Healthcare service is provided to continuously collect biomedical signals from multiple locations. To observe and analyze the ECG signals in real time, a mobile device is used as a mobile monitoring terminal. In addition, a personalized healthcare assistant is installed on the mobile device; several healthcare features such as health status summaries, medication QR code scanning, and reminders are integrated into the mobile application. Health data are being synchronized into the healthcare cloud computing service (Web server system and Web server dataset) to ensure a seamless healthcare monitoring system and anytime and anywhere coverage of network connection is available. Together with a Web page application, medical data are easily accessed by medical professionals or family members. Web page performance evaluation was conducted to ensure minimal Web server latency. The system demonstrates better availability of off-site and up-to-the-minute patient data, which can help detect health problems early and keep elderly patients out of the emergency room, thus providing a better and more comprehensive healthcare cloud computing service.

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Figures

Figure 1.
Figure 1.
Comparison between the conventional and noncontact capacitive-coupled ECG measurement methods.
Figure 2.
Figure 2.
Body–electrode interface that forms the coupling capacitance.
Figure 3.
Figure 3.
System design of mobile healthcare and cloud-based service for noncontact ECG monitoring system, which consists of a data acquisition module, a mobile system, and a cloud computing Web server module.
Figure 4.
Figure 4.
Flowchart of the data acquisition module.
Figure 5.
Figure 5.
Bluetooth communication between the transmitter and mobile devices.
Figure 6.
Figure 6.
Peak detection of the ECG signal.
Figure 7.
Figure 7.
Flowchart of mobile application for health status real-time monitoring and personalized life assistant.
Figure 8.
Figure 8.
Health monitoring cloud computing architecture where health data from multiple locations are monitored via a cloud server.
Figure 9.
Figure 9.
Client-server model. The clients request and receive service from the centralized server.
Figure 10.
Figure 10.
(a) Uploading process from the mobile device to the Web server, which involves the creation of a database table and insertion of the health data into the Web server database; (b) Downloading process from the Web server to the client side where the clients retrieve the health data from the Web server database.
Figure 11.
Figure 11.
Setup of the ECG real-time monitoring environment.
Figure 12.
Figure 12.
(a) ECG signals measured with standard ECG measurement; (b) ECG signal obtained using non-contact ECG measurement.
Figure 13.
Figure 13.
Display interface on a mobile device with ECG plotting, heart beat rate, location, and warning feedback for abnormal heart beat rate.
Figure 14.
Figure 14.
(a) QR code on prescribed medicine; (b) Personalized QR code medication list; (c) QR code scanning on mobile application; (d) Main screen for medication reminder; (e) Medication alert reminder; (f) BMI calculator; (g) Symptom checker.
Figure 15.
Figure 15.
(a) Table AllHealthStatusDate in a Web server SQL database to store the date and time, and the date table name; (b) Table Datetablename (HealthStatus20130305) in Web server SQL database to store the date and time, HR, and location; (c) Synchronization of health data between Web server database and the Web page. HR is synchronized in a cloud-based architecture system.
Figure 15.
Figure 15.
(a) Table AllHealthStatusDate in a Web server SQL database to store the date and time, and the date table name; (b) Table Datetablename (HealthStatus20130305) in Web server SQL database to store the date and time, HR, and location; (c) Synchronization of health data between Web server database and the Web page. HR is synchronized in a cloud-based architecture system.
Figure 16.
Figure 16.
Operational Web page for the noncontact health system for real-time health evaluation wherever a cellular network coverage is present. (a) JavaScript dropdown list to view the history and summary of the HR on the Web page; (b) HR records and HR plotting on the Web page.
Figure 17.
Figure 17.
Web page performance evaluation test.
Figure 18.
Figure 18.
Evaluation in the waterfall and connection views.
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