Key result
Cloud-based noncontact ECG monitoring achieves ~3-second load times for remote health tracking.
The proposed system provides a feasible, low-latency architecture for continuous, noncontact remote ECG monitoring using mobile and cloud technologies.
May support remote noncontact ECG feasibility; leaves open clinical outcome validation before practice integration.
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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Fong et al. (2013) studied Cardiovascular disease monitoring. Mobile cloud-computing-based healthcare service by noncontact ECG monitoring was evaluated on Web page performance latency. The mobile cloud-computing-based healthcare service with noncontact ECG monitoring demonstrated a First View load time of 2.833 seconds, enabling seamless remote health tracking.
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