Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care

Area of Science:

• Biomedical Engineering
• Health Informatics
• Ubiquitous Computing

Background:

• Increasing life expectancy leads to a greater prevalence of chronic diseases.
• Information and Communication Technology (ICT) advancements are crucial for effective healthcare.
• Telemedicine and health sensors are vital for patient engagement and remote monitoring.

Purpose of the Study:

• To evaluate a rapid prototyping solution for merging health sensor data.
• To compare the performance of Raspberry Pi 3 versus a Personal Computer for telemedicine applications.
• To assess the suitability of portable technologies for integrating wearable sensors in scalable telemedicine systems.

Main Methods:

• Utilized five health sensors and two low-cost computing components (Arduino and Raspberry Pi).
• Implemented data integration using a choreography engine and web services.
• Compared two deployment scenarios (Raspberry Pi 3 and Personal Computer) based on data transmission latency and loss.

Main Results:

• Raspberry Pi demonstrated lower latency (0.0175 ± 0.149 s) compared to Personal Computer (0.051 ± 0.0035 s).
• Both setups showed comparable performance in data transmission for N=300.
• Portable devices were found to be suitable for transmitting and analyzing biometric signals.

Conclusions:

• Portable devices, specifically Raspberry Pi, are viable for scalable telemedicine systems.
• The rapid prototyping solution effectively integrates wearable sensor data.
• This approach supports remote patient monitoring and self-management of chronic conditions.