Wearables Meet IoT: Synergistic Personal Area Networks (SPANs)

Area of Science:

• Integrative Health Technologies
• Internet of Things (IoT) in Healthcare
• Wearable Sensor Networks

Background:

• Wearable monitoring and mobile health (mHealth) have transformed healthcare delivery.
• The proliferation of Internet of Things (IoT) devices enables new forms of interaction and data collection.
• Existing systems often lack seamless integration between diverse sensors.

Purpose of the Study:

• To explore the applications and feasibility of Synergistic Personal Area Networks (SPANs).
• To demonstrate how integrating 'smart stuff' with wearables enhances data collection and analysis.
• To enable continuous, opportunistic monitoring of vital signs and user activity.

Main Methods:

• Development of dynamic, ad-hoc personal area networks (SPANs) spanning multiple domains.
• Integration of sensors from wearable devices (e.g., smartwatch) and everyday objects (e.g., smart water bottle).
• Synergistic processing of data from multiple, disparate sensors.

Main Results:

• SPANs facilitate the collection of vital signs through routine interactions with smart objects.
• Synergistic processing enables the assessment of new parameters like pulse wave velocity (PWV) and blood pressure.
• User identification and automatic annotation of events/records are achieved through integrated sensor data.

Conclusions:

• SPANs offer a dynamic 'opportunistic bubble' for seamless sensor integration and health monitoring.
• Continuous, long-term monitoring via SPANs can lead to improved diagnostics and personalized health feedback.
• This approach supports a proactive approach to health and wellbeing without additional user effort.